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1.329.397s.478.609.478 1.033v.662h-2.18c-1.329 0-2.366.265-3.136.821s-1.143 1.325-1.143 2.305a3.1 3.1 0 0 0 .372 1.483 2.56 2.56 0 0 0 1.09 1.033c.478.265 1.037.371 1.648.371.824 0 1.489-.212 2.047-.636zm-2.233-1.669a1.08 1.08 0 0 1-.425-.874 1.12 1.12 0 0 1 .585-1.033c.372-.239.957-.371 1.701-.371h1.595v.371c0 .318-.08.636-.266.98a2.35 2.35 0 0 1-.824.874c-.372.238-.771.344-1.249.344-.452.027-.824-.079-1.116-.291zm11.031 2.093V14.57c0-1.086.239-1.907.691-2.464s1.09-.848 1.861-.848a3.3 3.3 0 0 1 1.037.159v-2.41c-.159-.053-.319-.079-.478-.106s-.346-.026-.532-.026c-.611 0-1.143.212-1.568.636s-.771 1.033-.983 1.775V8.954h-2.499v9.748h2.472v.026zm7.681 0v-3.152l.904-.848 2.924 4h2.977l-4.173-5.695 4.093-4.053h-3.136l-3.562 3.444V5.272h-2.472v13.457zm10.819 0V5.272h-2.499v13.457zm3.827 3.629c.93 0 1.675-.185 2.259-.556s1.064-1.033 1.462-1.96l4.492-10.861h-2.578l-2.631 6.808-2.712-6.808h-2.578l4.014 9.722-.213.503c-.133.318-.292.583-.531.715-.213.159-.559.238-1.011.238h-2.073v2.199zM144.092 24a.56.56 0 0 1-.478-.291c-.08-.185-.08-.371.053-.53l5.662-7.762-9.915 4.027c-.08.027-.133.053-.212.053a.52.52 0 0 1-.505-.371c-.08-.212.026-.45.212-.583l8.719-5.113-15.337-.874a.525.525 0 0 1-.505-.53.52.52 0 0 1 .505-.53l15.337-.874-8.719-5.113c-.186-.132-.292-.371-.212-.583s.265-.371.505-.371c.079 0 .132.026.212.053l9.915 4.026-5.662-7.788c-.106-.159-.133-.371-.053-.53a.5.5 0 0 1 .478-.291c.133 0 .266.053.372.159l11.271 11.205c.159.159.239.397.239.609s-.08.424-.239.609l-11.271 11.232a.53.53 0 0 1-.372.159z"></path></g><defs><clipPath id="brand-light_svg__a"><path fill="#fff" d="M0 0h156v24H0z"></path></clipPath></defs></svg></a></div><div class="oldstyles-module__hgjkrG__mainNavGroup styles-module__stVVvG__mainNavGroup main-nav-container" id="mainNavigation"><nav aria-label="Main navigation" class="oldstyles-module__hgjkrG__mainNav"><div class="styles-module__wa_yaW__mainNavParent nav--main-nav-parent"><div class="moreStyles-module__udQsYq__parentNavItem 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https://images.prismic.io/launchdarkly-marketingsite/agpUVqYofJOwHTu-_icon-main-nav--CodeControl.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpUVqYofJOwHTu-_icon-main-nav--CodeControl.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><div class="styles-module__9d2Dpq__productLinkTextContainer"><h6>CodeControl</h6><p>Ship confidently, with automated control built in.</p></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-products-agentcontrol" href="/platform/agent-control/"><div class="styles-module__9d2Dpq__productLinkInner"><div class="styles-module__9d2Dpq__linkInnerIconContainer"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpUVaYofJOwHTu9_icon-main-nav--AgentControl.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpUVaYofJOwHTu9_icon-main-nav--AgentControl.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpUVaYofJOwHTu9_icon-main-nav--AgentControl.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><div class="styles-module__9d2Dpq__productLinkTextContainer"><h6>AgentControl</h6><p>One place to keep your agent behavior under control.</p></div></div></a></div></div><div class="styles-module__9d2Dpq__bookDemoCta"><a class="styles-module__d4f9cW__button styles-module__d4f9cW__variant_lime_outline styles-module__d4f9cW__size_default styles-module__9d2Dpq__bookDemoCtaLink" target="_self" tabindex="0" data-analytics="nav-products-book-a-demo" href="/request-a-demo/"><span class="styles-module__d4f9cW__label">Book a demo</span><span class="styles-module__d4f9cW__arrowBox false"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none" class="styles-module__d4f9cW__arrow" aria-hidden="true"><path fill="currentColor" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></span></a></div></div><div class="overview-wrapper styles-module__9d2Dpq__linksWrapper"><div><p class="styles-module__9d2Dpq__categoryTitle">How it works</p><div class="overview styles-module__9d2Dpq__linksContainer"><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-overview-platform-overview" href="/how-it-works/platform/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agwNv6YofJOwHWkd_platform-overview-icon.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agwNv6YofJOwHWkd_platform-overview-icon.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agwNv6YofJOwHWkd_platform-overview-icon.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Platform overview</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-overview-feature-flags" href="/how-it-works/feature-flags/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpNAKYofJOwHTuE_icon-main-nav--FeatureManagement.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpNAKYofJOwHTuE_icon-main-nav--FeatureManagement.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpNAKYofJOwHTuE_icon-main-nav--FeatureManagement.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Feature flags</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-overview-observability" href="/how-it-works/observability/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpNA6YofJOwHTuH_icon-main-nav--Observability.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpNA6YofJOwHTuH_icon-main-nav--Observability.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpNA6YofJOwHTuH_icon-main-nav--Observability.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Observability</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-overview-experimentation" href="/how-it-works/experimentation/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpM_6YofJOwHTuD_icon-main-nav--Experimentation.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpM_6YofJOwHTuD_icon-main-nav--Experimentation.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpM_6YofJOwHTuD_icon-main-nav--Experimentation.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Experimentation</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-overview-agent-integrations" href="/how-it-works/agent-integrations/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpM_qYofJOwHTuC_icon-main-nav--Agentintegrations.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpM_qYofJOwHTuC_icon-main-nav--Agentintegrations.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpM_qYofJOwHTuC_icon-main-nav--Agentintegrations.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Agent integrations</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-overview-integrations" href="/integrations/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpNAqYofJOwHTuG_icon-main-nav--Integrations.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpNAqYofJOwHTuG_icon-main-nav--Integrations.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpNAqYofJOwHTuG_icon-main-nav--Integrations.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Integrations</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-overview-architecture" href="/how-it-works/platform-architecture/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpNAaYofJOwHTuF_icon-main-nav--Infrastructure.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpNAaYofJOwHTuF_icon-main-nav--Infrastructure.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpNAaYofJOwHTuF_icon-main-nav--Infrastructure.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Architecture</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a></div></div></div></div></div></div></div></div></div><div class="styles-module__wa_yaW__mainNavParent nav--main-nav-parent"><div class="moreStyles-module__udQsYq__parentNavItem styles-module__wa_yaW__parentNavItem main-nav-parent-nav-item"><div class="moreStyles-module__udQsYq__navItem styles-module__wa_yaW__navItem" id="solutions" data-analytics="nav-solutions" role="button" tabindex="0"><span class="moreStyles-module__udQsYq__navItemTitle styles-module__wa_yaW__navItemTitle main-nav-title">Solutions</span><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none" class="styles-module__wa_yaW__mobileCaretClosed "><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div><div class="
moreStyles-module__udQsYq__dropdown
main-nav-dropdown
solutions
styles-module__wa_yaW__dropdown
"><div class="moreStyles-module__udQsYq__dropdownContainer styles-module__wa_yaW__dropdownContainer main-nav-dropdown-container"><div class="moreStyles-module__udQsYq__linksContainer styles-module__wa_yaW__linksContainer"><div class="styles-module__wa_yaW__linksContainerInner"><div class="by-team-wrapper styles-module__9d2Dpq__linksWrapper"><div><p class="styles-module__9d2Dpq__categoryTitle">By Use Case</p><div class="by-team styles-module__9d2Dpq__linksContainer"><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-team-release-ai-built-code" href="/solutions/release-ai-built-code/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpOrqYofJOwHTuK_icon-main-nav--ReleaseAI-BuiltCode.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpOrqYofJOwHTuK_icon-main-nav--ReleaseAI-BuiltCode.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpOrqYofJOwHTuK_icon-main-nav--ReleaseAI-BuiltCode.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Release AI-built code</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-team-control-ai-agents" href="/solutions/control-ai-agents/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpOrKYofJOwHTuI_icon-main-nav--ControlAIAgents.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpOrKYofJOwHTuI_icon-main-nav--ControlAIAgents.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpOrKYofJOwHTuI_icon-main-nav--ControlAIAgents.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Control AI agents</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-team-optimize-ai-performance-cost" href="/solutions/optimize-ai-performance/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpOraYofJOwHTuJ_icon-main-nav--OptimizeAIPerformance%26Cost.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpOraYofJOwHTuJ_icon-main-nav--OptimizeAIPerformance%26Cost.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpOraYofJOwHTuJ_icon-main-nav--OptimizeAIPerformance%26Cost.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Optimize AI performance &amp; cost</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-team-self-heal-systems" href="/solutions/self-heal-systems/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpOsKYofJOwHTuM_icon-main-nav--Self-HealSystems.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpOsKYofJOwHTuM_icon-main-nav--Self-HealSystems.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpOsKYofJOwHTuM_icon-main-nav--Self-HealSystems.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Self-heal systems</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-team-run-experiments" href="/solutions/run-experiments/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpOr6YofJOwHTuL_icon-main-nav--RunExperiments.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpOr6YofJOwHTuL_icon-main-nav--RunExperiments.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpOr6YofJOwHTuL_icon-main-nav--RunExperiments.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Run experiments</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a></div></div></div><div class="by-industry-wrapper styles-module__9d2Dpq__linksWrapper"><div><p class="styles-module__9d2Dpq__categoryTitle">By Team</p><div class="by-industry styles-module__9d2Dpq__linksContainer"><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-industry-ai-engineers" href="/persona/ai-engineers/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpQmaYofJOwHTuS_icon-main-nav--AIEngineer.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpQmaYofJOwHTuS_icon-main-nav--AIEngineer.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpQmaYofJOwHTuS_icon-main-nav--AIEngineer.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>AI engineers</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-industry-developers" href="/persona/development-teams/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpQmqYofJOwHTuT_icon-main-nav--Developers.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpQmqYofJOwHTuT_icon-main-nav--Developers.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpQmqYofJOwHTuT_icon-main-nav--Developers.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Developers</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-industry-devops-sre" href="/persona/devops-site-reliability-engineer-teams/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpQm6YofJOwHTuU_icon-main-nav--DevOps-SRE.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpQm6YofJOwHTuU_icon-main-nav--DevOps-SRE.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpQm6YofJOwHTuU_icon-main-nav--DevOps-SRE.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>DevOps &amp; SRE</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-industry-product-managers" href="/persona/product-managers/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/agpQnaYofJOwHTuW_icon-main-nav--ProductManagers.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, https://images.prismic.io/launchdarkly-marketingsite/agpQnaYofJOwHTuW_icon-main-nav--ProductManagers.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840 2x" src="https://images.prismic.io/launchdarkly-marketingsite/agpQnaYofJOwHTuW_icon-main-nav--ProductManagers.png?auto=format%2Ccompress&amp;fit=max&amp;w=3840"/></div><span>Product managers</span><div class="styles-module__9d2Dpq__arrowIcon"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none"><path fill="#fff" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></div></div></a><a class="styles-module__9d2Dpq__link " target="_self" tabindex="0" data-analytics="nav-by-industry-data-scientists" href="/persona/data-scientists/"><div class="styles-module__9d2Dpq__linkWrapper"><div class="styles-module__9d2Dpq__linkIcon"><img alt="" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly-marketingsite/8Rpfg-gh7BMefouu_persona-data-scientist-icon-nav.png?auto=format%2Ccompress&amp;fit=max&amp;w=1920 1x, 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class="styles-module__xmAU9a__container"><div class="styles-module__xmAU9a__breadcrumbs"><a target="_self" tabindex="0" href="/blog/">Blog</a><img class="styles-module__xmAU9a__breadcrumbArrow" src="https://launchdarkly-marketingsite.cdn.prismic.io/launchdarkly-marketingsite/Z5UufJbqstJ992SK_right-arrow-padded.svg" alt="Right arrow" loading="lazy"/><a target="_self" tabindex="0" href="/blog/category/industry-insights/">Industry Insights</a><div class="styles-module__xmAU9a__thirdBreadcrumb"><img class="styles-module__xmAU9a__breadcrumbArrow" src="https://launchdarkly-marketingsite.cdn.prismic.io/launchdarkly-marketingsite/Z5UufJbqstJ992SK_right-arrow-padded.svg" alt="Right arrow" loading="lazy"/><span class="styles-module__xmAU9a__titleBreadcrumb">The Fallacy of Move Fast and Break Things</span></div></div><div class="styles-module__xmAU9a__barWrapper"><div class="styles-module__xmAU9a__barContainer"><div class="styles-module__xmAU9a__searchBarContainer "><div 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class="styles-module__HXqOTa__blogContainer"><div class="styles-module__HXqOTa__header"><div class="styles-module__HXqOTa__content"><p class="styles-module__J0n02W__variant_textXsmallCaps styles-module__J0n02W__paragraph styles-module__J0n02W__color_gray04 styles-module__J0n02W__weight_medium">Mar 17, 2020</p><h1 class="styles-module__J0n02W__variant_h3 styles-module__J0n02W__weight_semibold styles-module__HXqOTa__blogTitle">The Fallacy of Move Fast and Break Things</h1><div class="styles-module__HXqOTa__authorContainer"><div class="styles-module__5zAopa__author "><a class="styles-module__5zAopa__authorImage" target="_self" tabindex="0" href="/blog/author/dparzych/"><div class="styles-module__nv1SBG__container styles-module__nv1SBG__ratio_natural styles-module__nv1SBG__object-fit_cover prismic-image post-details-author-image"><img alt="" loading="lazy" width="2000" height="1499" decoding="async" data-nimg="1" class="styles-module__nv1SBG__image" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly/a4a4f6c4-a269-4cc9-b3f0-cbcc8acbfae6_604d1814-4d37-4e0e-ac1b-ce47284df5be_KHH_Dawn_%2B39.png?auto=compress%2Cformat&amp;rect=0%2C0%2C878%2C658&amp;w=2048&amp;fit=max&amp;q=80 1x, https://images.prismic.io/launchdarkly/a4a4f6c4-a269-4cc9-b3f0-cbcc8acbfae6_604d1814-4d37-4e0e-ac1b-ce47284df5be_KHH_Dawn_%2B39.png?auto=compress%2Cformat&amp;rect=0%2C0%2C878%2C658&amp;w=3840&amp;fit=max&amp;q=80 2x" src="https://images.prismic.io/launchdarkly/a4a4f6c4-a269-4cc9-b3f0-cbcc8acbfae6_604d1814-4d37-4e0e-ac1b-ce47284df5be_KHH_Dawn_%2B39.png?auto=compress%2Cformat&amp;rect=0%2C0%2C878%2C658&amp;w=3840&amp;fit=max&amp;q=80"/></div></a><div class="styles-module__5zAopa__authorDetails"><a class="styles-module__5zAopa__authorName" target="_self" tabindex="0" href="/blog/author/dparzych/">Dawn Parzych</a><div class="styles-module__5zAopa__authorJobTitle">LaunchDarkly</div></div></div></div></div><div class="styles-module__nv1SBG__container styles-module__nv1SBG__ratio_natural styles-module__nv1SBG__object-fit_cover prismic-image styles-module__HXqOTa__featuredImage"><img alt="The Fallacy of Move Fast and Break Things" loading="eager" width="2000" height="1125" decoding="async" data-nimg="1" class="styles-module__nv1SBG__image" style="color:transparent" srcSet="https://images.prismic.io/launchdarkly/YzE4MzZjYTAtYTcyOS00OWU1LTlhYTQtZjA0MDIyMDc4NTZh_2020_03_blog_1920x1080_thefallacyofmovefastandbreakthings_v021x.jpg?auto=compress%2Cformat&amp;rect=0%2C0%2C1920%2C1080&amp;w=2048&amp;fit=max&amp;q=80 1x, https://images.prismic.io/launchdarkly/YzE4MzZjYTAtYTcyOS00OWU1LTlhYTQtZjA0MDIyMDc4NTZh_2020_03_blog_1920x1080_thefallacyofmovefastandbreakthings_v021x.jpg?auto=compress%2Cformat&amp;rect=0%2C0%2C1920%2C1080&amp;w=3840&amp;fit=max&amp;q=80 2x" src="https://images.prismic.io/launchdarkly/YzE4MzZjYTAtYTcyOS00OWU1LTlhYTQtZjA0MDIyMDc4NTZh_2020_03_blog_1920x1080_thefallacyofmovefastandbreakthings_v021x.jpg?auto=compress%2Cformat&amp;rect=0%2C0%2C1920%2C1080&amp;w=3840&amp;fit=max&amp;q=80"/></div></div><div class="styles-module__HXqOTa__staticBar"><div id="blog-progress-bar" class="styles-module__lQ92Cq__container"><div class="styles-module__lQ92Cq__progress" style="width:0%"></div></div></div><div class="styles-module__HXqOTa__blogMainContainer"><div class="styles-module__HXqOTa__body"><div class="styles-module__HXqOTa__blogContentWrapper"><article class="blog-post-main-content"><div data-ld-slice-index="0" data-ld-slice-type="wysiwyg"><div class="wysiwyg styles-module__yVDX7W__wysiwyg "><section class="style-module__REJINa__section style-module__REJINa__spacing_bottom_xl style-module__REJINa__spacing_top_xl section"><div class="wysiwyg-content"><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md"><em>*Originally published on <a href="https://devops.com/the-fallacy-of-move-fast-and-break-things/" target="_blank" tabindex="0" rel="nofollow noreferrer">DevOps.com</a>.</em></p><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">Ever since Mark Zuckerburg uttered the phrase “move fast and break things,” it has become the motto of many development teams. Companies wanting to be the next unicorn decided this must be the way to operate. The race was on to release more, ship faster, never stop. If moving slowly and methodically wasn&#x27;t working, doing more had to be the key to success.</p><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">These companies would cherry-pick statistics from reports such as the Accelerate: State of DevOps Report. The 2019 report showed elite companies have 46 times more frequent code deployments than low-performing teams and a 2,555 times faster lead time to move from code commit to deploy to support their initiatives to move faster.</p><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">The problem is moving fast doesn&#x27;t work across industries or for all teams. To effectively move fast, you need processes in place to support the velocity. The consequences of moving too fast and not being able to fix things when they break are high.</p><h3 class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_lg styles-module__5zGs1G__weight_medium styles-module__5zGs1G__spacing_bottom_xl">How we got here</h3><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">What has gotten us to the point where we are moving too fast? In short, we have. How do you feel when it takes months or a week for a PR to be resolved compared to hours or days? As consumers and end-users of software, our expectations are continually rising. We have to ship quickly because that is what we as consumers expect. As customers, we are pushing companies, which in turn push their employees to meet the increasing expectations.</p><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">What are the consequences when you try to move fast and not just break things, but fail?</p><ul class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md"><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm">It takes longer to resolve incidents.</li><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm">You lose customer confidence and sales.</li><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm">Employees burn out, and you have a high turnover rate.</li></ul><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">Let&#x27;s go back to the stats from the <a href="https://cloud.google.com/devops/state-of-devops/?utm_source=cloudblog" target="_blank" tabindex="0" rel="nofollow noreferrer">Accelerate: State of DevOps Report</a>. Yes, elite teams ship faster. But, their changes are 1/7 as likely to fail, and they recover from incidents 2,604 times faster than low-performing teams. It&#x27;s not just about moving fast and breaking things; it is about having the right systems and processes in place to support this way of working.</p><h3 class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_lg styles-module__5zGs1G__weight_medium styles-module__5zGs1G__spacing_bottom_xl">Setting yourself up for success</h3><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">You need two things to effectively move fast: a culture of psychological safety and smart investments in tooling. Employees need to feel empowered to speak up if things are moving too fast—if they are concerned about why a feature is being built and to identify gaps in the processes. They need to feel they won&#x27;t be blamed when something breaks. Building this requires empathy, open communication, and teamwork. This psychological safety is the foundation of being able to move quickly and quickly recover when things break.</p><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">Next up is selecting the right tooling and processes. Invest in tools that make things easier. Tools should be useful, usable, and change the underlying problems, not create more.</p><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">Think about the tools in place to quickly resolve incidents when something fails:</p><ul class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md"><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm">Observability and monitoring tools to identify and notify when things go wrong.</li><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm">Incident management tools to route, track, and escalate issues.</li><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm"><a target="_self" tabindex="0" href="/feature-management/">Feature management</a> tools to enable circuit breakers and load shedding to turn off features quickly.</li></ul><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">The culture and tools are part of the equation; the final piece is having the right processes in place to effectively use the tools and support the people.</p><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">What are some processes you can implement to enable safety at speed?</p><ul class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md"><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm">Schedule <a href="https://www.gremlin.com/community/tutorials/planning-your-own-chaos-day/" target="_blank" tabindex="0" rel="nofollow noreferrer">chaos days</a> to understand how things break and know how to fix them.</li><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm">Release features via <a target="_self" tabindex="0" href="/blog/release-management-flags-best-practices/">targeted rollouts, betas, or canary launches</a>.</li><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm"><a href="https://opensource.com/article/19/5/dont-test-production" target="_blank" tabindex="0" rel="nofollow noreferrer">Test code in production</a> without exposing it to all users.</li><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm">Configure <a target="_self" tabindex="0" href="/blog/operational-flags-best-practices/">operational feature flags</a> to dynamically change logging levels when an incident occurs.</li><li class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_sm"><a target="_self" tabindex="0" href="/blog/nine-experimentation-best-practices/">Run experiments</a> to gather feedback and ensure features are moving in the right direction before a release.</li></ul><p class="styles-module__5zGs1G__text styles-module__5zGs1G__variant_body styles-module__5zGs1G__size_md styles-module__5zGs1G__spacing_md">You should attempt to move fast, you should try to break things—but only when you have the right protections and processes in place. Using a combination of the right tools and processes, you can deliver more value faster without sacrificing quality or your employees&#x27; health.</p></div></section></div></div><div class="styles-module__HXqOTa__mobileCta"><h5 class="styles-module__HXqOTa__footerTitle">Like what you read?</h5></div></article></div></div><section class="styles-module__o_kpTq__sidebar"><div class="styles-module__o_kpTq__sidebarNewsletter"><div class="styles-module__yaWGhq__sidebarVersion undefined styles-module__yaWGhq__blogNewsletter "><div class="styles-module__yaWGhq__blogNewsletterSection"><div class="styles-module__yaWGhq__textContent"><img class="styles-module__yaWGhq__newsletterIcon" src="https://launchdarkly-marketingsite.cdn.prismic.io/launchdarkly-marketingsite/aimOzgeQX7-eXLr4_icon-bw--notification.svg" alt="Notification icon" loading="lazy"/><h5 class="styles-module__J0n02W__variant_h5 styles-module__J0n02W__weight_medium">Sign up for our newsletter</h5></div><div class="styles-module__yaWGhq__customForm" id="customNewsletterForm"><div class="styles-module__yaWGhq__formElements" id="customNewsletterFormElements"><input id="customNewsletterEmail" type="email" placeholder="Email address" aria-label="Email address" name="email" value=""/><button class="styles-module__d4f9cW__button styles-module__d4f9cW__variant_dark styles-module__d4f9cW__size_default styles-module__yaWGhq__subscribeButton" type="button"><span class="styles-module__d4f9cW__label">Subscribe</span><span class="styles-module__d4f9cW__arrowBox false"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="12" fill="none" class="styles-module__d4f9cW__arrow" aria-hidden="true"><path fill="currentColor" d="M11.283 11.714c.14-3.008 1.827-4.8 4.336-5.035V5.014C13.11 4.78 11.423 3.01 11.283 0L9.416.427A6 6 0 0 0 10.48 3.35c.622.853 1.325 1.408 2.128 1.664H0V6.68h12.608c-.803.256-1.506.81-2.128 1.685a6 6 0 0 0-1.064 2.902z"></path></svg></span></button><div class="styles-module__WD-Msa__tos sidebar-version-form-tos styles-module__yaWGhq__formTos styles-module__yaWGhq__sidebarVersionFormTos"><p>By supplying my contact information, I authorize LaunchDarkly to contact me with personalized marketing communications about our products and services. 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Companies wanting to be the next unicorn decided this must be the way to operate. The race was on to release more, ship faster, never stop. If moving slowly and methodically wasn't working, doing more had to be the key to success.\",\"spans\":[]},{\"type\":\"paragraph\",\"text\":\"These companies would cherry-pick statistics from reports such as the Accelerate: State of DevOps Report. The 2019 report showed elite companies have 46 times more frequent code deployments than low-performing teams and a 2,555 times faster lead time to move from code commit to deploy to support their initiatives to move faster.\",\"spans\":[]},{\"type\":\"paragraph\",\"text\":\"The problem is moving fast doesn't work across industries or for all teams. To effectively move fast, you need processes in place to support the velocity. 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is transforming the home and community care industry with an end-to-end platform that helps improve patient outcomes for home-based care agencies. They serve over 700 care organizations and thousands of users across North America, Australia, and New Zealand. As their platform and customer base have grown, they’ve encountered a new challenge—how to scale software releases without disrupting care professionals who rely on their platform for critical healthcare service delivery.\",\"spans\":[{\"start\":0,\"end\":9,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://alayacare.com/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"In a recent blog post, \\\"Establishing a Customer-Friendly Pace of Change Without Sacrificing DevOps Practices,\\\" Jean-Philippe Boudreault, Director of Product and Engineering, shared how they’ve adapted their approach to software deployment. With LaunchDarkly, they’ve reduced incidents, increased developer productivity, and boosted satisfaction ratings. 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Ally Financial—the largest all-digital FDIC-insured bank in the United States—recognized this need, and built an ambitious plan to modernize their software release process. Nathan Gray, Ally’s Director of Digital Engineering Operations, and Jeremy Cox, the company’s Director Lead of Software Engineering, spoke at the LaunchDarkly Galaxy Conference in 2024 about how they collaborated with LaunchDarkly to build faster, safer software releases.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Ally's innovative growth\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"To truly understand Ally’s trajectory, let’s take a quick look at its history.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Ally Financial was founded in 1919 as General Motors Acceptance Corporation (GMAC). Its initial purpose was groundbreaking for its time: to provide auto financing options to help General Motors compete with Ford's growing empire. For decades, GMAC played a key role in the automotive industry, expanding its services and weathering the ups and downs of the American economy.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Ally’s recent transformation began about 15 years ago when the company's leadership saw an opportunity to leverage their strong position in auto financing to create something new: one of the world's first all-digital banks. This bold move transitioned Ally into the organization it is today. The transition wasn't just a name change; it represented a fundamental shift in how banking services could be delivered, moving from traditional to digital.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Ally now stands as a testament to making a successful digital shift. With over 11 million customers, nearly $200 billion in assets, and a comprehensive suite of financial products including deposits, investments, mortgage, and credit cards, Ally is a powerhouse in fintech.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Within this context, Ally took on its next big challenge: modernizing releases in order to stay competitive in the market.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Balancing speed and safety\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"As Ally’s digital services evolved, the need to deliver change more quickly and safely while allowing teams to work independently (and at their own pace) became clear.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"One major issue was the structure of applications. \\\"We had some cumbersome monoliths,\\\" Cox noted. \\\"When you release a large application that has lots of changes from lots of teams, it requires a lot of coordination, a lot of planning, a lot of work. It's really difficult to do.\\\" This monolithic architecture was a significant bottleneck for Ally’s engineers, making it challenging to implement changes quickly and safely.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Another major pain point was the reliance on monthly release outages to ship releases.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$68edf00b-5120-4ec0-8c53-556383541dd6\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"content\":[{\"type\":\"paragraph\",\"text\":\"\\\"We had monthly release outages. Not outages because something went wrong necessarily, but we had to plan on taking our applications down so that we could release software.\\\" ~ Jeremy Cox, Director Lead of Software Engineering, Ally Financial\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"simple_quote$f9eb28eb-13db-47f9-86cd-6c312cf16d18\",\"slice_type\":\"simple_quote\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"This approach was not only disruptive to customers, but it put additional pressure on development teams.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Problems extended beyond just the size of applications. Ally was working with uncoordinated tooling across their web and mobile platforms. Before 2020, they used different feature flagging solutions for their web and mobile applications—making it impossible to turn on a feature for all customers at once. Some of these solutions only worked at build time but not at runtime, leading to events like customers having access to a feature on the web app but having to wait weeks for it to appear on mobile devices.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Furthermore, teams often relied on individual \\\"heroes\\\" who held critical knowledge about their systems. As Cox put it, \\\"There's [going] to be that one person who knows how everything fits together, or that one person who knows the secret of why this one thing is breaking everything… and that's not sustainable.\\\"\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Ally worked on addressing these challenges, but solutions were still fragmented across different platforms and didn't provide the necessary flexibility and control. The team knew they needed a more comprehensive approach to feature management and release coordination.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Goals for modernization\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Ally's leadership issued a clear mandate: figure out how to deliver change faster but also safer, iteratively instead of in big-bang releases, and allow teams to release changes independently. This wasn't just about adopting new tools; it required a fundamental shift in how Ally approached software development and delivery.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"To meet this challenge, Ally focused on a few key areas. The goals were to increase release velocity, implement API versioning and backwards compatibility, and enable daytime releases. Gray spoke about the practice of issuing overnight releases: \",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$59104122-fa00-4663-a3ac-c4df9c01c908\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"content\":[{\"type\":\"paragraph\",\"text\":\"“We can’t deliver more change, more value, while also working forty to fifty hours a week and asking teams to then work overnights and to give up their weekends. That’s… burning out your best engineers.” ~ Nathan Gray, Director of Digital Engineering Operations, Ally Financial\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"simple_quote$6afa8235-3548-4357-a641-2900960f1346\",\"slice_type\":\"simple_quote\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"The team also wanted to introduce feature-level rollbacks, implement testing in production, and achieve parity between their web and mobile platforms. Gray recalled, “in our previous state, web and API might deliver a feature a month before mobile, or vice versa. We had to have them releasing at the same time.” \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Collaborating with LaunchDarkly\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"In 2020, Ally brought in LaunchDarkly to help with modernization efforts. The first use case demonstrated the power of feature flagging during a critical time in the COVID-19 pandemic. Cox shared this important moment: \\\"The first time we used it, we had a feature that was about to go out to production for customers to verify their employment status. Well, we all remember 2020. March was a time when everything went into chaos. A lot of folks lost their jobs. It's not [the] right time to ask folks to tell us who their employer is.\\\"\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Using the LaunchDarkly feature flagging capability, Ally was able to simply turn off the feature without rebuilding the entire application or going through new cycles of testing. This experience sold the team on the benefits of separating deploy from release, setting the stage for broader improvements to their release process.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Transforming the release process\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"With LaunchDarkly as an enabler, Ally implemented several big changes. The first was decoupling the UI from the API. This let teams work in parallel, releasing APIs and gradually turning on features without tight dependencies. This shift towards a more modular architecture was complemented by a move toward microservices and a micro-frontend architecture. By breaking down monoliths into smaller, independently deployable services and frontend components, Ally gained the flexibility to release and roll back features individually.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Feature flagging became central to Ally's new architecture, with LaunchDarkly allowing them to control the rollout of features across the banking frontend with a new level of granularity. This enabled Ally to implement a more sophisticated approach to testing in production. The team developed a gradual rollout process, starting with internal pilots and progressing to canary releases for customers, significantly reducing the risk associated with new deployments.\",\"spans\":[{\"start\":415,\"end\":464,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/5-strategies-de-risk-releases-financial-services/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Alongside technical changes, Ally also revamped release management. The team created clear, automated paths for safely deploying changes to production, giving application developers more autonomy while maintaining necessary controls. Gray says he was “talking about release management as a service provider to the engineering teams that we support.” He remarked that his team is showing engineers “the easiest, least treacherous path, and not just a series of toll gates that they must pass.” This shared responsibility across engineering and release teams helped Ally strike a balance between freedom and responsibility.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Results and impact\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The results of Ally's modernization efforts were impressive. From 2020 to 2023, they achieved a 97% reduction in overnight and weekend releases. At the same time, they saw a 300% increase in production deployments. Gray summarized the impact:\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$3fc2d325-d383-4e41-ac7b-cc6bd7db2def\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"content\":[{\"type\":\"paragraph\",\"text\":\"\\\"Did we get ourselves out of nights and weekends? Largely, yes. But this is reality, and we're in technology. The occasional night, the occasional weekend has popped up. 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maximizes efficiency and reduces guesswork about which features customers actually want.\",\"spans\":[],\"direction\":\"ltr\"}]},{\"bullet_point\":[{\"type\":\"paragraph\",\"text\":\"Feature flags let teams roll out an experiment progressively, starting with a targeted segment of highly engaged users.\",\"spans\":[],\"direction\":\"ltr\"}]}],\"id\":\"key_takeaways$9c2a8654-9208-498e-9a1b-0c9638cc4a8b\",\"slice_type\":\"key_takeaways\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"From loan applications to mobile apps, tailor digital financial services through continuous experimentation.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"In financial services, personalization is a key differentiator. Customers demand tailored experiences, whether applying for loans, using banking apps, or engaging with chatbots. Through experimentation and A/B testing, financial institutions can acquire the data to fuel personalized experiences. But experimentation goes beyond personalization—it’s also about maximizing efficiency and reducing guesswork. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"By running controlled tests, digital product delivery teams can spend more time building features that customers actually want and less time on ones that flop.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"This article explores five ways FinServCo, a fictional financial services company, leverages experimentation to increase engagement, improve business outcomes, and create a more efficient product development process.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$b57d99df-191f-4131-9a9d-9d1fd3850810\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Experiment 1: Increasing loan application completion rates\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Experiment 1: Increasing loan application completion rates\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Challenge\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"FinServCo faced high abandonment rates during the loan application process. The hypothesis was that simplifying the application flow would reduce drop-offs and increase the completion rate by at least 10%.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Experiment approach\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Product managers led the redesign of the loan application flow, streamlining the steps and improving clarity. Engineers built and implemented the changes in LaunchDarkly, enabling a controlled rollout of the experiment to a small percentage of users. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Using LaunchDarkly's funnel optimization capabilities, they could precisely track each step in the application process, identifying where users were dropping off and adjusting the flow in real time. Funnel experiments in LaunchDarkly not only helped FinServCo monitor user behavior but also allowed them to experiment with different flows for various user segments. This helped create more efficient paths to conversion.\",\"spans\":[{\"start\":21,\"end\":40,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/funnel-experiments-make-it-easier-than-ever-to-measure/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Lastly, data scientists monitored metrics like completion rates and load times, pulling experiment data securely from LaunchDarkly into their data warehouse for deeper analysis. They used tools like Looker to run additional analyses to, among other things, help correlate user behavior with performance metrics.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Results\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The streamlined application process resulted in a 15% increase in loan application completion. The success of this experiment validated that efficient product delivery processes, coupled with data-driven decisions, improve customer engagement.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$68513f91-d215-4cbb-87d3-b2a9581fcf84\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1600,\"height\":900},\"alt\":\"Funnel Experiment in LaunchDarkly\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/Zv3eobVsGrYSwUcJ_image1.png?auto=format,compress\",\"id\":\"Zv3eobVsGrYSwUcJ\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$9009dfb0-d9a8-49f1-81c0-3ff151c0587f\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Experiment 2: Improving the mobile banking app experience\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"Example: LaunchDarkly funnel optimization experiment\",\"spans\":[{\"start\":0,\"end\":52,\"type\":\"em\"}],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Experiment 2: Improving the mobile banking app experience\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Challenge\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"FinServCo saw declining user engagement with its mobile banking app, particularly when it came to managing accounts. The hypothesis was that a gesture-based navigation would offer a more intuitive experience and improve user engagement.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Experiment approach\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Product managers proposed testing two navigation structures: a traditional menu and a gesture-based interface. Engineers implemented both versions using feature flags, enabling them to progressively roll out the experiment, starting with 5% of a targeted segment of highly engaged users. This allowed the team to reduce risk and quickly gather valuable feedback—both qualitative and quantitative. \",\"spans\":[{\"start\":153,\"end\":166,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/what-are-feature-flags/\",\"target\":\"_self\"}},{\"start\":212,\"end\":222,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/core-services/experimentation/\",\"target\":\"_self\"}},{\"start\":313,\"end\":324,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/5-strategies-de-risk-releases-financial-services/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The product and data team tracked user interaction metrics such as session length and feature usage in their experiment. And they used LaunchDarkly’s results segmentation to explore how the experiment impacted users differently based on what type of mobile device the user was on.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Results\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Overall, the gesture-based interface led to a 25% increase in session time and a 10% improvement in account feature usage compared to the traditional menu. This experiment validated the hypothesis, leading to the full rollout of the gesture-based navigation.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$abe08389-dba9-41b4-9657-d2711a447097\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1198,\"height\":647},\"alt\":\"Experimentation gif in LaunchDarkly\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/Zv3fnbVsGrYSwUcO_image2.gif?auto=format,compress\",\"id\":\"Zv3fnbVsGrYSwUcO\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$0b2db74c-f691-4b68-90a1-54775378f71c\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Experiment 3: Enhancing chatbot performance\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"Example: LaunchDarkly feature change experiment\",\"spans\":[{\"start\":0,\"end\":47,\"type\":\"em\"}],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Experiment 3: Enhancing chatbot performance\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Challenge\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"FinServCo’s chatbot was underperforming, with many customers escalating their queries to live agents. 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Feature flags allowed a gradual deployment of the AI chatbot experiment, ensuring a controlled environment for the test. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The team also securely exported their experiment data to one of their existing analytics platforms, where data scientists correlated chatbot performance with additional customer satisfaction data.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Results\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The generative AI model reduced escalated queries by 30%, leading to an improvement in overall customer satisfaction. The experiment validated that AI-driven responses could significantly enhance chatbot performance, driving both efficiency and customer satisfaction.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$b4043177-7f87-4c90-93e8-00413bb3e10e\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Experiment 4: Testing new payment features\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Experiment 4: Testing new payment features\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Challenge\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"FinServCo wanted to introduce a “Pay Later” feature, but the team was unsure how different placements and messaging would affect customer adoption. The hypothesis was that a more prominent position in the payment flow would increase adoption by at least 15%.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Experiment approach\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Product managers designed an A/B test to evaluate different placements and messaging for the “Pay Later” option in the payment flow. Engineers implemented the changes with feature flags, rolling out the experiment to a small group of users. Data scientists used LaunchDarkly’s experiment results to track adoption rates and engagement metrics. \",\"spans\":[{\"start\":29,\"end\":37,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/features/experimentation/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Results\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The “Pay Later” option placed prominently within the payment flow led to a 20% increase in adoption rates, confirming the hypothesis that a “louder” placement would drive a desirable impact on usage.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$4ba6a86f-5008-4fb6-873e-a34e86b3bd0d\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Experiment 5: Optimizing fraud detection algorithms\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Experiment 5: Optimizing fraud detection algorithms\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Challenge\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"FinServCo wanted to improve the accuracy of its fraud detection system for credit card transactions. 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flags\"],\"lang\":\"en-us\",\"slug\":\"ai-development-with-launchdarkly-release-measure-and-iterate\",\"first_publication_date\":\"2023-12-11T19:05:39+0000\",\"last_publication_date\":\"2026-09-04T18:21:31+0000\",\"uid\":\"ai-development-with-launchdarkly\",\"url\":\"/blog/ai-development-with-launchdarkly/\",\"link_type\":\"Document\",\"key\":\"1f80a7c1-f68a-4db8-b211-4b3309119448\",\"isBroken\":false}}],\"video_id\":[],\"video_type\":\"Wistia\",\"body\":[{\"primary\":{\"key_takeaway_title\":[],\"takeaway_paragraph\":[]},\"items\":[{\"bullet_point\":[{\"type\":\"paragraph\",\"text\":\"100% of financial services leaders surveyed in Ernst \u0026 Young's 2023 Financial Services GenAI Survey were already using or planning to use generative AI, despite strict regulatory and data-sensitivity constraints.\",\"spans\":[],\"direction\":\"ltr\"}]},{\"bullet_point\":[{\"type\":\"paragraph\",\"text\":\"An AI kill switch is a feature flag that disables a misbehaving AI feature instantly at runtime, with no redeploy or CI/CD rollback.\",\"spans\":[],\"direction\":\"ltr\"}]},{\"bullet_point\":[{\"type\":\"paragraph\",\"text\":\"AI model flags let teams swap LLMs and tune parameters like temperature and token count in production, while AI prompt flags update system prompts without a release.\",\"spans\":[],\"direction\":\"ltr\"}]},{\"bullet_point\":[{\"type\":\"paragraph\",\"text\":\"Targeting rules let teams adjust AI behavior to comply with varying regulations across jurisdictions or customer types, such as applying stricter lending guidelines in specific states or regions.\",\"spans\":[],\"direction\":\"ltr\"}]}],\"id\":\"key_takeaways$336b521b-4bd3-41d5-8167-e58b4af6bbd4\",\"slice_type\":\"key_takeaways\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"A guide for software engineering leaders on de-risking, controlling, and optimizing AI applications in production\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The race for financial services organizations to find profitable use cases for generative AI continues. According to Ernst \u0026 Young's 2023 Financial Services GenAI Survey, every single financial services leader surveyed (100%) said they are already using or planning to use generative AI (GenAI) at their organizations.\",\"spans\":[{\"start\":117,\"end\":169,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.prnewswire.com/news-releases/ey-survey-ai-adoption-among-financial-services-leaders-universal-amid-mixed-signals-of-readiness-302009309.html\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Financial institutions must be especially careful in how they deploy this powerful technology, owing to the sensitive data, precious assets, and regulations characteristic of their industry. If banks, brokerages, fintechs, wealth management firms, and insurance companies are to capitalize on GenAI, they need ways to deploy and control it in production without slowing down. \",\"spans\":[{\"start\":0,\"end\":22,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/solutions/financial-services/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"This article details how to get that control. I’ll explain how developers at financial institutions building AI applications upon large language models (LLMs) like GPT, Claude, and Gemini, can control, optimize, and mitigate risk in those applications.\",\"spans\":[{\"start\":216,\"end\":229,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/5-strategies-de-risk-releases-financial-services/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$d853cce9-ddee-433c-b500-260fa4660acc\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"1. Mitigate risk with feature flags\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"1. Mitigate GenAI risk in financial services with feature flags\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Rolling out GenAI features to production traffic without secure controls can expose banks and other financial institutions to regulatory compliance violations, downtime, or hallucinations. Feature flags offer a powerful solution to these risks.\",\"spans\":[{\"start\":189,\"end\":202,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/what-are-feature-flags/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Decouple deployments from releases\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"A key strategy for delivering AI features safely is to decouple the deployment of those features to production servers from the release to end users (i.e., a dark launch). Deploy first to ensure the AI doesn’t break production. Then release. \",\"spans\":[{\"start\":172,\"end\":184,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/ai-model-deployment/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"For example, a bank might deploy a chatbot powered by an LLM like GPT-4, but only enable the feature for internal users initially. This lets developers validate the AI’s performance in a more realistic environment. It also avoids exposing the chatbot to the public before it is proven reliable. \",\"spans\":[{\"start\":15,\"end\":42,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Progressively deliver for safe testing\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Financial institutions can also progressively deliver AI features, using feature flags to control which users receive the new capabilities. Start by releasing to a limited set of users—such as internal teams, early access users, or customers in a specific region. This lets you observe how the model is performing in a controlled setting before a full-scale rollout.\",\"spans\":[{\"start\":32,\"end\":53,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/what-is-progressive-delivery-all-about/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"For instance, a wealth management firm could roll out a GenAI-powered investment advice tool to its most tech-savvy customers first. This lets them gather feedback and make real-time adjustments to system prompts or model parameters based on actual usage data. And if something goes wrong, the issue would have only impacted a small group of users.\",\"spans\":[{\"start\":16,\"end\":38,\"type\":\"strong\"},{\"start\":56,\"end\":92,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Instantly disable faulty AI features with a kill switch\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"At times, GenAI systems can spit out hallucinations or degrade system performance. Using feature flags, you can flip a kill switch to disable problematic AI features.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"For example, if an AI-powered fraud detection system begins misclassifying legitimate transactions as fraudulent or slowing down transaction processing, engineers can immediately toggle off the feature in runtime. By disabling the feature without triggering a CI/CD rollback, the team instantly remediates the issue and protects the customer experience.\",\"spans\":[{\"start\":19,\"end\":52,\"type\":\"strong\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$419641c0-a550-4d04-926c-72045e4f1d9f\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":3600,\"height\":1576},\"alt\":\"Progressive-delivery-pattern-diagram\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZqQOyh5LeNNTxiRo_24-07-Riskstrategy-Progressiverollout.png?auto=format,compress\",\"id\":\"ZqQOyh5LeNNTxiRo\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$93a31316-8bd4-40e4-bf3f-8416d38113b5\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"2. Rapidly iterate with AI-specific feature flags\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"2. Deploy and update GenAI models without slowing down releases\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Building and delivering excellent generative AI features for banks and other financial organizations requires constant tuning, customization, and adoption of new models. By using the LaunchDarkly AI model feature flags and AI prompt flags, financial services organizations can quickly iterate on AI features in real time, without the need for redeployments.\",\"spans\":[{\"start\":196,\"end\":238,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/docs/home/agentcontrol\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Seamlessly swap out models and tune parameters\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"New models and configurations are released frequently. Developers must adopt the latest versions to avoid the flaws of outdated models. With AI model flags, your team can rapidly switch between different LLMs (e.g., GPT vs. Claude) and adjust tunable parameters like model temperature and token count. This agility ensures you stay competitive and can optimize for cost, accuracy, and performance.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Dynamically engineer system prompts\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"System prompts, which instruct the AI on how to behave, need continuous refinement. AI prompt flags allow developers to update prompts dynamically in the production environment. For example, if a bank's GenAI chatbot is failing to adhere to regulatory compliance guidelines, developers can adjust the system prompt immediately.\",\"spans\":[{\"start\":84,\"end\":99,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/home/flag-templates/ai-prompt-flags\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Being able to seamlessly update system prompts in production without requiring customers to refresh their app creates a better experience.\",\"spans\":[{\"start\":25,\"end\":60,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/solutions/enterprise-prompt-management-tools/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Here’s another use case to consider: an insurance company using AI for claims processing could rapidly switch to a newer, more accurate model that better detects fraudulent claims. Similarly, a banking chatbot's prompts could be rapidly updated to reflect new product offerings or regulatory requirements without service interruption.\",\"spans\":[{\"start\":36,\"end\":37,\"type\":\"strong\"},{\"start\":40,\"end\":89,\"type\":\"strong\"},{\"start\":194,\"end\":219,\"type\":\"strong\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$96f57485-8f64-49a6-9fd1-402a46f3e2e7\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"video_type\":\"YouTube\",\"youtube_id\":[{\"type\":\"paragraph\",\"text\":\"yGMzJAr2UZs\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"youtube_video$24447bd1-1e33-4547-a492-d79183435fff\",\"slice_type\":\"youtube_video\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"3. Optimize AI through experimentation\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"3. Run safe experiments on GenAI models and prompts\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"To help ensure that GenAI applications deliver maximum value at a reasonable cost, financial services firms should experiment with a variety of models, prompts, and configurations.\",\"spans\":[{\"start\":39,\"end\":81,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/solutions/optimize-ai-performance/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"A/B test to increase conversions\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"For customer-facing applications like AI financial advisors, running A/B tests allows you to compare different versions of the model and its configurations. For example, one model may return more concise answers and use fewer tokens. While another model may offer longer, more personalized advice that drives higher conversions. \",\"spans\":[{\"start\":38,\"end\":59,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Through experimentation, engineering teams can refine the AI’s behavior while balancing utility with cost. (You can run these kinds of experiments in LaunchDarkly.)\",\"spans\":[{\"start\":116,\"end\":146,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/solutions/run-experiments/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Run experiments to help improve fraud detection and risk management\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"For AI-powered fraud detection systems, performance and accuracy are critical. Experimenting with different model configurations can help determine which setups minimize false positives while maintaining low-latency transaction processing. Through continuous experimentation, financial services firms can improve the system’s ability to accurately detect fraud in real-time.\",\"spans\":[{\"start\":4,\"end\":38,\"type\":\"strong\"},{\"start\":79,\"end\":92,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/core-services/experimentation/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Consider another use case: a fintech company could run experiments on its AI credit scoring model, comparing traditional methods with new AI approaches. By measuring approval rates, default risks, and regulatory compliance, they can make data-driven decisions on which model to adopt.\",\"spans\":[{\"start\":74,\"end\":97,\"type\":\"strong\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$e1cc93d8-a9fd-454c-b855-91cd9131e239\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"4. Personalize GenAI to improve customer experiences\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"4. Personalize GenAI features to improve customer experiences\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"With the LaunchDarkly targeting engine, you can customize AI applications to different user groups based on any attribute you can imagine: device type, mobile app version, location, customer tier, financial profile, and so on.\",\"spans\":[{\"start\":38,\"end\":39,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Customizing AI experiences by user segment\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"For example, a fintech company might tailor its GenAI trading assistant based on the user’s investment preferences or subscription tier. Premium users could receive advanced, personalized financial advice, while other users might get more basic recommendations. Such personalization increases customer satisfaction and retention.\",\"spans\":[{\"start\":48,\"end\":71,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Selectively disable AI features for cost and performance optimization\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Financial services teams can also selectively disable AI features for certain users to manage costs and improve system performance. For example, if an AI feature causes excessive latency on older devices, you can turn off the feature for those users while keeping it live for others. This avoids disrupting the overall user experience while optimizing system performance and cost-efficiency.\",\"spans\":[{\"start\":99,\"end\":100,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Use targeting to help maintain regulatory compliance\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Engineers can also use targeting to adjust AI behavior to comply with varying regulations across different jurisdictions or customer types. For example, an AI lending platform could be configured to follow stricter lending guidelines for specific states or regions. Or it could provide transparency in line with local consumer protection laws. By dynamically modifying AI behavior to fit regulatory environments, financial institutions can better navigate compliance complexities.\",\"spans\":[{\"start\":36,\"end\":54,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/solutions/control-ai-agents/\",\"target\":\"_self\"}},{\"start\":156,\"end\":175,\"type\":\"strong\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$310187a3-c0af-4938-9b62-2713ce28883a\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Drive AI innovation with LaunchDarkly\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Drive AI innovation with LaunchDarkly\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"As financial services firms integrate generative AI into their applications, the need for control, flexibility, and safety increases. Through feature management and experimentation, AI deployments can be decoupled from releases by software engineering teams, progressively deliver AI features, and use kill switches to disable problematic functionality.\",\"spans\":[{\"start\":3,\"end\":27,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/solutions/financial-services/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"What’s more, teams can rapidly iterate on AI models and prompts. They can optimize model performance through experimentation, thus driving innovation without compromising on performance or accuracy. And with targeting and personalization, financial institutions can fine-tune AI behavior for different user segments, enhance customer experiences, and navigate complex regulatory environments.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"By incorporating these strategies, engineering leaders in financial services can unlock more potential from generative AI.\",\"spans\":[{\"start\":81,\"end\":121,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/platform/agent-control/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$49caf565-25a1-4ae3-971d-9c5fc68946db\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"FAQs\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"FAQs\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"How can banks and financial institutions roll out generative AI features more safely?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Financial institutions can roll out GenAI safely by using feature flags to decouple deployment from release. Deploy the feature to production first to confirm it doesn't break anything, then release it. Start with a limited group such as internal teams, early-access users, or customers in a specific region before a full rollout. If something goes wrong, only a small group is affected.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"What is an AI kill switch and when would you use one?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"An AI kill switch is a feature flag that lets you instantly disable a problematic AI feature in runtime. You'd use it when a GenAI system produces hallucinations or degrades performance.\\n\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"How can teams switch between LLMs like GPT and Claude without redeploying?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"AI model flags let teams rapidly switch between different LLMs and adjust tunable parameters like model temperature and token count  without having to redeploy. AI prompt flags let developers update system prompts dynamically in production, so a chatbot's behavior can be corrected or updated without requiring customers to refresh their app.\\n\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"How do you keep AI behavior compliant across different regulations and jurisdictions?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Financial institutions can adjust AI behavior by using targeting to comply with regulations across jurisdictions or customer types. This way, organizations in banking and finance can dynamically modify AI behavior to fit regulatory environments.\\n\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"How can financial services teams optimize GenAI cost and performance?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Teams within financial organizations can optimize AI cost and performance through experimentation and targeting. A/B testing different model versions and configurations reveals trade-offs between response quality versus token usage. Teams can also selectively disable AI features for certain users to help manage costs and improve performance without widespread disruption.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$1f0ba431-cdb8-48b8-adfc-7d6ff457647c\",\"slice_type\":\"wysiwyg\",\"slice_label\":null}],\"meta_title\":[{\"type\":\"heading1\",\"text\":\"Generative AI in Financial Services: Deploy Safely\",\"spans\":[],\"direction\":\"ltr\"}],\"meta_description\":[{\"type\":\"paragraph\",\"text\":\"Generative AI in financial services demands control and compliance. 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outage.\",\"spans\":[],\"direction\":\"ltr\"}]},{\"bullet_point\":[{\"type\":\"paragraph\",\"text\":\"MTTR measures recovery speed, not incident frequency: a team with frequent issues can still post a low MTTR through strong response processes.\",\"spans\":[],\"direction\":\"ltr\"}]},{\"bullet_point\":[{\"type\":\"paragraph\",\"text\":\"MTTR is one of the key metrics identified by the DevOps Research and Assessment (DORA) team, alongside deployment frequency, lead time for changes, and change failure rate.\",\"spans\":[],\"direction\":\"ltr\"}]},{\"bullet_point\":[{\"type\":\"paragraph\",\"text\":\"Feature flags act as an undo button for a bad release, letting teams disable problematic code instantly instead of rolling back the entire deployment.\",\"spans\":[],\"direction\":\"ltr\"}]}],\"id\":\"key_takeaways$03f3f369-9789-4c95-8095-402f0058c5a9\",\"slice_type\":\"key_takeaways\",\"slice_label\":null},{\"primary\":{\"key_takeaway_title\":[{\"type\":\"heading3\",\"text\":\"Defining mean time to restore (MTTR)\",\"spans\":[],\"direction\":\"ltr\"}],\"takeaway_paragraph\":[{\"type\":\"paragraph\",\"text\":\"Mean time to restore (MTTR) is the average time it takes to recover from a system failure or outage. It's calculated by dividing the total downtime by the number of failure incidents over a specific period. A lower MTTR indicates a more resilient system and a more effective incident response process, while a higher MTTR suggests room for incident response improvements.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[{\"bullet_point\":[]}],\"id\":\"key_takeaways$873fe7ad-60c6-4b4c-9cdb-a354d847b6f7\",\"slice_type\":\"key_takeaways\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"Regardless of your experience, testing, or quality assurance procedures, we all know the truth about software development: bad ship happens. The question, then, isn't whether you’ll experience a software incident but how quickly can you recover.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"That’s where the mean time to restore (MTTR) service becomes important. This critical DevOps metric reveals how quickly your teams bounce back from incidents and bugs. The lower your MTTR, the faster you're back in business, keeping your users happy, stress levels in check, and bottom line healthy. \",\"spans\":[{\"start\":21,\"end\":45,\"type\":\"strong\"},{\"start\":86,\"end\":99,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/guides/metrics/engineering-insights-metrics\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"However, reducing your MTTR is easier said than done (without the right tools and know-how). With microservices, cloud infrastructure, and endless integrations, pinpointing and fixing issues can feel like looking for a misplaced semicolon in a sea of JavaScript.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Fortunately, we can help.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Below, we’ll walk you through everything you need to know about MTTR and how you can use feature management platforms (like LaunchDarkly) to reduce downtime and save your business.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$217b3ab2-db40-40e0-b0dd-07d9788f4cd9\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"What is mean time to restore (MTTR)?\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"What is mean time to restore (MTTR)?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The faster you recover, the less impact on your business operations and your customers' experience. Simple as that. A low MTTR helps maintain business continuity and guarantees critical systems and services are available when needed.\",\"spans\":[{\"start\":142,\"end\":161,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/rto-vs-rpo/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Let’s face it: users aren’t patient. Every moment of downtime is a moment where a user might be cursing your app, leaving a bad review, or worse, jumping ship to a competitor. Keeping your MTTR low shows users that when issues occur (because they will), you’ll take care of it quickly.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"MTTR isn’t just about your incident response process or brand reputation. A high MTTR can lead to severe consequences for other businesses and consumers:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"In the airline industry, system outages can lead to thousands of flights being canceled globally, resulting in hundreds of millions of dollars in losses and leaving countless passengers stranded.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"For healthcare providers, system failures can prevent patients from accessing vital care, potentially putting lives at risk and disrupting critical medical services.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Financial institutions experiencing prolonged downtime may face substantial monetary losses, regulatory scrutiny, and a significant erosion of customer trust.\",\"spans\":[{\"start\":0,\"end\":22,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/5-strategies-de-risk-releases-financial-services/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"E-commerce platforms can lose millions in revenue during peak shopping periods if systems are down for even short periods.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Common misconceptions about MTTR\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"One of the best ways to learn about MTTR is about understanding what it’s not. These misconceptions commonly trip businesses up:\",\"spans\":[{\"start\":74,\"end\":77,\"type\":\"em\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Low MTTR means fewer incidents: Not necessarily. MTTR measures how quickly you recover, not how often issues occur. You could have a low MTTR but still face frequent incidents.\",\"spans\":[{\"start\":0,\"end\":31,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"MTTR is all about fixing bugs: While bug fixes are part of it, MTTR encompasses all types of incidents, including infrastructure issues, configuration errors, or even planned maintenance.\",\"spans\":[{\"start\":0,\"end\":30,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Automating everything will automatically lower MTTR: Automation can help, but it's not a silver bullet. Without proper planning and implementation, automated systems can sometimes make issues harder to diagnose and resolve.\",\"spans\":[{\"start\":0,\"end\":52,\"type\":\"strong\"},{\"start\":53,\"end\":72,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/features/automation/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"MTTR is purely a tech team metric: While tech teams are on the front lines, MTTR is a business-wide concern. It affects customer service, sales, marketing—everyone.\",\"spans\":[{\"start\":0,\"end\":34,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"The goal should always be zero MTTR: It’s very unlikely you’ll recover instantaneously. But recovering from a failed deployment in minutes is possible with the right combination of DevOps tools and processes—and it puts you among the elite engineering teams, according to DORA.\",\"spans\":[{\"start\":0,\"end\":36,\"type\":\"strong\"},{\"start\":259,\"end\":276,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://cloud.google.com/devops/state-of-devops\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$9431149c-b234-426c-91a7-7ae56d4c6722\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"MTTR and the Four DORA Metrics\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"MTTR and the Four DORA Metrics\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"MTTR is one of the four key metrics identified by the DevOps Research and Assessment (DORA) team. These DORA metrics are widely used to measure software development and operational performance.\",\"spans\":[{\"start\":104,\"end\":116,\"type\":\"hyperlink\",\"data\":{\"id\":\"Zxq10REAACAAHBD-\",\"type\":\"blog_post\",\"tags\":[\"dora metrics\"],\"lang\":\"en-us\",\"slug\":\"dora-metrics-4-metrics-to-measure-your-devops-performance\",\"first_publication_date\":\"2024-10-24T21:13:19+0000\",\"last_publication_date\":\"2026-09-10T22:02:51+0000\",\"uid\":\"dora-metrics\",\"url\":\"/blog/dora-metrics/\",\"link_type\":\"Document\",\"isBroken\":false}}],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Deployment Frequency: How often an organization successfully releases to production.\",\"spans\":[{\"start\":0,\"end\":21,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/deployment-frequency/\",\"target\":\"_self\"}},{\"start\":0,\"end\":20,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Lead Time for Changes: The time it takes to go from code committed to code successfully running in production.\",\"spans\":[{\"start\":0,\"end\":21,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Change Failure Rate: The percentage of deployments causing a failure in production.\",\"spans\":[{\"start\":0,\"end\":19,\"type\":\"hyperlink\",\"data\":{\"id\":\"ZuMbmBMAACAAYXSY\",\"type\":\"blog_post\",\"tags\":[\"dora metrics\",\"CI/CD\",\"DevOps\",\"automation\"],\"lang\":\"en-us\",\"slug\":\"change-failure-rate-what-it-is--how-to-measure\",\"first_publication_date\":\"2024-09-12T16:59:34+0000\",\"last_publication_date\":\"2026-09-10T15:31:55+0000\",\"uid\":\"change-failure-rate\",\"url\":\"/blog/change-failure-rate/\",\"link_type\":\"Document\",\"isBroken\":false}},{\"start\":0,\"end\":19,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Mean Time to Restore: How long it takes to restore service when a service incident occurs.\",\"spans\":[{\"start\":0,\"end\":20,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Ultimately, MTTR is just a single metric with a focused purpose—however, in the context of these other metrics, it provides a more comprehensive view of your team's effectiveness.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Also, it’s helpful to distinguish between a few similar-sounding metrics. While the following terms are often used interchangeably, they all mean something just a little bit different:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Mean time to recover: The average time between when an incident starts and when it's fully resolved.\",\"spans\":[{\"start\":0,\"end\":20,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Mean time to repair: The average time taken to repair a failed component.\",\"spans\":[{\"start\":0,\"end\":19,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Mean time to restore: The average time to restore a system to a functional state after a failure.\",\"spans\":[{\"start\":0,\"end\":20,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"MTTR in the broader incident management landscape\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"MTTR is part of a larger set of incident metrics that DevOps and engineering teams use to measure and improve their performance:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Mean time to detect (MTTD): How long it takes to discover an incident.\",\"spans\":[{\"start\":0,\"end\":26,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Mean time to acknowledge (MTTA): The average time between detection and response initiation.\",\"spans\":[{\"start\":0,\"end\":31,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Mean time between failures (MTBF): The average time between system failures.\",\"spans\":[{\"start\":0,\"end\":33,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Together, these metrics provide a comprehensive view of an organization's incident management capabilities.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"DevOps and engineering teams leverage these metrics for setting and measuring service level objectives (SLOs). These metrics also help in monitoring compliance with service level agreements (SLAs), which often include specific commitments about system uptime and incident resolution times. Plus, tracking incident metrics like these over time give you benchmarks to gauge your performance year-over-year or against industry standards.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$9524923b-3187-461b-bf0e-237b219faac2\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"How to calculate MTTR\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"How to calculate mean time to restore\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"MTTR = Total downtime / Number of incidents\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"You take the total amount of downtime over a given period and divide it by the number of incidents that occurred during that same period.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Let’s look at an example:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Imagine your system experienced three outages last month:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Outage 1: 2 hours\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Outage 2: 30 minutes\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Outage 3: 1 hour and 30 minutes\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"First, let's convert all times to the same unit (we'll use minutes):\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"2 hours = 120 minutes\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"30 minutes\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"1 hour and 30 minutes = 90 minutes\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Now, let's plug these numbers into our formula:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Total downtime = 120 + 30 + 90 = 240 minutes. Number of incidents = 3\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"MTTR = 240 minutes / 3 incidents = 80 minutes\",\"spans\":[{\"start\":0,\"end\":4,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"So, your mean time to restore for the month is 80 minutes.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"While the calculation is relatively simple, the tricky part comes in accurately tracking downtime and defining what constitutes an \\\"incident\\\" for your specific system.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$a0ebf3f1-f354-4afc-8def-e7dac862d793\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"The real cost(s) of slow recovery\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"The real cost(s) of slow recovery\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"When systems go down, every minute counts. Here are just a few of the costs of slow recovery time:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Financial losses: The most immediate and tangible cost of downtime is lost revenue. For e-commerce sites, payment processors, or subscription-based services, every minute offline is money left on the table. Large enterprises can lose up to $5 million per hour during major outages.\",\"spans\":[{\"start\":0,\"end\":17,\"type\":\"strong\"},{\"start\":229,\"end\":259,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.pingdom.com/outages/average-cost-of-downtime-per-industry/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Reputation damage: News of outages spreads like wildfire on social media. Extended downtime can lead to negative reviews, lost customer trust, and a tarnished brand image. It can take months or even years to rebuild a reputation damaged by significant service disruptions.\",\"spans\":[{\"start\":0,\"end\":18,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Decreased productivity: System outages don't just affect your customers—they paralyze your own team. Developers shift from building new features to firefighting, support teams are flooded with tickets, and other departments can't access critical tools. This ripple effect can derail project timelines and strategic initiatives.\",\"spans\":[{\"start\":0,\"end\":23,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Competitive disadvantage: While your system is down, your competitors are up and running. Extended or frequent outages can drive customers to explore alternative solutions, and once they've switched, winning them back is an uphill battle.\",\"spans\":[{\"start\":0,\"end\":25,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Compliance and legal risks: For businesses in regulated industries like healthcare or finance, extended downtime can lead to compliance violations. This can result in hefty fines, legal action, or even the loss of necessary certifications. \",\"spans\":[{\"start\":0,\"end\":27,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Employee morale and burnout: Constantly fighting fires and dealing with angry customers takes a toll on your team. High-stress incidents can lead to burnout, decreased job satisfaction, and even increased turnover.\",\"spans\":[{\"start\":0,\"end\":28,\"type\":\"strong\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$4feeb4c3-b942-4a40-9d1a-08f314b65348\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Factors impacting your MTTR\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Factors impacting your MTTR\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Before you can improve your mean time to restore, you need to know what’s impacting it. While that list could be endless, here is a shortlist of the likely factors impacting your MTTR:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Complexity of modern software systems: Modern-day applications are like digital Jenga towers—pull out the wrong piece, and everything might come tumbling down.\",\"spans\":[{\"start\":0,\"end\":38,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Manual processes and human error: Manual deployments, configuration changes, and recovery processes are all opportunities for mistakes to creep in. And in high-stress situations, even the most experienced developers can slip up.\",\"spans\":[{\"start\":0,\"end\":33,\"type\":\"strong\"},{\"start\":34,\"end\":52,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/guides/infrastructure/deployment-strategies\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Inadequate monitoring and alerting systems: You can't fix what you don't know is broken. Insufficient monitoring and observability tools or poorly configured alerts can lead to delayed response times or (worse) issues flying under the radar until they become full-blown crises.\",\"spans\":[{\"start\":0,\"end\":43,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Full-user deployments: Pushing changes to all users simultaneously is an unnecessary risk. Without gradual rollouts, issues that weren't caught in testing can suddenly affect your entire user base, amplifying the impact and complicating recovery.\",\"spans\":[{\"start\":0,\"end\":22,\"type\":\"strong\"},{\"start\":99,\"end\":115,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/how-percentage-rollouts-minimize-deployment-risks/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Muddy code: Code without clear demarcations or feature flags makes it challenging to isolate problematic features or roll back to a stable state quickly.\",\"spans\":[{\"start\":0,\"end\":11,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Non-targeted rollouts: Without the ability to target specific user segments, environments, or regions, you're left with an all-or-nothing approach that can make recovery more complex and time-consuming.\",\"spans\":[{\"start\":0,\"end\":22,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Inconsistent environments: If your development, staging, and production environments are wildly different, issues that crop up in production can be near impossible to reproduce and resolve quickly.\",\"spans\":[{\"start\":0,\"end\":26,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"No kill switch: Rolling back an entire release and routing all production traffic to an old working version of your application prolongs your recovery time. The same is true when you write a bug fix and run it through your deployment pipeline. \",\"spans\":[{\"start\":0,\"end\":16,\"type\":\"strong\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$4234809b-840d-49cf-9cc8-c9a78beac86f\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"10 strategies to reduce MTTR\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"10 strategies to reduce your mean time to restore\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"While there’s no one-size-fits-all approach to reducing your mean time to restore, you can implement several strategies and tools to move it in the right direction.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"1. Implement monitoring and alerting\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Early detection is half the battle. Set up comprehensive monitoring across your entire stack—from infrastructure to application performance. Use tools that provide real-time insights and alerts, so you're not caught off guard when issues arise. The sooner you know about a problem, the quicker you can start fixing it.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Remember, issues will arise—it’s about when, not if. \",\"spans\":[{\"start\":17,\"end\":21,\"type\":\"em\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"2. Create and maintain detailed runbooks\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Develop clear, step-by-step runbooks for common issues and update them regularly. These playbooks can guide your team through the recovery process, reducing confusion and speeding up resolution times.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"3. Automate, automate, automate\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The less manual intervention required, the faster your recovery can be. Automate routine tasks, deployments, and even parts of your incident response process. Tools like configuration management systems and infrastructure-as-code can help guarantee consistency and reduce human error.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"For example, Release Guardian monitors operational performance at the feature level and automatically remediates issues that arise. \",\"spans\":[{\"start\":13,\"end\":29,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/meet-release-guardian/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"4. Use feature flags as a kill switch\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Feature flags are your secret weapon for quick recoveries. Tools like LaunchDarkly let you toggle features on and off without redeploying your entire application. This granular control allows you to quickly disable problematic features or roll back changes without disrupting your entire system. \",\"spans\":[{\"start\":0,\"end\":13,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/features/feature-flags/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"For example, if a feature throws a bug in production, you can selectively disable the offending feature in runtime, instantly resolving the issue. You don’t need to roll back the entire release associated with the buggy feature. You don’t need to route all production traffic back to an older version of your app. And you don’t need to rush a new version of your app through your deployment pipeline. You toggle a feature flag and resolve the problem instantly. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"5. Implement progressive rollouts and canary releases\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Use progressive delivery and canary releases to deploy changes to a small subset of users first. This approach helps you catch issues early and limits the blast radius if something goes wrong.\",\"spans\":[{\"start\":4,\"end\":24,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/what-is-progressive-delivery-all-about/\",\"target\":\"_blank\"}},{\"start\":29,\"end\":44,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/four-common-deployment-strategies/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"6. Create a blameless culture\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"When things go wrong, focus on learning, not finger-pointing. Conduct blameless post-mortems to understand what happened and how to prevent similar issues in the future.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"7. Implement runtime configuration management\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Use long-term feature flags to govern important app configurations. For example, if site latency spikes dramatically due to an unexpected surge in traffic, toggle a flag to instantly disable non-essential features and services, thus improving latency (and avoiding a full outage).\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"8. Consider  chaos engineering\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Don't wait for disasters to happen—create them yourself (in a controlled way, of course). Chaos engineering involves intentionally introducing failures into your system to test its resilience. This proactive approach helps you identify and address weaknesses before they cause real outages.\",\"spans\":[{\"start\":90,\"end\":107,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/chaos-engineering-and-continuous-verification-in-production/\",\"target\":\"_blank\"}},{\"start\":259,\"end\":265,\"type\":\"em\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"9. Implement redundancy and failover mechanisms\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Design your systems with redundancy in mind. Use load balancers, multi-region deployments, and automatic failover mechanisms to guarantee that a single point of failure doesn't bring down your entire application.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"10. Leverage AI and machine learning for predictive maintenance\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Stay ahead of issues with predictive maintenance. Use AI and machine learning algorithms to analyze system metrics and identify potential problems before they escalate into full-blown outages.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$a36ba5d9-92ff-4a42-95d6-c9d78969231c\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"How LaunchDarkly reduces your MTTR\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"How LaunchDarkly reduces your MTTR\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"LaunchDarkly allows you to wrap your code in feature flags to give you unprecedented control over how and when features are released to your users. But it's not just a toggle switch—it’s a comprehensive platform that integrates seamlessly with your existing workflows to provide real-time control, detailed analytics, and the flexibility to adapt on the fly.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Features flags let you instantly disable problematic code without rolling back your entire deployment. It's essentially an \\\"undo\\\" button for specific features and code patches.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Noticed a performance issue with that new algorithm? Flip a switch, and it's off. Database connection acting up? Toggle it back to the old system while you investigate. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Feature flags give you the power to isolate issues and mitigate their impact in real-time, drastically reducing your MTTR.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"With real-time monitoring of your feature flags, you can watch the impact of your changes as they happen. Spot a spike in error rates or a dip in performance? You can react instantly, rolling back the change with a single click. No need to wake up the entire dev team or push a panicked hotfix. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"This real-time control means you can often resolve issues before they even impact your MTTR metrics.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"In a recent survey of 250 LaunchDarkly customers, 86% recover from software incidents in a day or less, on average. \",\"spans\":[{\"start\":50,\"end\":102,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/2024-survey-impact-launchdarkly-customer-outcomes/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Success stories of engineering teams improving their MTTR\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"DIOR reduced their MTTR from hours to minutes\",\"spans\":[{\"start\":0,\"end\":45,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/case-studies/dior/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Paramount used to take up to a week to fix bugs, now they resolve them in a day\",\"spans\":[{\"start\":0,\"end\":79,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/paramount-improves-developer-productivity-100x/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading2\",\"text\":\"Reduce your mean time to restore with LaunchDarkly\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"A high mean time to restore isn't a life sentence. With the right strategies, tools, and know-how, you can transform your incident response from a panic-inducing fire drill into a smooth, efficient process.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"We get it: bad ship happens. But, with LaunchDarkly, you're not just fixing problems faster—you're preventing them before they start. Because in the world of software reliability, the best incident is the one that never happens.\",\"spans\":[{\"start\":11,\"end\":27,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/bad-ship-happens/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Start your free full-access 14-day trial today, or schedule a demo with our team to learn more.\",\"spans\":[{\"start\":0,\"end\":47,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://app.launchdarkly.com/signup\",\"target\":\"_blank\"}},{\"start\":51,\"end\":94,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/request-a-demo/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$8a94a596-ea8f-4035-985b-9c34b47d3b88\",\"slice_type\":\"wysiwyg\",\"slice_label\":null}],\"meta_title\":[{\"type\":\"heading1\",\"text\":\"Mean Time to Restore (MTTR): What It Is \u0026 How to Reduce 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Feature management software, particularly feature flag systems, has emerged as a key tool for developers, providing centralized control over which features are live and facilitating A/B testing to optimize user interactions.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"In 2024, LaunchDarkly solidified its position as the leading solution in this space, according to the latest report from G2 Grid® for Feature Management. Here’s a closer look at why LaunchDarkly is the standout choice for feature management this year.\",\"spans\":[{\"start\":121,\"end\":152,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.g2.com/categories/feature-management\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$ba21200f-c8c0-4dec-b268-7a215b0f97a2\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1039,\"height\":554},\"alt\":\"G2 Grid for Fall 2024\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZvRn_rVsGrYSwAlt_2024G2FallReport.png?auto=format,compress\",\"id\":\"ZvRn_rVsGrYSwAlt\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$89584e8d-ab70-4d13-94df-a085d6f4d3e7\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Why Feature Management Matters\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Why Feature Management Software Matters\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Feature management software allows for the strategic rollout and rollback of features with precision, mitigating risks associated with deploying new functionalities. By leveraging feature flags, developers can control which features are visible to users, test new functionalities, and gather actionable data without requiring code changes.\",\"spans\":[{\"start\":53,\"end\":85,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/core-services/releases/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Moreover, these tools offer robust analytics and monitoring capabilities, helping teams quickly identify and address issues with live features. A centralized hub for managing these aspects streamlines development and enhances overall software quality.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$c5aa1b33-67c2-490a-9c95-4bb300e2c94c\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"content\":[{\"type\":\"paragraph\",\"text\":\"\\\"LaunchDarkly is proven to be an indispensable tool for managing feature releases.\\\" \\n- G2 review 9/20/24\",\"spans\":[{\"start\":0,\"end\":84,\"type\":\"strong\"},{\"start\":85,\"end\":104,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"simple_quote$1950b69e-6e34-488f-aacf-1bfe2a6800b8\",\"slice_type\":\"simple_quote\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"LaunchDarkly: The Industry Leader\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"LaunchDarkly: The Industry Leader\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"1. Best for Mid-Market and Enterprise\\nIn the 2024 G2 Grid® for Feature Management rankings, LaunchDarkly was recognized as the best feature management software for both mid-market and enterprise companies. This dual recognition highlights LaunchDarkly's versatility and effectiveness across organizations of various sizes. Whether you're a growing mid-sized company or a large enterprise, LaunchDarkly’s platform scales easily to meet your needs.\",\"spans\":[{\"start\":0,\"end\":38,\"type\":\"strong\"},{\"start\":50,\"end\":81,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.g2.com/categories/feature-management\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"2. Highest User Satisfaction\\nUser satisfaction is a critical metric in evaluating software solutions. According to G2’s user reviews, LaunchDarkly boasts the highest user satisfaction in the feature management category. This accolade is a testament to the platform's reliability and ease of use, and the value it delivers to its users. This feedback from real-world users underscores LaunchDarkly’s commitment to providing a superior feature management experience.\",\"spans\":[{\"start\":0,\"end\":29,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"3. Best Free Software\\nFor those looking to explore feature management without a significant financial commitment, LaunchDarkly stands out as the best free software option. This is particularly advantageous for startups and smaller teams that need powerful tools without the upfront costs. LaunchDarkly’s free tier offers a taste of the comprehensive features available in paid versions, allowing users to experience the benefits of feature management before making a financial commitment.\",\"spans\":[{\"start\":0,\"end\":22,\"type\":\"strong\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$29406d86-acc8-4116-b2c3-4ac4f4e42af0\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"The G2 Advantage\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"The G2 Advantage\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The G2 Grid® for Feature Management is a valuable resource for technology buyers, offering a data-driven perspective on software products. Unlike subjective analyst opinions, G2’s rankings are based on real user reviews and market data. This democratic approach ensures that the products highlighted in the Grid are those truly delivering value to users.\",\"spans\":[{\"start\":4,\"end\":35,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.g2.com/categories/feature-management\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Products are evaluated on several criteria, including user satisfaction, market presence, and product performance. The Grid categorizes solutions into four main areas, reflecting their strengths and suitability for different needs. LaunchDarkly’s strong performance across these categories—particularly in user satisfaction and market presence—demonstrates its leadership and reliability in the feature management space.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$26af074a-5b79-45e8-ad59-1c8315419c4d\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"content\":[{\"type\":\"paragraph\",\"text\":\"\\\"We’ve reduced the stress around releases, knowing that we always have a safety net.\\\" \\n- G2 review 9/20/24\",\"spans\":[{\"start\":0,\"end\":87,\"type\":\"strong\"},{\"start\":87,\"end\":106,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"simple_quote$9fddbd9e-983f-4b97-9bd2-e778b28bfd78\",\"slice_type\":\"simple_quote\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"What Makes LaunchDarkly Stand Out?\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"What Makes LaunchDarkly Stand Out?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"1. Comprehensive Feature Flag Management\\nLaunchDarkly provides an intuitive and centralized hub for managing feature flags. This simplifies the complexities associated with feature rollouts and rollbacks, making it easier for development teams to implement changes with confidence.\\n\",\"spans\":[{\"start\":0,\"end\":41,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"2. Advanced Analytics and Monitoring\\nThe platform offers sophisticated analytics and monitoring tools, allowing teams to track feature performance, conduct A/B testing, and gather valuable insights. This data-driven approach helps teams make informed decisions.\\n\",\"spans\":[{\"start\":0,\"end\":37,\"type\":\"strong\"},{\"start\":71,\"end\":101,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/release-assistant-automation-monitoring-ux-improvements/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"3. 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The platform’s extensive documentation, responsive customer service, and active user community contribute to a positive user experience and effective problem-solving.\",\"spans\":[{\"start\":0,\"end\":32,\"type\":\"strong\"},{\"start\":61,\"end\":98,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/community/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$adc752de-fa96-4c07-b32e-145d53881d15\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Conclusion\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Conclusion\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"As feature management evolves, LaunchDarkly’s dominance in 2024 reflects its robust capabilities and user-centric approach. 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The results show unequivocally that the LaunchDarkly feature management and experimentation platform drives positive business outcomes for customers. They also reveal trends in use cases, adoption levels, and feature management maturity. \",\"spans\":[{\"start\":37,\"end\":55,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://wakefieldresearch.com/\",\"target\":\"_blank\"}},{\"start\":168,\"end\":228,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/product/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Explore the survey results below to discover the tangible business impact of LaunchDarkly. And see how you compare to surveyed customers in terms of software engineering performance and feature management maturity.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"(We also ran a survey comparing software engineering and business performance between LaunchDarkly customers and non-customers. View the results here if you're interested)\",\"spans\":[{\"start\":0,\"end\":171,\"type\":\"em\"},{\"start\":128,\"end\":170,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/2024-survey-impact-of-feature-management/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$7ef18d52-a744-4627-8de7-6d4109273e33\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Tangible business impact\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Tangible business impact\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Innovation velocity, cost-savings, and revenue growth\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$30840afd-ef49-4a8a-9328-5549ce2808f5\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"content\":[{\"type\":\"paragraph\",\"text\":\"95% of surveyed customers agree that “LaunchDarkly has a positive impact on organizational performance such as revenue, customer satisfaction, and operational efficiency.\\\"\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"simple_quote$ea56bff0-4d5a-4520-9597-7fa9503e427b\",\"slice_type\":\"simple_quote\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"This finding echoes what we often hear from customers: they regard LaunchDarkly as an indispensable solution in their DevOps stack that makes a big impact across multiple areas of the business.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$9b1a7e92-a9e0-4cb5-95c7-13258d1d2554\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"content\":[{\"type\":\"paragraph\",\"text\":\"90% of surveyed customers agree that LaunchDarkly has helped increase their innovation velocity.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"simple_quote$7e5ccc61-d861-495b-95dd-edeff075dfee\",\"slice_type\":\"simple_quote\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"LaunchDarkly helps customers increase their innovation velocity by 1) reducing the risk of delivering software dramatically, and 2) giving customers extreme control over what, when, and to whom they release. Here are a few examples: \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Autodesk increases release velocity by 500%\",\"spans\":[{\"start\":0,\"end\":8,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/how-autodesk-manages-mobile-app-releases-with-launchdarkly/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Paramount improves developer productivity 100x\",\"spans\":[{\"start\":0,\"end\":9,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/paramount-improves-developer-productivity-100x/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Christian Dior shortens time to market from 15 minutes to instant updates\",\"spans\":[{\"start\":0,\"end\":14,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/case-studies/dior/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Customers reported that LaunchDarkly has helped increase revenue, in some cases by over 50%\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"11% of customers estimate that LaunchDarkly has helped increase revenue growth by more than 50% \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"41% estimate an increase between 10% to 49%\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"33% estimate an increase of up to 10%\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"“In your estimation, how much has LaunchDarkly helped increase revenue growth tied to your software products?”\",\"spans\":[{\"start\":0,\"end\":110,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$4acd677a-1278-4675-bde4-6f1fc73cae4b\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1156},\"alt\":\"Impact of LaunchDarkly on revenue growth chart\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZrLlyUaF0TcGIvJQ_24-07-WakefieldSurveyJuly2024-LDCustomers-RevenueGrowth-3-.png?auto=format,compress\",\"id\":\"ZrLlyUaF0TcGIvJQ\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$33e69f1c-b8ba-4d9d-bcf1-13a8b6c6a842\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"LaunchDarkly helps customers increase revenue by enabling them to ship valuable software innovations faster. Also, the LaunchDarkly targeting engine enables them to deliver personalized experiences to users, in turn, increasing engagement and satisfaction. What’s more, developers and product managers can easily run beta tests and experiments with LaunchDarkly. By collecting and acting upon data early on, they end up releasing features that perform exceedingly well in the market. All of this can help drive revenue.\",\"spans\":[{\"start\":165,\"end\":197,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/core-services/targeting/\",\"target\":\"_blank\"}},{\"start\":317,\"end\":327,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/beta-testing-programs/\",\"target\":\"_blank\"}},{\"start\":332,\"end\":343,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/core-services/experimentation/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"LaunchDarkly reduces the operational costs of software delivery\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"8% of customers say LaunchDarkly has reduced their operational costs by over 50%.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"59% say LaunchDarkly has reduced their operational costs between 11% and 50%.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"26% say LaunchDarkly has reduced their operational costs up to 10%.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"“In your estimation, by how much has LaunchDarkly helped reduce your operational costs tied to software delivery?”\",\"spans\":[{\"start\":0,\"end\":114,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$3f51ca9f-9d4c-4056-8703-6998a642f360\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1285},\"alt\":null,\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZrLmLEaF0TcGIvJU_24-07-WakefieldSurveyJuly2024-LDCustomers-Cost-savings-2-.png?auto=format,compress\",\"id\":\"ZrLmLEaF0TcGIvJU\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$c70b7eca-2ddf-49ca-be66-9a7429c1fcb0\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"LaunchDarkly reduces the operational costs of software delivery by eliminating \\\"big-bang\\\" releases. A big-bang release looks like this:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Dozens—or hundreds—of highly-paid engineering personnel assemble at midnight or on the weekend to execute a major software launch. The launch includes updates from multiple development teams, all of whom had to a) run their changes through extensive pre-production testing, and b) wait for QA to approve every team's changes before merging their feature branches with the mainline—at which point costly merge conflicts arise. The fear of the release causing an outage looms large with a big-bang release.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"With LaunchDarkly feature flags, developers can safely test their code in a realistic production environment. This spares them the expense of maintaining staging environments that unreliably simulate production. What's more, teams—or even individual developers—can safely merge and deploy their code as soon as it's ready. And a single person can release that code patch whenever they choose. Should the patch degrade system performance, one person can disable it instantly in LaunchDarkly. Where there once was fear, there now is confidence...and lower operational costs.\",\"spans\":[{\"start\":5,\"end\":31,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/features/feature-flags/\",\"target\":\"_blank\"}},{\"start\":55,\"end\":108,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/testing-in-production-for-safety-and-sanity/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$a99a50e9-4c6d-4120-a987-f9d4b72334bd\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Software delivery and operational performance\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Software delivery and operational performance\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"See how you compare to LaunchDarkly customers when it comes to deployment frequency, MTTR, 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minutes.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Frequency of software reliability issues\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"“How often is the primary software service or application you work on unavailable, slow, or operating incorrectly?”\",\"spans\":[{\"start\":0,\"end\":115,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$7adbde6b-4634-4970-9b28-48633c33f94e\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1163},\"alt\":\"Frequency of software reliability issues LaunchDarkly 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release?”\",\"spans\":[{\"start\":0,\"end\":140,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$5134f1a7-6676-483c-a203-ced2b19773f4\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1140},\"alt\":\"Number of people required to execute a release - LaunchDarkly customers - chart\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZrLoF0aF0TcGIvJm_24-07-WakefieldSurveyJuly2024-LDCustomers-executearelease-1-.png?auto=format,compress\",\"id\":\"ZrLoF0aF0TcGIvJm\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$e4362860-5227-4ee2-bf9d-0282bd996d1f\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"Interestingly, nearly 70% of customers only require five people or less to execute a software release. This suggests that, for our customers, the overhead associated with delivering software—at least in terms of labor resources—is quite low. It’s not uncommon for engineering teams to require dozens, if not hundreds, of engineering personnel to execute a release. The fact that most LaunchDarkly customers can count on one hand the number of people they need for a launch is significant.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$11d1c857-e316-4d6b-bb14-b77283602390\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Feature management maturity and usage trends\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Feature management maturity and usage trends\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Use cases\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"“How does your team use LaunchDarkly?”\",\"spans\":[{\"start\":0,\"end\":38,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$d85551c2-d407-4c53-ae67-5b74150cfa44\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1465},\"alt\":\"Feature management use cases chart\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZrpnNkaF0TcGI336_24-07-WakefieldSurveyJuly2024-LDCustomers-Usecases-2-.png?auto=format,compress\",\"id\":\"ZrpnNkaF0TcGI336\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$551eca86-ff5d-4f85-b9a9-1a737400de7e\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"The top 3 most popular use cases for LaunchDarkly were dark launches, testing in production (canary tests), and progressive delivery.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Dark launches - turning features on/off for all users\",\"spans\":[{\"start\":0,\"end\":13,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/guide-to-dark-launching/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Testing in production (canary tests) - testing features with a subset of users to measure operational impact\",\"spans\":[{\"start\":0,\"end\":21,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/testing-in-production-for-safety-and-sanity/\",\"target\":\"_blank\"}},{\"start\":23,\"end\":35,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/four-common-deployment-strategies/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Progressive delivery - gradually releasing to increasingly large segments (includes percentage rollouts)\",\"spans\":[{\"start\":0,\"end\":20,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/what-is-progressive-delivery-all-about/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Beta tests - testing features with a subset of external users to gather qualitative feedback\",\"spans\":[{\"start\":0,\"end\":10,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/beta-testing-programs/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Experimentation - running A/B and multivariate tests to gather quantitative data\",\"spans\":[{\"start\":0,\"end\":15,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/a-guide-to-experimentation-in-launchdarkly/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Long-term operational controls - using permanent flags for things like load shedding during high-traffic periods\",\"spans\":[{\"start\":39,\"end\":54,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/guides/7-best-practices-for-short-term-and-permanent-feature/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Trunk-based development – smaller, more frequent updates to a main trunk\",\"spans\":[{\"start\":0,\"end\":23,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/introduction-to-trunk-based-development/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Entitlements and plan management - controlling feature/product access based on things like customer tier\",\"spans\":[{\"start\":0,\"end\":32,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/managing-entitlements-in-launchdarkly/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Level of LaunchDarkly adoption\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"“Which best describes your organization's level of adoption of LaunchDarkly?”\",\"spans\":[{\"start\":0,\"end\":77,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$7ba15a39-506e-4486-b3d6-4795de596c6d\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":967},\"alt\":\"Level of LaunchDarkly adoption chart\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZrLpAUaF0TcGIvJp_24-07-WakefieldSurveyJuly2024-LDCustomers-LaunchDarklyadoption-4-.png?auto=format,compress\",\"id\":\"ZrLpAUaF0TcGIvJp\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$f9221370-c68c-4b39-90e0-22b871d47fb7\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"A majority of LaunchDarkly customers (87%) have standardized their use of the platform on at least one team. Twenty-four percent have centralized and standardized their use of the platform across their entire organization, which represents a high degree of feature management maturity. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Feature flag usage\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"“For what percentage of code changes (frontend and backend) does your team use LaunchDarkly feature flags?”\",\"spans\":[{\"start\":0,\"end\":107,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$818bde3f-3c6e-4f26-8f3d-7d16c2853137\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1199},\"alt\":\"Feature flag usage chart\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZrLpPUaF0TcGIvJr_24-07-WakefieldSurveyJuly2024-LDCustomers-Changesinvolvingfeatureflags-1-.png?auto=format,compress\",\"id\":\"ZrLpPUaF0TcGIvJr\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$45b15a3d-520a-430d-83a0-4e0402e8bb27\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"Roughly one-fifth of LaunchDarkly customers (19%) use feature flags for more than 50% of software changes that they push to production. But most customers use flags for fewer than 50% of changes.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Integrations \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"“How many of the LaunchDarkly integrations (e.g., with Datadog, Github, Jira Cloud, Slack, etc.) does your team use?”\",\"spans\":[{\"start\":0,\"end\":117,\"type\":\"em\"},{\"start\":17,\"end\":42,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/integrations/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$fb321783-b472-4106-a34b-24b569b849c6\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1157},\"alt\":\"Number of integrations chart\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZrLphUaF0TcGIvJs_24-07-WakefieldSurveyJuly2024-LDCustomers-Numberofintegrations-2-.png?auto=format,compress\",\"id\":\"ZrLphUaF0TcGIvJs\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$89d03b44-f880-4ef1-a3f0-5d7e8c35536a\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"LaunchDarkly helps streamline critical workflows with 60+ integrations with popular tools in the modern DevOps tool chain like Datadog, GitHub, Jira Cloud, ServiceNow, and Slack. Currently, a majority of customers (89%) only leverage between zero and five integrations. \",\"spans\":[{\"start\":54,\"end\":70,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/integrations/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Automation\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"“Which of the LaunchDarkly automation features does your team use?”\",\"spans\":[{\"start\":0,\"end\":67,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$39acd060-f9a4-4051-a4e6-39592f0f7526\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1352},\"alt\":\"Automation features\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZrLpwkaF0TcGIvKa_24-07-WakefieldSurveyJuly2024-LDCustomers-Automationfeatures-2-.png?auto=format,compress\",\"id\":\"ZrLpwkaF0TcGIvKa\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$0f21ada7-956c-416d-9a1f-59da02f8a49e\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"LaunchDarkly offers several capabilities that automate workflows in software delivery, remediation, and change management. Far and away, the most popular of those automation capabilities are Approvals (41% of customers use Approvals) and Slack alerts (40% of customers).\",\"spans\":[{\"start\":46,\"end\":64,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/features/automation/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Approvals - automatically require and issue flag change approvals\",\"spans\":[{\"start\":0,\"end\":9,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/home/releases/approvals\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Automatic Slack alerts of flag updates and/or change approvals\",\"spans\":[{\"start\":10,\"end\":22,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/integrations/slack\",\"target\":\"_blank\"}},{\"start\":46,\"end\":62,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/integrations/slack/approvals\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Scheduling of software releases in advance\",\"spans\":[{\"start\":0,\"end\":10,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/home/releases/scheduled-changes\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Flag triggers/Automatic kill switches - automatically turn ‘off’ a flag when your observability tool detects a critical service issue\",\"spans\":[{\"start\":0,\"end\":37,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/home/releases/triggers\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Release Assistant - deliver features through repeatable release pipelines that follow an ordered set of environments and targeting rules\",\"spans\":[{\"start\":0,\"end\":17,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/release-assistant-automation-monitoring-ux-improvements/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Automatic flag syncing with Jira Cloud\",\"spans\":[{\"start\":28,\"end\":38,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/integrations/jira\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Automatic generation of ServiceNow tickets\",\"spans\":[{\"start\":24,\"end\":42,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.launchdarkly.com/integrations/servicenow\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$b7e2657d-8682-4d06-8cf1-5fb343dfcf3e\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Conclusion\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Conclusion\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"LaunchDarkly customers have spoken. The LaunchDarkly platform has a material impact on the bottom line, improving everything from operational efficiency and innovation velocity to revenue growth and customer satisfaction. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"In a software-powered world, LaunchDarkly enables product delivery teams to ship software faster, more intelligently, and with less risk. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"If you’re interested in seeing a live demo of the LaunchDarkly feature management and experimentation platform, request a demo here. You may also start a free trial of the product. To learn more about LaunchDarkly and how it may transform the way you deliver software, visit launchdarkly.com.\",\"spans\":[{\"start\":112,\"end\":131,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/request-a-demo/\",\"target\":\"_blank\"}},{\"start\":154,\"end\":164,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/request-a-demo/\",\"target\":\"_blank\"}},{\"start\":275,\"end\":291,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"http://launchdarkly.com\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"---\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"About the survey\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"The LaunchDarkly Customer Survey was conducted by Wakefield Research (www.wakefieldresearch.com) among 250 DevOps and IT Professionals, between April 23rd and May 1st, 2024, using an email invitation distributed by LaunchDarkly.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Respondents spanned multiple industries, company sizes, and annual revenue amounts. They also ranged from individual contributors to C-level executives, including job titles such as Software Developer, VP of Engineering, IT Director, Platform Engineer, CTO, and more. Results of any sample are subject to sampling variation.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$901c3745-8357-47ff-b910-9a7fc2e21976\",\"slice_type\":\"wysiwyg\",\"slice_label\":null}],\"meta_title\":[{\"type\":\"heading1\",\"text\":\"2024 Survey: Impact of LaunchDarkly on Customer Outcomes\",\"spans\":[],\"direction\":\"ltr\"}],\"meta_description\":[{\"type\":\"paragraph\",\"text\":\"Learn how LaunchDarkly drives high innovation velocity, operational efficiency, and revenue growth for customers. 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In theory, the more lines of code you test (i.e., the higher your code coverage), the more likely you’ll find harmful defects. Although high code coverage doesn’t guarantee high quality, it’s an important part of any risk mitigation strategy. And generally speaking, low code coverage is associated with a higher risk of software instability.\",\"spans\":[{\"start\":45,\"end\":58,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/comprehensive-guide-smoke-testing-software-development/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Benefits of high code coverage\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Improved quality: High code coverage often correlates with fewer bugs and higher software quality. 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This is typically done using code coverage tools and frameworks that provide detailed reports. Code coverage, or test coverage, will appear as a percentage like 80% code coverage, 90%, etc. \",\"spans\":[{\"start\":74,\"end\":82,\"type\":\"em\"},{\"start\":87,\"end\":98,\"type\":\"em\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Why don’t automated tests cover 100% of your code every time?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Usually, automated tests fail to cover 100% of your code because the code is low quality and has a high degree of cyclomatic complexity. Also, it could be because you do not have a downstream dependency spun up when running the unit test.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Unreasonable standards can halt progress in trying to make things perfect. Releasing new functionality to the market without creating a mountain of tech debt is a challenge.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$02782db8-70ee-4678-8698-a033031924c0\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Industry benchmarks\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Industry benchmarks\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"What is considered “good” code coverage?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Generally, code coverage between 80 and 90% is strong. Obviously, the amount of code in question influences the difficulty of achieving such coverage. After all, testing a large percentage of 700 lines of code (LoC) is easier than 15,000.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"As a frame of reference, one study of 47 software projects spanning seven programming languages found an average code coverage of 74-76%.[1] The average project duration was 20 months, and the average LoC across the software projects was 8,178.\",\"spans\":[{\"start\":130,\"end\":136,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"In another study, a participant whose team achieved 100% code coverage in a large space software project remarked: “When you have reached more than 90%, you are doing well.”[2]\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"As a rule of thumb, Google considers 60% “acceptable”, 75% “commendable,” and 90% “exemplary\\\". (source)\",\"spans\":[{\"start\":96,\"end\":102,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://testing.googleblog.com/2020/08/code-coverage-best-practices.html\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$2a898ff5-65f8-402d-9912-39cbc70bc213\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":1247},\"alt\":null,\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/Zqj75x5LeNNTxmZv_24-07-OnCodeCoverageinSoftwareTesting-Table2.png?auto=format,compress\",\"id\":\"Zqj75x5LeNNTxmZv\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$b43662c8-5da1-4c3f-839e-b88d91c355d4\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"A study of 47 software projects found an average code coverage of 74-76%.\",\"spans\":[{\"start\":0,\"end\":73,\"type\":\"em\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$2f8f067c-9101-407d-9506-8723964c49c7\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"heading3\",\"text\":\"Is 100% code coverage necessary or desirable?\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Though possible, it’s unusual to achieve 100% code coverage for your whole codebase. And if you were to reach 100% coverage, it’d require enormous effort.\",\"spans\":[{\"start\":96,\"end\":100,\"type\":\"em\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"When dealing with highly critical software, which affects human health and safety or can irreparably destroy the machine it powers (e.g., a spacecraft), you may want—or be required—to achieve near 100% test coverage. For example, in one study, a development team managing a laser communication software project for satellites was required to achieve 100% coverage. And they did. But accomplishing this feat was extremely difficult: two developers worked painstakingly for two years to reach 100% test coverage for 25,000 LoC.[3] \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Interestingly, the authors of the study observed that getting from 95 to 100% coverage required a great deal more effort (proportionally) than getting from 0 to 95%. Due to the high effort in the last mile of coverage, you actually introduce risk when aiming for excessively high coverage. Such risks might include a delayed time to market.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"If your development team is strapped for resources, your software systems are not “highly” critical, and you need to move fast, then it’s probably best to avoid pursuing 100% coverage.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"That said, achieving near 100% coverage is more feasible for specific “patches”, i.e., new lines of code.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$0cc6b872-4677-4a45-99d2-c4175d6a298d\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Getting started with code coverage\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Getting started with code coverage\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Setting up code coverage tools\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"To get started, integrate a code coverage tool appropriate for your programming language into your development environment. 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While 100% coverage is ideal, as mentioned, it’s often impractical. Focus on critical and frequently used parts of the codebase. Adjust your coverage goals based on the:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Potential consequences of a software failure for the application being tested - e.g., if you’re testing a less critical piece of software, then you may aim for modest coverage goals (80%).\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Broader goals of the software project - e.g., if the primary goal of a project is to get the new software product to market as quickly as possible, then you should set modest coverage goals to accommodate the need for speed.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Other software testing and risk mitigation measures you’ve employed - e.g., if you have strong, holistic testing procedures in place, then you may be able to justify lowering your coverage goals, at least slightly.\",\"spans\":[],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$132f940a-ec86-4092-9295-a310f7503dc3\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"content\":[{\"type\":\"paragraph\",\"text\":\"“100%: it sounds really good. 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For example, critical applications might require higher branch and path coverage.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Aim for a balance between achieving high coverage and low testing overhead. Avoid excessive focus on coverage at the expense of overall software engineering performance and business objectives. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Interpreting coverage reports\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Coverage reports usually highlight executed and unexecuted parts of the code, providing percentages and visualizations that help in understanding the extent of coverage.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"In this sample dashboard of Codecov, a code coverage tool, we see a branch coverage of 95.4%. (Source)\",\"spans\":[{\"start\":95,\"end\":101,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.codecov.com/docs/quick-start\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$4c824624-3826-4e85-81d2-a3837ec89e9b\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":930},\"alt\":\"Codecov sample dashboard\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZqkK8h5LeNNTxmlE_24-07-OnCodeCoverageinSoftwareTesting-CoverageReport-1-.png?auto=format,compress\",\"id\":\"ZqkK8h5LeNNTxmlE\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$013c01de-1c95-4f48-9d47-83147c85a3af\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"paragraph\",\"text\":\"In this sample coverage report in Coverage.py, another code coverage tool, we see two files containing a total of 76 statements, with 10 statements missed during testing, resulting in 87% test coverage. (Source)\",\"spans\":[{\"start\":204,\"end\":210,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://coverage.readthedocs.io/en/7.5.4/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$0f3402ed-19ad-4b80-a7a7-09672ebdb18f\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"image\":{\"dimensions\":{\"width\":1800,\"height\":469},\"alt\":\"Coverage.py sample report\",\"copyright\":null,\"url\":\"https://images.prismic.io/launchdarkly/ZqkLJh5LeNNTxmlK_24-07-OnCodeCoverageinSoftwareTesting-CoverageReport.png?auto=format,compress\",\"id\":\"ZqkLJh5LeNNTxmlK\",\"edit\":{\"x\":0,\"y\":0,\"zoom\":1,\"background\":\"transparent\"}},\"lightbox\":true,\"image_link\":{\"link_type\":\"Any\"}},\"items\":[],\"id\":\"image$961ede23-5535-4788-8ce8-de644975e7d1\",\"slice_type\":\"image\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Best practices for improving code coverage\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Best practices for improving code coverage\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Write testable code - Develop code with testability in mind. Avoid complex and tightly coupled code structures.\",\"spans\":[{\"start\":0,\"end\":19,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Identify and address gaps - Regularly review coverage reports to identify untested parts of the code and write additional tests to cover these gaps.\",\"spans\":[{\"start\":0,\"end\":25,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Continuous integration and reporting - Automate code coverage reporting in your CI pipeline to monitor coverage trends over time and catch regressions early.\",\"spans\":[{\"start\":0,\"end\":37,\"type\":\"strong\"},{\"start\":38,\"end\":39,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Code coverage in practice\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading4\",\"text\":\"Real-world examples\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Here are a few real-world examples of organizations that improved their software reliability as a result of increasing their code coverage:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Fitch Solutions went 100 days without downtime after increasing their code coverage\",\"spans\":[{\"start\":0,\"end\":46,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.parasoft.com/resources/case-studies/fitch-delivers-high-code-coverage-quality-for-microservices-applications/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"After improving code coverage, Vevo reduced tech support time by ~60%\",\"spans\":[{\"start\":31,\"end\":69,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.codacy.com/resources/case-study-vevo\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Goldman Sachs improved code quality and security after increasing code coverage of legacy code\",\"spans\":[{\"start\":0,\"end\":35,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.diffblue.com/case-studies/goldman-sachs-complete-a-years-worth-of-java-unit-test-writing-overnight-with-diffblue-cover/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading4\",\"text\":\"Challenges and limitations\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Be aware of challenges such as the overhead of maintaining tests and the false sense of security high coverage might provide if tests are not well-designed. High coverage does not guarantee high reliability. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading4\",\"text\":\"Combining with other techniques\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Combine code coverage with other testing techniques like static analysis, peer reviews, and even controlled testing in production for comprehensive quality assurance.\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Usage in industry\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Standards and guidelines - Adopt industry standards and guidelines for code coverage, such as those from ISO.\",\"spans\":[{\"start\":0,\"end\":27,\"type\":\"strong\"},{\"start\":105,\"end\":108,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://about.codecov.io/blog/the-role-of-code-coverage-in-regulations-and-standards/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Organizational approaches - Different organizations might have varying approaches. For instance, startups might prioritize rapid development over high coverage, while financial institutions might enforce strict coverage policies.\",\"spans\":[{\"start\":0,\"end\":25,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Part of quality metrics - Include code coverage as a part of a broader set of quality metrics, alongside code complexity and defect density.\",\"spans\":[{\"start\":0,\"end\":23,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Maintaining high code coverage\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Sustain coverage over time - Regularly update tests to cover new code and refactored parts of the application to maintain high coverage levels.\",\"spans\":[{\"start\":0,\"end\":29,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Deal with legacy code - In this context, legacy code refers to code that was written before modern software testing practices emerged. It’s advised to address coverage in legacy code incrementally. Start with the most critical parts and gradually increase coverage. Also, you can leverage tools that automate the process of increasing code coverage for legacy code.\",\"spans\":[{\"start\":0,\"end\":21,\"type\":\"strong\"},{\"start\":280,\"end\":294,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.diffblue.com/case-studies/goldman-sachs-complete-a-years-worth-of-java-unit-test-writing-overnight-with-diffblue-cover/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Automate tracking and reporting - Automate the process of tracking and reporting coverage to reduce manual effort and ensure consistency.\",\"spans\":[{\"start\":0,\"end\":32,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Follow SOLID principles - Following things like SOLID principles will make code easier to test.\",\"spans\":[{\"start\":0,\"end\":23,\"type\":\"strong\"},{\"start\":48,\"end\":64,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://dave.cheney.net/2016/08/20/solid-go-design\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Pay attention to cyclomatic complexity - Cyclomatic complexity indicates that code may be degrading in quality, in turn, creating testing difficulties.\",\"spans\":[{\"start\":0,\"end\":38,\"type\":\"strong\"},{\"start\":41,\"end\":62,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.ibm.com/docs/en/raa/6.1?topic=metrics-cyclomatic-complexity\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Code coverage and testing frameworks\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading4\",\"text\":\"Popular testing frameworks\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Use frameworks like JUnit for Java, pytest for Python, and Mocha for JavaScript, which have built-in support for code coverage. Integrate coverage tools with these frameworks to streamline the process and enhance reporting. Use the data from coverage reports to optimize tests, focusing on high-risk and frequently changed parts of the code.\",\"spans\":[{\"start\":20,\"end\":34,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://junit.org/junit5/\",\"target\":\"_blank\"}},{\"start\":36,\"end\":53,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://docs.pytest.org/en/7.1.x/getting-started.html\",\"target\":\"_blank\"}},{\"start\":59,\"end\":79,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://mochajs.org/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$07610a94-9cf9-4f25-a6e4-231fef75ae73\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Code coverage in CI/CD\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Code coverage in CI/CD\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"heading3\",\"text\":\"Integrating into your development workflow and CI/CD pipeline\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"You can integrate code coverage tools into your continuous integration (CI) pipeline, making code coverage a standard part of every build. How you integrate code coverage into your automated testing process depends on the programming language and specific code coverage tool. Implementing code coverage checks in your CI/CD pipelines enables you to catch issues early in the development cycle. \",\"spans\":[{\"start\":318,\"end\":333,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/cicd-best-practices-devops/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Set thresholds - Set minimum coverage thresholds that must be met for code to be merged or released. \",\"spans\":[{\"start\":0,\"end\":15,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Use code coverage as a gate - Utilize coverage metrics as a gate in your deployment process, allowing only code that meets the required coverage to be deployed.\",\"spans\":[{\"start\":0,\"end\":27,\"type\":\"strong\"}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$a7969c3a-accf-45d9-a0d5-5712408fc4f7\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Code coverage and software quality\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Code coverage and software quality\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Measure of quality - Use code coverage as one of the indicators of software quality, but not the sole determinant.\",\"spans\":[{\"start\":0,\"end\":21,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Combined metrics - Combine coverage with other metrics like change fail rates and user satisfaction to get a holistic view of software quality.\",\"spans\":[{\"start\":0,\"end\":17,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"list-item\",\"text\":\"Establishing standards - Set organizational standards for code coverage to maintain consistency and high quality across projects.\",\"spans\":[{\"start\":0,\"end\":23,\"type\":\"strong\"},{\"start\":24,\"end\":25,\"type\":\"strong\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Again, we must reiterate that just because you’ve tested a large portion of your codebase does not mean you’ll necessarily avert an outage. Bugs may still lurk in your code. You must, therefore, employ multiple risk mitigation strategies to ensure high stability. \",\"spans\":[{\"start\":211,\"end\":237,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/risk-mitigation-strategies-software-releases/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$d4a89d95-2e84-4658-b737-432181945985\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[{\"type\":\"paragraph\",\"text\":\"Limits of pre-production testing and code coverage\",\"spans\":[],\"direction\":\"ltr\"}],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Limits of pre-production testing and code coverage\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"No matter how much pre-production testing you do, you’re merely approximating production. Such tests cannot perfectly replicate a real-world environment with large-scale production traffic. In some cases, despite extensive pre-production testing, when you release changes to production, they cause your app to go down for an unknown reason.\",\"spans\":[{\"start\":78,\"end\":88,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/what-is-a-production-environment/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"This is why, in addition to pre-production testing, we advise using feature flags to test in production with a small subset of users and environments. Doing so, gives you a more accurate idea of how software changes will impact operational health when exposed to a large volume of production traffic.\",\"spans\":[{\"start\":85,\"end\":103,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/testing-in-production-for-safety-and-sanity/\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"}]},\"items\":[],\"id\":\"wysiwyg$3340501b-a392-41e0-af5f-9733c969301b\",\"slice_type\":\"wysiwyg\",\"slice_label\":null},{\"primary\":{\"toc_title\":[],\"wysiwyg\":[{\"type\":\"heading2\",\"text\":\"Footnotes\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"[1] Michael Hilton, Jonathan Bell, and Darko Marinov. 2018. A Large-Scale Study of Test Coverage Evolution. In Proceedings of the 2018 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE ’18), September 3–7, 2018, Montpellier, France. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/3238147.3238183\",\"spans\":[{\"start\":59,\"end\":108,\"type\":\"em\"}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"[2] Christian Prause, Jürgen Werner, Kay Hornig, Sascha Bosecker, and Marco Kuhrmann. 2017. Is 100% Test Coverage a Reasonable Requirement? Lessons Learned from a Space Software Project. Conference: International Conference on Product-Focused Software Process Improvement. 10.1007/978-3-319-69926-4_25.  https://www.researchgate.net/publication/319141355_Is_100_Test_Coverage_a_Reasonable_Requirement_Lessons_Learned_from_a_Space_Software_Project\",\"spans\":[{\"start\":3,\"end\":4,\"type\":\"em\"},{\"start\":92,\"end\":185,\"type\":\"em\"},{\"start\":304,\"end\":446,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://www.researchgate.net/publication/319141355_Is_100_Test_Coverage_a_Reasonable_Requirement_Lessons_Learned_from_a_Space_Software_Project\",\"target\":\"_blank\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"[3] Ibid. 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pace of innovation and software delivery is at an all time high, which is an exciting and encouraging development. But as our world becomes increasingly reliant on digital solutions, and those solutions become more and more interconnected, now it’s time to pause and ensure we’re doing everything we can as an industry to minimize the inherent risks of software delivery. The scope and process of how we manage software is more crucial than ever—not only for the vendors of such software, but for end users across the world and across industries. This, coupled with the increased output of code, driven in large part by innovation in AI-assisted development, means the stakes are higher and the risks greater for technology providers than ever before.\",\"spans\":[{\"start\":638,\"end\":661,\"type\":\"hyperlink\",\"data\":{\"link_type\":\"Web\",\"url\":\"https://launchdarkly.com/blog/prevent-ai-coding-errors-in-production/\",\"target\":\"_self\"}}],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"Let's face it: bugs are inevitable. From the early days of coding on punch cards to today's much more advanced workflows, developers have always had to face unexpected issues. All of us can empathize with the frustration and embarrassment of an outage or buggy software. But while bugs are inevitable, the disruptions they can cause don't have to be. \",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"paragraph\",\"text\":\"It’s estimated that a significant portion of outages are internally generated—not third-party-based, infrastructure-driven, or from other external forces. This highlights the importance of internal processes and tools to help minimize these risks. At LaunchDarkly, we believe that together, we can help prevent these disruptions to your business and ensure a smoother software delivery experience for your engineering teams, here's how to start:\",\"spans\":[],\"direction\":\"ltr\"},{\"type\":\"o-list-item\",\"text\":\"Progressive Rollouts: Gradually introducing new features enables controlled exposure and real-time impact assessment. Instead of deploying new features to all users simultaneously, start with a small segment—perhaps 1%, then increase to 5%, and 10%—moving to the next group only when you're confident in the stability of your code. 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