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Learn how splitting workloads can improve your monolithic architecture&#x27;s performance and scalability, and understand the trade-offs between monolithic systems and microservices."/><meta name="keywords" content="incident,incident management,incident response,post mortem,outage,slack incident,incident channel"/><meta name="slack-app-id" content="A01DEGPUHHC"/><link rel="canonical" href="https://incident.io/blog/monolith"/><link rel="alternate" type="text/markdown" href="https://incident.io/blog/monolith.md"/><meta property="og:title" content="Keep the monolith, but split the workloads | Blog | incident.io"/><meta property="og:description" content="Everybody loves a monolith, but you can hit issues as you scale. Learn how splitting workloads can improve your monolithic architecture&#x27;s performance and scalability, and understand the trade-offs between monolithic systems and microservices."/><meta property="og:image" content="https://incident.io/socialcard/blog/monolith?1728933656000"/><meta property="og:image:width" content="1200"/><meta property="og:image:height" content="628"/><meta name="twitter:card" content="summary_large_image"/><meta name="twitter:site" content="@incident_io"/><meta name="twitter:creator" content="@incident_io"/><meta name="twitter:title" content="Keep the monolith, but split the workloads | Blog"/><meta name="twitter:description" content="Everybody loves a monolith, but you can hit issues as you scale. 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your monolith for database efficiency</a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500" href="#keeping-a-monolithic-architecture-can-still-be-a-smart-choice-for-scaling">Keeping a monolithic architecture can still be a smart choice for scaling</a></li></ul></div></div><div class="lg:max-w-[788px] grow flex flex-col gap-4 lg:gap-10" id="content-top"><div class="flex flex-col gap-4"><div class="flex flex-col gap-2"><h1 class="text-h3 text-balance">Keep the monolith, but split the workloads</h1></div><div class="flex flex-col gap-2 md:flex-row justify-between mt-auto"><div class="flex items-center gap-2"><span class="flex items-center gap-2"><div class="size-[22px] rounded-full overflow-hidden shrink-0"></div><a class="text-body-sm-emphasis leading-[1.1] w-min sm:w-auto transition hover:text-alarmalade-500" href="/blog/author/lawrence">Lawrence Jones</a></span></div><div class="text-body-sm text-content-secondary">April 12, 2023<span> — <!-- -->10 min read</span></div></div></div><div class="relative"><span class="relative overflow-hidden block align-top transition-opacity opacity-0 w-full rounded-lg"><img alt="" width="2181" height="940" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent;view-transition-name:blog-monolith" sizes="100vw" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F74ffb757eec8e6ba9e64884868346732e7231452-2181x940.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=60&amp;q=75 60w, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F74ffb757eec8e6ba9e64884868346732e7231452-2181x940.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=64&amp;q=75 64w, 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/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F74ffb757eec8e6ba9e64884868346732e7231452-2181x940.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=1200&amp;q=75 1200w, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F74ffb757eec8e6ba9e64884868346732e7231452-2181x940.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=1920&amp;q=75 1920w, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F74ffb757eec8e6ba9e64884868346732e7231452-2181x940.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=2048&amp;q=75 2048w, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F74ffb757eec8e6ba9e64884868346732e7231452-2181x940.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75 3840w" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F74ffb757eec8e6ba9e64884868346732e7231452-2181x940.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75"/></span></div><div class="prose prose-orange text-body max-w-none mb-6"><p class="">I’m a big fan of monolithic architectures. Writing code is hard enough without each function call requiring a network request, and that’s before considering the investment in observability, RPC frameworks, and dev environments you need to be productive in a microservice environment.</p><p class="">But having spent half a decade stewarding a Ruby monolith from 20 to 200 engineers and watched its modest 10GB Postgres database grow beyond 5TB, there’s a point where the pain outweighs the benefits.</p><p class="">This post is about splitting your workloads, a technique that can significantly reduce that pain, costs little and can be applied early as you scale. Something that, if executed well, can let you enjoy that sweet monolithic goodness for that much longer.</p><p class="">Let’s dive in!</p><h2 id="a-wild-outage-appears" class=""><a class="heading-link" href="#a-wild-outage-appears"><span class="icon icon-link"></span></a>A wild outage appears!</h2><p class="">Back in November 2022, we had an outage we affectionately called <a href="https://incident.io/blog/intermittent-downtime" target="_blank" rel="noopener noreferrer" class="">“Intermittent downtime from repeated crashes”</a>.</p><p class="">Probably the first genuinely major outage we’ve faced, it resulted in our app repeatedly crashing over a period of 32 minutes. Pretty stressful stuff, even for responders who spend their entire day jobs building incident tooling.</p><p class="">While the post-mortem goes into detail, the gist of the issue was:</p><ul><li>We run our app as a Go monolith in Heroku, using Heroku Postgres as a database, and GCP Pub/Sub as an async message queue.</li><li>Our application runs several replicas of a single binary running web, worker, and cron threads.</li><li>When a bad Pub/Sub message was pulled into the binary, an unhandled panic would crash the entire app, meaning web, workers, and crons all died.</li></ul><p class="">Well, that sucks and seems easily avoidable. If only we’d built everything as microservices, we’d only have crashed the service responsible for that message, right?</p><h2 id="understanding-reliability-in-monolithic-systems-vs-microservices" class=""><a class="heading-link" href="#understanding-reliability-in-monolithic-systems-vs-microservices"><span class="icon icon-link"></span></a>Understanding reliability in monolithic systems vs. microservices</h2><p class="">The most common reason teams opt for a microservice architecture tends to be for reliability or scalability, often used interchangeably.</p><p class="">This means that:</p><ul><li>The blast radius of problems – such as the bad Pub/Sub message we saw above – is limited to the service it runs in, often allowing the service to degrade gracefully (continue serving most requests, failing only for certain features).</li><li>Each microservice can manage its own resources such as setting limits for CPU or memory that can be scaled to whatever that service needs at the time. This prevents a bad code path from consuming all of a limited resource and impacting other code, as it might in a monolithic app.</li></ul><p class="">Microservices certainly solve these problems but come with a huge amount of associated baggage (distributed system problems, RPC frameworks, etc). If we want the benefits of microservices without the baggage, we’ll need some alternative solutions.</p><h2 id="rule-1-never-mix-workloads-" class=""><a class="heading-link" href="#rule-1-never-mix-workloads-"><span class="icon icon-link"></span></a>Rule 1: Never mix workloads </h2><p class="">First, we should apply the cardinal rule of running monoliths, which is: never mix your workloads.</p><p class="">For our incident.io app, we have three key workloads:</p><ul><li>Web servers that handle incoming requests.</li><li>Pub/Sub subscribers that process async work.</li><li>Cron jobs that fire on a schedule.</li></ul><p class="">We were breaking this rule by running all of this code inside of the same process (as in, literally the same linux process). By mixing workloads we left ourselves open to:</p><ul><li>Bad code in a specific part of the codebase bringing down the whole app, as in our November incident.</li><li>If we deployed a Pub/Sub subscriber that was CPU heavy (maybe compressing Slack images, or a badly written loop that spun indefinitely) we’d impact the entire app, causing all web/worker/cron activity to slow to a halt. CPU in that process is a limited resource and by consuming 90% of it, we’d leave only 10% left for the other work.</li></ul><p class="">The same day as our incident occurred, we split our app into separate tiers of deployment for each workload type. This meant creating three separate dyno tiers in Heroku, which for those unfamiliar with Heroku just means three independent deployments of the app processing only its own type of workload.</p><p class=""></p><figure class=""><span class="relative overflow-hidden block align-top"><img alt="" data-zoom-src="https://cdn.sanity.io/images/oqy5aexb/production/655ac9e2d799c4b7d71bfa9f3edbd812961b03e8-1726x566.png?q=85&amp;auto=format" loading="lazy" width="1726" height="566" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" src="https://cdn.sanity.io/images/oqy5aexb/production/655ac9e2d799c4b7d71bfa9f3edbd812961b03e8-1726x566.png?w=2000&amp;q=80&amp;fit=max&amp;auto=format"/></span></figure><p class="">You might ask if we’re doing this, then why not go the whole way and have separate microservices?</p><p class="">The answer is that this split preserves all the benefits of the monolith while solving the problems we presented above. Every deployment is running the same code, using the same Docker image and environment variables, the only thing that differs is the command we run to start the code. No complex dev setup required, or RPC framework needed, it’s the same old monolith, just operated differently.</p><p class="">Our application entry point code looks a bit like this:</p><pre class="refractor language-go"><code class="language-go"><span class="token keyword">package</span> main
<span class="token keyword">var</span> <span class="token punctuation">(</span>
app <span class="token operator">=</span> kingpin<span class="token punctuation">.</span><span class="token function">New</span><span class="token punctuation">(</span><span class="token string">&quot;app&quot;</span><span class="token punctuation">,</span> <span class="token string">&quot;incident.io&quot;</span><span class="token punctuation">)</span>
web <span class="token operator">=</span> app<span class="token punctuation">.</span><span class="token function">Flag</span><span class="token punctuation">(</span><span class="token string">&quot;web&quot;</span><span class="token punctuation">,</span> <span class="token string">&quot;Run web server&quot;</span><span class="token punctuation">)</span><span class="token punctuation">.</span><span class="token function">Bool</span><span class="token punctuation">(</span><span class="token punctuation">)</span>
workers <span class="token operator">=</span> app<span class="token punctuation">.</span><span class="token function">Flag</span><span class="token punctuation">(</span><span class="token string">&quot;workers&quot;</span><span class="token punctuation">,</span> <span class="token string">&quot;Run async workers&quot;</span><span class="token punctuation">)</span><span class="token punctuation">.</span><span class="token function">Bool</span><span class="token punctuation">(</span><span class="token punctuation">)</span>
cron <span class="token operator">=</span> app<span class="token punctuation">.</span><span class="token function">Flag</span><span class="token punctuation">(</span><span class="token string">&quot;cron&quot;</span><span class="token punctuation">,</span> <span class="token string">&quot;Run cron jobs&quot;</span><span class="token punctuation">)</span><span class="token punctuation">.</span><span class="token function">Bool</span><span class="token punctuation">(</span><span class="token punctuation">)</span>
<span class="token punctuation">)</span>
<span class="token keyword">func</span> <span class="token function">main</span><span class="token punctuation">(</span><span class="token punctuation">)</span> <span class="token punctuation">{</span>
<span class="token keyword">if</span> <span class="token operator">*</span>web <span class="token punctuation">{</span>
<span class="token comment">// run web</span>
<span class="token punctuation">}</span>
<span class="token keyword">if</span> <span class="token operator">*</span>workers <span class="token punctuation">{</span>
<span class="token comment">// run workers</span>
<span class="token punctuation">}</span>
<span class="token keyword">if</span> <span class="token operator">*</span>cron <span class="token punctuation">{</span>
<span class="token comment">// run cron</span>
<span class="token punctuation">}</span>
<span class="token function">wait</span><span class="token punctuation">(</span><span class="token punctuation">)</span>
<span class="token punctuation">}</span>
</code></pre><p class="">You can easily add this to any application, with the neat benefit that for your local development environment, you can have all components running in a single hot-reloaded process (a pipe dream for many microservice shops!).</p><p class="">As a small catch to switching over blindly, be aware that code assuming everything runs within the same process is both hard to recognize, subtly buggy, and difficult to fix. If, for example, your web server code stashes data in a process-local cache that the worker attempts to use, you’re going to have a sad time.</p><p class="">The good news is those dependencies are generally code smells are easily solved by pushing coordination into an external store such as Postgres or Redis, and won’t reappear after you’ve made the initial change. Worth doing even if you aren’t splitting your code, in my opinion.</p><p class="">Note there’s no limit to how granular you split these workloads. I’ve seen a deployment per queue or even job class before, going up to ~20 deployments for a single application environment.</p><h2 id="rule-2-apply-guardrails-to-your-monolith-for-database-efficiency" class=""><a class="heading-link" href="#rule-2-apply-guardrails-to-your-monolith-for-database-efficiency"><span class="icon icon-link"></span></a>Rule 2: Apply guardrails to your monolith for database efficiency</h2><p class="">Ok, so our monolith is no longer a big bundle of code running all the things: it’s three separate, isolated deployments that can succeed or fail independently. Great.</p><p class="">Most people’s applications aren’t just about the code running in the process, though. One of the most significant reliability risks is rogue or even well-behaved but unfortunately timed code consuming the most precious of a monoliths limited resources, which is usually…</p><p class="">Database capacity. In our case, Postgres.</p><p class="">Even having split your workloads, you’ll always have the underlying data store that needs some form of protection. And this is where microservices – which often try to share nothing – can help, with each service deployment only able to indirectly consume database time via another services API.</p><p class="">This is solvable in our monolith though, we just need to <strong>create guardrails and limits around resource consumption</strong>. Limits that can be arbitrarily granular.</p><p class="">In our code, the guardrails around our Postgres database look like this:</p><pre class="refractor language-go"><code class="language-go"><span class="token keyword">package</span> main
<span class="token keyword">var</span> <span class="token punctuation">(</span>
<span class="token comment">// ...</span>
workers <span class="token operator">=</span> app<span class="token punctuation">.</span><span class="token function">Flag</span><span class="token punctuation">(</span><span class="token string">&quot;workers&quot;</span><span class="token punctuation">,</span> <span class="token string">&quot;Run async workers&quot;</span><span class="token punctuation">)</span><span class="token punctuation">.</span><span class="token function">Bool</span><span class="token punctuation">(</span><span class="token punctuation">)</span>
workersDatabase <span class="token operator">=</span> <span class="token function">new</span><span class="token punctuation">(</span>database<span class="token punctuation">.</span>ConnectOptions<span class="token punctuation">)</span><span class="token punctuation">.</span><span class="token function">Bind</span><span class="token punctuation">(</span>
app<span class="token punctuation">,</span> <span class="token string">&quot;workers.database.&quot;</span><span class="token punctuation">,</span> <span class="token number">20</span><span class="token punctuation">,</span> <span class="token number">5</span><span class="token punctuation">,</span> <span class="token string">&quot;30s&quot;</span><span class="token punctuation">)</span>
<span class="token punctuation">)</span>
<span class="token keyword">func</span> <span class="token function">main</span><span class="token punctuation">(</span><span class="token punctuation">)</span> <span class="token punctuation">{</span>
<span class="token comment">// ...</span>
<span class="token keyword">if</span> <span class="token operator">*</span>workers <span class="token punctuation">{</span>
db<span class="token punctuation">,</span> err <span class="token operator">:=</span> <span class="token function">createDatabasePool</span><span class="token punctuation">(</span>ctx<span class="token punctuation">,</span> <span class="token string">&quot;worker&quot;</span><span class="token punctuation">,</span> workersDatabase<span class="token punctuation">)</span>
<span class="token keyword">if</span> err <span class="token operator">!=</span> <span class="token boolean">nil</span> <span class="token punctuation">{</span>
<span class="token keyword">return</span> errors<span class="token punctuation">.</span><span class="token function">Wrap</span><span class="token punctuation">(</span>err<span class="token punctuation">,</span> <span class="token string">&quot;connecting to Postgres pool for workers&quot;</span><span class="token punctuation">)</span>
<span class="token punctuation">}</span>
<span class="token function">runWorkers</span><span class="token punctuation">(</span>db<span class="token punctuation">)</span> <span class="token comment">// start running workers</span>
<span class="token punctuation">}</span>
<span class="token punctuation">}</span>
</code></pre><p class="">This code sets and allows customization of the database pool used specifically for workers. The defaults mean “maximum of 20 active connections, allowing up to 5 idle connections, with a 30s statement timeout”.</p><p class="">Perhaps easier to see from the <code>app --help</code> output:</p><pre class="refractor language-go"><code class="language-go"><span class="token operator">--</span>workers<span class="token punctuation">.</span>database<span class="token punctuation">.</span>max<span class="token operator">-</span>open<span class="token operator">-</span>connections<span class="token operator">=</span><span class="token number">20</span>
Max database connections to open against the Postgres server
<span class="token operator">--</span>workers<span class="token punctuation">.</span>database<span class="token punctuation">.</span>max<span class="token operator">-</span>idle<span class="token operator">-</span>connections<span class="token operator">=</span><span class="token number">5</span>
Max database connections to keep open while idle
<span class="token operator">--</span>workers<span class="token punctuation">.</span>database<span class="token punctuation">.</span>max<span class="token operator">-</span>connection<span class="token operator">-</span>idle<span class="token operator">-</span>time<span class="token operator">=</span>10m
Max time to wait before closing idle Postgres server connections
<span class="token operator">--</span>workers<span class="token punctuation">.</span>database<span class="token punctuation">.</span>max<span class="token operator">-</span>connection<span class="token operator">-</span>lifetime<span class="token operator">=</span>60m
Max time to reuse a connection before recycling it
<span class="token operator">--</span>workers<span class="token punctuation">.</span>database<span class="token punctuation">.</span>statement<span class="token operator">-</span>timeout<span class="token operator">=</span><span class="token string">&quot;30s&quot;</span>
What to set as a statement timeout
</code></pre><p class="">Most applications will specify values for their connection pool, but the key ah-ha moment is that we have separate pools for any type of work we want to throttle or restrict, anticipating that it might – in an incident situation – consume too much database capacity and impact other components of the service.</p><p class="">Just some examples are:</p><ul><li><code>eventsDatabase</code> which is a pool of 2 connections used by a worker that consumes a copy of every Pub/Sub event and pushes it to BigQuery for later analysis. We don’t care about this queue falling behind but it would be very bad if it rinsed the database, especially if that happens – and it naturally would – at time when our service was most busy.</li><li><code>triggersDatabase</code> with 5 connections used by a cron job that scans all incidents for recent activity, helping drive nudges like “it’s been a while, would you like to send another incident update?”. These queries are expensive and nudges are best effort, so we’d rather fall behind than hurt the database trying to keep up.</li></ul><p class="">Using limits like this can help you protect a shared resource like database capacity from being overly consumed by any one part of your monolith. If you make them extremely easy to configure – as we have via a shared <code>database.ConnectOptions</code> helper – then it’s minimal effort to specify up-front “I expect to consume only up-to X of this resource, and beyond that I’d like to know”.</p><p class="">Useful for any moderately sized monolith, but even more powerful when multiple teams work in different parts of the codebase and protecting everyone from one another becomes a priority.</p><h2 id="keeping-a-monolithic-architecture-can-still-be-a-smart-choice-for-scaling" class=""><a class="heading-link" href="#keeping-a-monolithic-architecture-can-still-be-a-smart-choice-for-scaling"><span class="icon icon-link"></span></a>Keeping a monolithic architecture can still be a smart choice for scaling</h2><p class="">Obviously you hit issues when scaling a monolith, but here’s the secret: microservices aren’t all rainbows and butterflies, and distributed system problems can be <em>really</em> nasty.</p><p class="">So let’s not throw the baby out with the bathwater. When you hit monolith scaling issues, try asking yourself “what is really the issue here?”. Most of the time you can add guardrails or build limits into your code that emulate some of the benefits of microservices while keeping yourself single codebase and avoiding the RPC complexity.</p></div><div class="flex justify-between"><div class="flex gap-3"></div><div class="flex gap-6"><button title="Bluesky" class="relative"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 576 512" class="shrink-0 size-6 text-content-primary transition-colors hover:text-alarmalade-500"><path fill="currentColor" d="M407.8 294.7c-3.3-.4-6.7-.8-10-1.3 3.4.4 6.7.9 10 1.3M288 227.1c-26.1-50.7-97.1-145.2-163.1-191.8C61.6-9.4 37.5-1.7 21.6 5.5 3.3 13.8 0 41.9 0 58.4S9.1 194 15 213.9c19.5 65.7 89.1 87.9 153.2 80.7 3.3-.5 6.6-.9 10-1.4-3.3.5-6.6 1-10 1.4-93.9 14-177.3 48.2-67.9 169.9C220.6 589.1 265.1 437.8 288 361.1c22.9 76.7 49.2 222.5 185.6 103.4 102.4-103.4 28.1-156-65.8-169.9-3.3-.4-6.7-.8-10-1.3 3.4.4 6.7.9 10 1.3 64.1 7.1 133.6-15.1 153.2-80.7C566.9 194 576 75 576 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12.4-27.4-17-62.1-27.7-100-29.1v-.2c0-25.4 18.9-46.5 43.4-49.9 4.4 18.8 21.3 32.8 41.5 32.8zm-172.5 93.3c16.7 0 29.5 17.6 28.5 39.3s-13.5 29.6-30.3 29.6-31.4-8.8-30.4-30.5S160.3 247 177 247zm190.1 38.3c1 21.7-13.7 30.5-30.4 30.5s-29.3-7.9-30.3-29.6 11.8-39.3 28.5-39.3 31.2 16.6 32.1 38.3zm-48.1 56.7c-10.3 24.6-34.6 41.9-63 41.9s-52.7-17.3-63-41.9c-1.2-2.9.8-6.2 3.9-6.5 18.4-1.9 38.3-2.9 59.1-2.9s40.7 1 59.1 2.9c3.1.3 5.1 3.6 3.9 6.5"></path></svg></button></div></div><div class="p-8 bg-white border border-stroke-primary rounded-lg flex flex-col gap-4 flame-background lg:flex-row"><div class="flex-1 flex flex-col gap-4 justify-between flex-grow items-center lg:flex-row"><div class="flex gap-4 items-center"><span class="relative overflow-hidden block align-top w-25 h-25 rounded-full object-cover ring-1 ring-inset ring-black/10"><img alt="Picture of Lawrence Jones" loading="lazy" width="250" height="250" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe7b906adbcc6184c09d6abda07181ee946f50ab5-800x800.png%3Fw%3D250%26h%3D250%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe7b906adbcc6184c09d6abda07181ee946f50ab5-800x800.png%3Fw%3D250%26h%3D250%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=640&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe7b906adbcc6184c09d6abda07181ee946f50ab5-800x800.png%3Fw%3D250%26h%3D250%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=640&amp;q=75"/></span><div class="text-pretty"><div class="text-content-primary text-body-emphasis">Lawrence Jones</div><div class="text-alarmalade-600 text-body-xs">Product Engineer</div></div></div><a class="relative inline-flex gap-2 items-center justify-center rounded-full focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-offset-2 disabled:opacity-60 group/button cursor-pointer transition-[color,background-color,border-color,opacity,transform] border border-stroke-primary hover:border-stroke-hover text-content-primary dark:text-white text-body-emphasis h-[41px] px-4 py-2 max-sm:w-full" href="/blog/author/lawrence">View more<!-- --> <span class="hidden sm:inline">from <!-- -->Lawrence</span><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" fill="none" class="transition ease-in-out inline-block size-5 group-hover/button:translate-x-1"><path d="M12.8 8.59965H3.00002C2.66882 8.59965 2.40002 8.33085 2.40002 7.99965C2.40002 7.66845 2.66882 7.39965 3.00002 7.39965H12.8C13.1312 7.39965 13.4 7.66845 13.4 7.99965C13.4 8.33085 13.1312 8.59965 12.8 8.59965Z" fill="currentColor"></path><path d="M9.60002 11.9996C9.53122 11.9996 9.46082 11.9876 9.39202 11.9628C9.08082 11.8476 8.92242 11.5028 9.03682 11.1924C9.66242 9.49645 10.7328 8.53005 11.5816 8.00045C10.7328 7.47085 9.66322 6.50445 9.03682 4.80845C8.92162 4.49725 9.08082 4.15245 9.39202 4.03805C9.70322 3.92125 10.048 4.08285 10.1624 4.39325C11.0656 6.84205 13.0656 7.39805 13.1496 7.42045C13.4144 7.49085 13.5992 7.73085 13.5976 8.00365C13.596 8.27725 13.412 8.51565 13.1464 8.58285C13.0648 8.60445 11.0656 9.16045 10.1624 11.6092C10.0728 11.8516 9.84402 12.0012 9.59922 12.0012L9.60002 11.9996Z" fill="currentColor"></path></svg></a></div></div></div></section><section class="flex flex-col gap-6"><div class="flex flex-col md:flex-row justify-between gap-4"><h2 class="text-h3">See related articles</h2><a class="relative gap-2 items-center justify-center rounded-full focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-offset-2 disabled:opacity-60 group/button cursor-pointer transition-[color,background-color,border-color,opacity,transform] bg-surface-secondary hover:bg-surface-tertiary active:bg-surface-quaternary text-content-primary text-body-emphasis h-[41px] px-4 py-2 hidden md:block" href="/blog">View all<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" fill="none" class="transition ease-in-out inline-block size-5 group-hover/button:translate-x-1"><path d="M12.8 8.59965H3.00002C2.66882 8.59965 2.40002 8.33085 2.40002 7.99965C2.40002 7.66845 2.66882 7.39965 3.00002 7.39965H12.8C13.1312 7.39965 13.4 7.66845 13.4 7.99965C13.4 8.33085 13.1312 8.59965 12.8 8.59965Z" fill="currentColor"></path><path d="M9.60002 11.9996C9.53122 11.9996 9.46082 11.9876 9.39202 11.9628C9.08082 11.8476 8.92242 11.5028 9.03682 11.1924C9.66242 9.49645 10.7328 8.53005 11.5816 8.00045C10.7328 7.47085 9.66322 6.50445 9.03682 4.80845C8.92162 4.49725 9.08082 4.15245 9.39202 4.03805C9.70322 3.92125 10.048 4.08285 10.1624 4.39325C11.0656 6.84205 13.0656 7.39805 13.1496 7.42045C13.4144 7.49085 13.5992 7.73085 13.5976 8.00365C13.596 8.27725 13.412 8.51565 13.1464 8.58285C13.0648 8.60445 11.0656 9.16045 10.1624 11.6092C10.0728 11.8516 9.84402 12.0012 9.59922 12.0012L9.60002 11.9996Z" fill="currentColor"></path></svg></a></div><div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-8 md:gap-4"><a id="imported-blog-2023-03-29-giving-away-my-legos-index-md" class="group flex flex-col" href="/blog/giving-away-my-legos"><div class="bg-surface-tertiary rounded-lg mb-3 md:mb-6 p-0 relative aspect-video"><span class="block align-top w-full overflow-hidden transition-all ease-in-out duration-300 mx-auto absolute inset-0 group-hover:w-[calc(100%-16px)] group-hover:py-2 [&amp;_img]:transition-all [&amp;_img]:rounded-lg group-hover:[&amp;_img]:rounded"><img alt="What it meant for me to give away my Lego" loading="lazy" width="1920" height="1080" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe396795e7489a28277e6f72703f3a2477c9b0a25-1920x1080.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=1920&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe396795e7489a28277e6f72703f3a2477c9b0a25-1920x1080.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe396795e7489a28277e6f72703f3a2477c9b0a25-1920x1080.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75"/></span></div><div class="max-w-[546px] grow flex flex-col gap-2"><h3 class="text-h4 text-pretty">What it meant for me to give away my Lego</h3><p class="text-body-sm line-clamp-2">If you join an early-stage startup, you&#x27;ll probably have to give away your Lego one day. Here&#x27;s what I learned when I had to part with mine.</p><div class="flex flex-wrap items-center gap-x-4 gap-y-1"><div class="flex items-center gap-2 flex-wrap"><span class="flex items-center gap-2"><div class="size-[22px] rounded-full overflow-hidden shrink-0"><span class="relative overflow-hidden block align-top"><img alt="Lisa Karlin Curtis" loading="lazy" width="100" height="100" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Ffdd2d553f58284a7641cb96adad76b70c273d127-690x690.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=128&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Ffdd2d553f58284a7641cb96adad76b70c273d127-690x690.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Ffdd2d553f58284a7641cb96adad76b70c273d127-690x690.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75"/></span></div><span class="text-body-sm-emphasis leading-[1.1]">Lisa Karlin Curtis</span></span></div><div class="text-body-sm text-content-secondary">March 29, 2023</div></div></div></a><a id="imported-blog-2023-04-20-database-performance-index-md" class="group flex flex-col" href="/blog/database-performance"><div class="bg-surface-tertiary rounded-lg mb-3 md:mb-6 p-0 relative aspect-video"><span class="block align-top w-full overflow-hidden transition-all ease-in-out duration-300 mx-auto absolute inset-0 group-hover:w-[calc(100%-16px)] group-hover:py-2 [&amp;_img]:transition-all [&amp;_img]:rounded-lg group-hover:[&amp;_img]:rounded"><img alt="Battling database performance" loading="lazy" width="4911" height="2762" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fcebcb221cd7d674137e3d25f23d0c114eab2b94f-4911x2762.jpg%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75 1x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fcebcb221cd7d674137e3d25f23d0c114eab2b94f-4911x2762.jpg%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75"/></span></div><div class="max-w-[546px] grow flex flex-col gap-2"><h3 class="text-h4 text-pretty">Battling database performance</h3><p class="text-body-sm line-clamp-2">Earlier this year, we experienced intermittent timeouts in our application — here’s how we tried to address the underlying issue over the next two weeks.</p><div class="flex flex-wrap items-center gap-x-4 gap-y-1"><div class="flex items-center gap-2 flex-wrap"><span class="flex items-center gap-2"><div class="size-[22px] rounded-full overflow-hidden shrink-0"><span class="relative overflow-hidden block align-top"><img alt="Rory Bain" loading="lazy" width="100" height="100" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F03152b7eec852151f760e893d865963694542181-500x500.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=128&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F03152b7eec852151f760e893d865963694542181-500x500.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F03152b7eec852151f760e893d865963694542181-500x500.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75"/></span></div><span class="text-body-sm-emphasis leading-[1.1]">Rory Bain</span></span></div><div class="text-body-sm text-content-secondary">April 20, 2023</div></div></div></a><a id="imported-blog-2022-09-07-building-workflows-index-md" class="group flex flex-col" href="/blog/building-workflows-part-1"><div class="bg-surface-tertiary rounded-lg mb-3 md:mb-6 p-0 relative aspect-video"><span class="block align-top w-full overflow-hidden transition-all ease-in-out duration-300 mx-auto absolute inset-0 group-hover:w-[calc(100%-16px)] group-hover:py-2 [&amp;_img]:transition-all [&amp;_img]:rounded-lg group-hover:[&amp;_img]:rounded"><img alt="Building Workflows, Part 1 — Core concepts and the Workflow Builder" loading="lazy" width="3231" height="1741" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fa9c58ca473ebe5520548b999d857fa77db38ab09-3231x1741.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75 1x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fa9c58ca473ebe5520548b999d857fa77db38ab09-3231x1741.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75"/></span></div><div class="max-w-[546px] grow flex flex-col gap-2"><h3 class="text-h4 text-pretty">Building Workflows, Part 1 — Core concepts and the Workflow Builder</h3><p class="text-body-sm line-clamp-2">Part one of a deep-dive into building our workflow engine, covering core workflow concepts and how they are used to power the Workflow Builder.</p><div class="flex flex-wrap items-center gap-x-4 gap-y-1"><div class="flex items-center gap-2 flex-wrap"><span class="flex items-center gap-2"><div class="size-[22px] rounded-full overflow-hidden shrink-0"><span class="relative overflow-hidden block align-top"><img alt="Lawrence Jones" loading="lazy" width="100" height="100" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe7b906adbcc6184c09d6abda07181ee946f50ab5-800x800.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=128&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe7b906adbcc6184c09d6abda07181ee946f50ab5-800x800.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fe7b906adbcc6184c09d6abda07181ee946f50ab5-800x800.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75"/></span></div><span class="text-body-sm-emphasis leading-[1.1]">Lawrence Jones</span></span></div><div class="text-body-sm text-content-secondary">September 14, 2022</div></div></div></a></div><a class="relative inline-flex gap-2 items-center justify-center rounded-full focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-offset-2 disabled:opacity-60 group/button cursor-pointer transition-[color,background-color,border-color,opacity,transform] bg-surface-secondary hover:bg-surface-tertiary active:bg-surface-quaternary text-content-primary text-body-emphasis h-[41px] px-4 py-2 md:hidden" href="/blog">View all<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" fill="none" class="transition ease-in-out inline-block size-5 group-hover/button:translate-x-1"><path d="M12.8 8.59965H3.00002C2.66882 8.59965 2.40002 8.33085 2.40002 7.99965C2.40002 7.66845 2.66882 7.39965 3.00002 7.39965H12.8C13.1312 7.39965 13.4 7.66845 13.4 7.99965C13.4 8.33085 13.1312 8.59965 12.8 8.59965Z" fill="currentColor"></path><path d="M9.60002 11.9996C9.53122 11.9996 9.46082 11.9876 9.39202 11.9628C9.08082 11.8476 8.92242 11.5028 9.03682 11.1924C9.66242 9.49645 10.7328 8.53005 11.5816 8.00045C10.7328 7.47085 9.66322 6.50445 9.03682 4.80845C8.92162 4.49725 9.08082 4.15245 9.39202 4.03805C9.70322 3.92125 10.048 4.08285 10.1624 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Book a call with one of our experts today.</p></div><div class="flex gap-4 flex-col lg:flex-row lg:gap-4"><div class="basis-1/2"><img alt="Signup image" loading="lazy" width="1176" height="641" decoding="async" data-nimg="1" class="w-full h-full object-cover rounded-lg" style="color:transparent" srcSet="/_next/image?url=%2F_next%2Fstatic%2Fimmutable%2Fmedia%2Fsignup-image.1f5nktjcty_re.png&amp;w=1200&amp;q=75 1x, /_next/image?url=%2F_next%2Fstatic%2Fimmutable%2Fmedia%2Fsignup-image.1f5nktjcty_re.png&amp;w=3840&amp;q=75 2x" src="/_next/image?url=%2F_next%2Fstatic%2Fimmutable%2Fmedia%2Fsignup-image.1f5nktjcty_re.png&amp;w=3840&amp;q=75"/></div><div class="basis-1/2 flex flex-col gap-6 bg-surface-secondary rounded-lg p-6"><div class="grow"><h3 class="text-body-emphasis mb-2">We’d love to talk to you about</h3><ul class="flex flex-col gap-2 text-body-serif grow"><li class="flex gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="21" viewBox="0 0 20 21" fill="none" class="mt-0.5"><path d="M9.14598 14.4365C10.6142 11.6377 12.4682 9.39312 14.6552 7.7673C15.0469 7.47672 15.1281 6.92263 14.8375 6.53205C14.547 6.1403 13.994 6.0603 13.6035 6.34971C11.5753 7.85671 9.81654 9.83428 8.35895 12.2401C7.8025 11.3648 7.19429 10.5978 6.5202 9.92016C6.1755 9.57311 5.61552 9.57312 5.27201 9.91663C4.92614 10.2601 4.92496 10.8201 5.26848 11.1648C6.14727 12.0483 6.90371 13.1165 7.58016 14.4306C7.73191 14.7247 8.03896 14.9129 8.36483 14.9094C8.69306 14.9094 8.99422 14.727 9.14598 14.4365Z" fill="#F25533"></path></svg>All-in-one incident management</li><li class="flex gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="21" viewBox="0 0 20 21" fill="none" class="mt-0.5"><path d="M9.14598 14.4365C10.6142 11.6377 12.4682 9.39312 14.6552 7.7673C15.0469 7.47672 15.1281 6.92263 14.8375 6.53205C14.547 6.1403 13.994 6.0603 13.6035 6.34971C11.5753 7.85671 9.81654 9.83428 8.35895 12.2401C7.8025 11.3648 7.19429 10.5978 6.5202 9.92016C6.1755 9.57311 5.61552 9.57312 5.27201 9.91663C4.92614 10.2601 4.92496 10.8201 5.26848 11.1648C6.14727 12.0483 6.90371 13.1165 7.58016 14.4306C7.73191 14.7247 8.03896 14.9129 8.36483 14.9094C8.69306 14.9094 8.99422 14.727 9.14598 14.4365Z" fill="#F25533"></path></svg>Our unmatched speed of deployment</li><li class="flex gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="21" viewBox="0 0 20 21" fill="none" class="mt-0.5"><path d="M9.14598 14.4365C10.6142 11.6377 12.4682 9.39312 14.6552 7.7673C15.0469 7.47672 15.1281 6.92263 14.8375 6.53205C14.547 6.1403 13.994 6.0603 13.6035 6.34971C11.5753 7.85671 9.81654 9.83428 8.35895 12.2401C7.8025 11.3648 7.19429 10.5978 6.5202 9.92016C6.1755 9.57311 5.61552 9.57312 5.27201 9.91663C4.92614 10.2601 4.92496 10.8201 5.26848 11.1648C6.14727 12.0483 6.90371 13.1165 7.58016 14.4306C7.73191 14.7247 8.03896 14.9129 8.36483 14.9094C8.69306 14.9094 8.99422 14.727 9.14598 14.4365Z" fill="#F25533"></path></svg>Why we’re loved by users and easily adopted</li><li class="flex 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Writing code is hard enough without each function call requiring a network request, and that’s before considering the investment in observability, RPC frameworks, and dev environments you need to be productive in a microservice environment.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"762895e1ef62\",\"_type\":\"block\",\"children\":[{\"_key\":\"762895e1ef620\",\"_type\":\"span\",\"marks\":[],\"text\":\"But having spent half a decade stewarding a Ruby monolith from 20 to 200 engineers and watched its modest 10GB Postgres database grow beyond 5TB, there’s a point where the pain outweighs the benefits.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"afbe788015f1\",\"_type\":\"block\",\"children\":[{\"_key\":\"afbe788015f10\",\"_type\":\"span\",\"marks\":[],\"text\":\"This post is about splitting your workloads, a technique that can significantly reduce that pain, costs little and can be applied early as you scale. Something that, if executed well, can let you enjoy that sweet monolithic goodness for that much longer.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"edb82e90b0fe\",\"_type\":\"block\",\"children\":[{\"_key\":\"edb82e90b0fe0\",\"_type\":\"span\",\"marks\":[],\"text\":\"Let’s dive in!\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"4299101df085\",\"_type\":\"block\",\"children\":[{\"_key\":\"4299101df0850\",\"_type\":\"span\",\"marks\":[],\"text\":\"A wild outage appears!\"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-a-wild-outage-appears\",\"slug\":\"a-wild-outage-appears\"}],\"style\":\"h2\"},{\"_key\":\"6546c83b6af9\",\"_type\":\"block\",\"children\":[{\"_key\":\"6546c83b6af90\",\"_type\":\"span\",\"marks\":[],\"text\":\"Back in November 2022, we had an outage we affectionately called \"},{\"_key\":\"6546c83b6af91\",\"_type\":\"span\",\"marks\":[\"47e50197230e\"],\"text\":\"“Intermittent downtime from repeated crashes”\"},{\"_key\":\"6546c83b6af92\",\"_type\":\"span\",\"marks\":[],\"text\":\".\"}],\"markDefs\":[{\"_key\":\"47e50197230e\",\"_type\":\"link\",\"href\":\"https://incident.io/blog/intermittent-downtime\",\"openInNewWindow\":true}],\"style\":\"normal\"},{\"_key\":\"9764b6967a63\",\"_type\":\"block\",\"children\":[{\"_key\":\"9764b6967a630\",\"_type\":\"span\",\"marks\":[],\"text\":\"Probably the first genuinely major outage we’ve faced, it resulted in our app repeatedly crashing over a period of 32 minutes. Pretty stressful stuff, even for responders who spend their entire day jobs building incident tooling.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"4b8d85fdbfa3\",\"_type\":\"block\",\"children\":[{\"_key\":\"4b8d85fdbfa30\",\"_type\":\"span\",\"marks\":[],\"text\":\"While the post-mortem goes into detail, the gist of the issue was:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"459170f30ebf\",\"_type\":\"block\",\"children\":[{\"_key\":\"459170f30ebf0\",\"_type\":\"span\",\"marks\":[],\"text\":\"We run our app as a Go monolith in Heroku, using Heroku Postgres as a database, and GCP Pub/Sub as an async message queue.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"f6d7dafd1f09\",\"_type\":\"block\",\"children\":[{\"_key\":\"f6d7dafd1f090\",\"_type\":\"span\",\"marks\":[],\"text\":\"Our application runs several replicas of a single binary running web, worker, and cron threads.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"a695168e6fcc\",\"_type\":\"block\",\"children\":[{\"_key\":\"a695168e6fcc0\",\"_type\":\"span\",\"marks\":[],\"text\":\"When a bad Pub/Sub message was pulled into the binary, an unhandled panic would crash the entire app, meaning web, workers, and crons all died.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"5fd7893e8350\",\"_type\":\"block\",\"children\":[{\"_key\":\"5fd7893e83500\",\"_type\":\"span\",\"marks\":[],\"text\":\"Well, that sucks and seems easily avoidable. 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This prevents a bad code path from consuming all of a limited resource and impacting other code, as it might in a monolithic app.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"686e1554649c\",\"_type\":\"block\",\"children\":[{\"_key\":\"686e1554649c0\",\"_type\":\"span\",\"marks\":[],\"text\":\"Microservices certainly solve these problems but come with a huge amount of associated baggage (distributed system problems, RPC frameworks, etc). If we want the benefits of microservices without the baggage, we’ll need some alternative solutions.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"5b756e9ff130\",\"_type\":\"block\",\"children\":[{\"_key\":\"5b756e9ff1300\",\"_type\":\"span\",\"marks\":[],\"text\":\"Rule 1: Never mix workloads \"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-rule-1-never-mix-workloads-\",\"slug\":\"rule-1-never-mix-workloads-\"}],\"style\":\"h2\"},{\"_key\":\"250a558b4bcd\",\"_type\":\"block\",\"children\":[{\"_key\":\"250a558b4bcd0\",\"_type\":\"span\",\"marks\":[],\"text\":\"First, we should apply the cardinal rule of running monoliths, which is: never mix your workloads.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"d9d782381784\",\"_type\":\"block\",\"children\":[{\"_key\":\"d9d7823817840\",\"_type\":\"span\",\"marks\":[],\"text\":\"For our incident.io app, we have three key workloads:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"128868651998\",\"_type\":\"block\",\"children\":[{\"_key\":\"1288686519980\",\"_type\":\"span\",\"marks\":[],\"text\":\"Web servers that handle incoming requests.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"5d0448052ab4\",\"_type\":\"block\",\"children\":[{\"_key\":\"5d0448052ab40\",\"_type\":\"span\",\"marks\":[],\"text\":\"Pub/Sub subscribers that process async work.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"81163fcdf660\",\"_type\":\"block\",\"children\":[{\"_key\":\"81163fcdf6600\",\"_type\":\"span\",\"marks\":[],\"text\":\"Cron jobs that fire on a schedule.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"91ed97fe868f\",\"_type\":\"block\",\"children\":[{\"_key\":\"91ed97fe868f0\",\"_type\":\"span\",\"marks\":[],\"text\":\"We were breaking this rule by running all of this code inside of the same process (as in, literally the same linux process). By mixing workloads we left ourselves open to:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"3519cab25e51\",\"_type\":\"block\",\"children\":[{\"_key\":\"3519cab25e510\",\"_type\":\"span\",\"marks\":[],\"text\":\"Bad code in a specific part of the codebase bringing down the whole app, as in our November incident.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"0918fef40609\",\"_type\":\"block\",\"children\":[{\"_key\":\"0918fef406090\",\"_type\":\"span\",\"marks\":[],\"text\":\"If we deployed a Pub/Sub subscriber that was CPU heavy (maybe compressing Slack images, or a badly written loop that spun indefinitely) we’d impact the entire app, causing all web/worker/cron activity to slow to a halt. CPU in that process is a limited resource and by consuming 90% of it, we’d leave only 10% left for the other work.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"e78c4aef9b32\",\"_type\":\"block\",\"children\":[{\"_key\":\"e78c4aef9b320\",\"_type\":\"span\",\"marks\":[],\"text\":\"The same day as our incident occurred, we split our app into separate tiers of deployment for each workload type. This meant creating three separate dyno tiers in Heroku, which for those unfamiliar with Heroku just means three independent deployments of the app processing only its own type of workload.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"06a10782d322\",\"_type\":\"block\",\"children\":[{\"_key\":\"06a10782d3220\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"ac2968c5fbbb\",\"_type\":\"image\",\"asset\":{\"_ref\":\"image-655ac9e2d799c4b7d71bfa9f3edbd812961b03e8-1726x566-png\",\"_type\":\"reference\"},\"description\":\"Diagram showing separate deployment tiers for web servers, Pub/Sub subscribers, and cron jobs in a monolithic app using Heroku.\",\"markDefs\":null},{\"_key\":\"0e5f21ea1f8b\",\"_type\":\"block\",\"children\":[{\"_key\":\"0e5f21ea1f8b0\",\"_type\":\"span\",\"marks\":[],\"text\":\"You might ask if we’re doing this, then why not go the whole way and have separate microservices?\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"dbe81dfb9c1f\",\"_type\":\"block\",\"children\":[{\"_key\":\"dbe81dfb9c1f0\",\"_type\":\"span\",\"marks\":[],\"text\":\"The answer is that this split preserves all the benefits of the monolith while solving the problems we presented above. Every deployment is running the same code, using the same Docker image and environment variables, the only thing that differs is the command we run to start the code. No complex dev setup required, or RPC framework needed, it’s the same old monolith, just operated differently.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"7974d0100777\",\"_type\":\"block\",\"children\":[{\"_key\":\"7974d01007770\",\"_type\":\"span\",\"marks\":[],\"text\":\"Our application entry point code looks a bit like this:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"15d154d7f38b\",\"_type\":\"code\",\"code\":\"package main\\n\\nvar (\\n app = kingpin.New(\\\"app\\\", \\\"incident.io\\\")\\n web = app.Flag(\\\"web\\\", \\\"Run web server\\\").Bool()\\n workers = app.Flag(\\\"workers\\\", \\\"Run async workers\\\").Bool()\\n cron = app.Flag(\\\"cron\\\", \\\"Run cron jobs\\\").Bool()\\n)\\n\\nfunc main() {\\n\\tif *web {\\n // run web\\n }\\n\\tif *workers {\\n // run workers\\n }\\n\\tif *cron {\\n // run cron\\n }\\n\\n\\twait()\\n}\\n\",\"language\":\"go\",\"markDefs\":null},{\"_key\":\"1937e6cafa40\",\"_type\":\"block\",\"children\":[{\"_key\":\"1937e6cafa400\",\"_type\":\"span\",\"marks\":[],\"text\":\"You can easily add this to any application, with the neat benefit that for your local development environment, you can have all components running in a single hot-reloaded process (a pipe dream for many microservice shops!).\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"f83b1180736f\",\"_type\":\"block\",\"children\":[{\"_key\":\"f83b1180736f0\",\"_type\":\"span\",\"marks\":[],\"text\":\"As a small catch to switching over blindly, be aware that code assuming everything runs within the same process is both hard to recognize, subtly buggy, and difficult to fix. If, for example, your web server code stashes data in a process-local cache that the worker attempts to use, you’re going to have a sad time.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"51978d52a319\",\"_type\":\"block\",\"children\":[{\"_key\":\"51978d52a3190\",\"_type\":\"span\",\"marks\":[],\"text\":\"The good news is those dependencies are generally code smells are easily solved by pushing coordination into an external store such as Postgres or Redis, and won’t reappear after you’ve made the initial change. Worth doing even if you aren’t splitting your code, in my opinion.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"4e8eae991280\",\"_type\":\"block\",\"children\":[{\"_key\":\"4e8eae9912800\",\"_type\":\"span\",\"marks\":[],\"text\":\"Note there’s no limit to how granular you split these workloads. I’ve seen a deployment per queue or even job class before, going up to ~20 deployments for a single application environment.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"c64c6847cfa4\",\"_type\":\"block\",\"children\":[{\"_key\":\"c64c6847cfa40\",\"_type\":\"span\",\"marks\":[],\"text\":\"Rule 2: Apply guardrails to your monolith for database efficiency\"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-rule-2-apply-guardrails-to-your-monolith-for-database-efficiency\",\"slug\":\"rule-2-apply-guardrails-to-your-monolith-for-database-efficiency\"}],\"style\":\"h2\"},{\"_key\":\"d6405ba3e4dc\",\"_type\":\"block\",\"children\":[{\"_key\":\"d6405ba3e4dc0\",\"_type\":\"span\",\"marks\":[],\"text\":\"Ok, so our monolith is no longer a big bundle of code running all the things: it’s three separate, isolated deployments that can succeed or fail independently. Great.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"6f404700180d\",\"_type\":\"block\",\"children\":[{\"_key\":\"6f404700180d0\",\"_type\":\"span\",\"marks\":[],\"text\":\"Most people’s applications aren’t just about the code running in the process, though. One of the most significant reliability risks is rogue or even well-behaved but unfortunately timed code consuming the most precious of a monoliths limited resources, which is usually…\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"7bdcdec5acae\",\"_type\":\"block\",\"children\":[{\"_key\":\"7bdcdec5acae0\",\"_type\":\"span\",\"marks\":[],\"text\":\"Database capacity. In our case, Postgres.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"1bc7104d59ba\",\"_type\":\"block\",\"children\":[{\"_key\":\"1bc7104d59ba0\",\"_type\":\"span\",\"marks\":[],\"text\":\"Even having split your workloads, you’ll always have the underlying data store that needs some form of protection. And this is where microservices – which often try to share nothing – can help, with each service deployment only able to indirectly consume database time via another services API.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"26fd717bfca6\",\"_type\":\"block\",\"children\":[{\"_key\":\"26fd717bfca60\",\"_type\":\"span\",\"marks\":[],\"text\":\"This is solvable in our monolith though, we just need to \"},{\"_key\":\"26fd717bfca61\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"create guardrails and limits around resource consumption\"},{\"_key\":\"26fd717bfca62\",\"_type\":\"span\",\"marks\":[],\"text\":\". Limits that can be arbitrarily granular.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"b1ccefb2dd7c\",\"_type\":\"block\",\"children\":[{\"_key\":\"b1ccefb2dd7c0\",\"_type\":\"span\",\"marks\":[],\"text\":\"In our code, the guardrails around our Postgres database look like this:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"fb219e6d0b2c\",\"_type\":\"code\",\"code\":\"package main\\n\\nvar (\\n // ...\\n workers = app.Flag(\\\"workers\\\", \\\"Run async workers\\\").Bool()\\n workersDatabase = new(database.ConnectOptions).Bind(\\n\\t\\tapp, \\\"workers.database.\\\", 20, 5, \\\"30s\\\")\\n)\\n\\nfunc main() {\\n // ...\\n if *workers {\\n db, err := createDatabasePool(ctx, \\\"worker\\\", workersDatabase)\\n\\t\\tif err != nil {\\n\\t\\t\\treturn errors.Wrap(err, \\\"connecting to Postgres pool for workers\\\")\\n\\t\\t}\\n\\n runWorkers(db) // start running workers\\n }\\n}\\n\",\"language\":\"go\",\"markDefs\":null},{\"_key\":\"48547038a0b1\",\"_type\":\"block\",\"children\":[{\"_key\":\"48547038a0b10\",\"_type\":\"span\",\"marks\":[],\"text\":\"This code sets and allows customization of the database pool used specifically for workers. 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We don’t care about this queue falling behind but it would be very bad if it rinsed the database, especially if that happens – and it naturally would – at time when our service was most busy.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"c8a7ec6adef2\",\"_type\":\"block\",\"children\":[{\"_key\":\"c8a7ec6adef20\",\"_type\":\"span\",\"marks\":[\"code\"],\"text\":\"triggersDatabase\"},{\"_key\":\"c8a7ec6adef21\",\"_type\":\"span\",\"marks\":[],\"text\":\" with 5 connections used by a cron job that scans all incidents for recent activity, helping drive nudges like “it’s been a while, would you like to send another incident update?”. 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If you make them extremely easy to configure – as we have via a shared \"},{\"_key\":\"76a4875a5d3a1\",\"_type\":\"span\",\"marks\":[\"code\"],\"text\":\"database.ConnectOptions\"},{\"_key\":\"76a4875a5d3a2\",\"_type\":\"span\",\"marks\":[],\"text\":\" helper – then it’s minimal effort to specify up-front “I expect to consume only up-to X of this resource, and beyond that I’d like to know”.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"6fa6f9f45d62\",\"_type\":\"block\",\"children\":[{\"_key\":\"6fa6f9f45d620\",\"_type\":\"span\",\"marks\":[],\"text\":\"Useful for any moderately sized monolith, but even more powerful when multiple teams work in different parts of the codebase and protecting everyone from one another becomes a priority.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"95de2f5f0089\",\"_type\":\"block\",\"children\":[{\"_key\":\"0d51c1c908140\",\"_type\":\"span\",\"marks\":[],\"text\":\"Keeping a monolithic architecture can still be a smart choice for scaling\"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-keeping-a-monolithic-architecture-can-still-be-a-smart-choice-for-scaling\",\"slug\":\"keeping-a-monolithic-architecture-can-still-be-a-smart-choice-for-scaling\"}],\"style\":\"h2\"},{\"_key\":\"f12280a2e5e4\",\"_type\":\"block\",\"children\":[{\"_key\":\"f12280a2e5e40\",\"_type\":\"span\",\"marks\":[],\"text\":\"Obviously you hit issues when scaling a monolith, but here’s the secret: microservices aren’t all rainbows and butterflies, and distributed system problems can be \"},{\"_key\":\"f12280a2e5e41\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"really\"},{\"_key\":\"f12280a2e5e42\",\"_type\":\"span\",\"marks\":[],\"text\":\" nasty.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"34c5ab5503ed\",\"_type\":\"block\",\"children\":[{\"_key\":\"34c5ab5503ed0\",\"_type\":\"span\",\"marks\":[],\"text\":\"So let’s not throw the baby out with the bathwater. 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