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styled__ImageWrapperStyled-sc-2c2295e1-1 eSvYQq hKhSsm"><img loading="eager" src="https://d21hwc2yj2s6ok.cloudfront.net/shrine_store/uploads/networks/3057/communication_news/11502437/ultra_wide-6fb6987a445cb2c3a3c25a45b24ee9f0.webp" alt="" decoding="async" fetchPriority="high" class="ui__StyledImg-sc-9b9ac9c0-0 llRGgU styled__ImageStyled-sc-2c2295e1-2 kAqQFG"/></div><div data-testid="news-content" class="Box-sc-3e41dc6a-0 styled__WrapperContentStyled-sc-2c2295e1-0 ercVhJ eOJpUd"><div class="Box-sc-3e41dc6a-0 styled__HeaderStyled-sc-2c2295e1-3 fScRFm bsTAPu"><div class="Box-sc-3e41dc6a-0 fzdQzq"><div class="Box-sc-3e41dc6a-0 cNWsPK"><div class="Box-sc-3e41dc6a-0 bRccPD"><h1 class="Box-sc-3e41dc6a-0 biNsvt">Superficial Blamelessness</h1><div class="Box-sc-3e41dc6a-0 ldkrga"></div></div><div class="Box-sc-3e41dc6a-0 jYXfit">Published on April 15, 2026</div><div style="height:48px"></div></div></div><div class="Box-sc-3e41dc6a-0 bWsukS"><div class="Box-sc-3e41dc6a-0 cXOiip"></div></div></div><div class="Box-sc-3e41dc6a-0 PublicationText__Wrapper-sc-272ab012-0 bSDPrX dSKAKJ"><div class="HtmlContentWrapperWithStyle-sc-d185182e-0 ckSTdk"><p dir="ltr">In 2012, John Allspaw (then CTO of Etsy) wrote a <a href="https://www.etsy.com/codeascraft/blameless-postmortems" rel="nofollow noreferrer noopener">seminal blog post</a> on the need for what he called Blameless Postmortems. Built off the notion of a “Just Culture” from the research of <a href="https://www.amazon.com/Just-Culture-Sidney-Dekker/dp/147247578X" rel="nofollow noreferrer noopener">Sidney Dekker</a>, he summarized Etsy’s approach to balancing accountability in post-incident reviews with a need for avoiding blaming individuals who were involved in the incident:&nbsp;</p>
<blockquote>
<p dir="ltr">“Having a "Just Culture" means that you’re making [an] effort to balance safety and accountability. It means that by investigating mistakes in a way that focuses on the situational aspects of a failure’s mechanism and the decision-making process of individuals proximate to the failure, an organization can come out safer than it would normally be if it had simply punished the actors involved as a remediation.”</p>
</blockquote>
<p dir="ltr">He goes on to explain how engineers involved in incidents can be encouraged to give detailed accounts of what happened without fear of punishment or retribution. The word blamelessness took on a life of its own and became slightly disconnected from Dekker’s research and John’s blog post. Further refinements such as <a href="https://dev.to/reinh/beyond-blameless-3oif" rel="nofollow noreferrer noopener">blame-awareness</a> came in to add some nuance to the ongoing discourse as well.</p>
<p dir="ltr">For many organizations, some form of <em>blamelessness</em> has become a more standard practice and <em>blame-awareness </em>has been gaining in popularity. However, there is an anti-pattern I have noticed as well, which I like to call superficial (or shallow) blamelessness that I think is important for people to be on the lookout for.</p>
<h1 dir="ltr">Why Try to Be Blameless?</h1>
<p dir="ltr">Resilience Engineering, and many of the connected disciplines it borrows from, aims to leverage incidents and the energy put behind them to better understand how a system works. The idea goes, the better you understand the dynamics in play, the less likely you are to make misguided suggestions, to operate on false assumptions, and to create accidental harm (among many other things).</p>
<p dir="ltr">Disciplines that look at complex systems prefer to focus on <em>interactions between components</em> rather than specific parts themselves (what many consider to be the “root cause”): individual units can be working fine—reliably and in accordance with their goals—but still end up behaving surprisingly <em>as an ensemble.</em></p>
<p dir="ltr">Looking at the parts in isolation may work well enough when your systems are simple: find what broke, replace or fix or tweak it, and move on. But as they scale up and become more connected to other systems, they also necessarily become more complex. As a result, the way we construct explanations about those systems has to change as well. Looking at so-called “faulty” individual components or people that need to be corrected provides diminishing returns and loses its effectiveness.</p>
<p dir="ltr">Eventually, this is why blame hurts. Blame fundamentally implies that someone or something misbehaved, that they are <em>responsible</em> for causing the outcomes. Blame, as a concept, invites retribution. And retribution in turn drives people involved in adverse events to protect themselves, which means it becomes harder to learn from what happened.</p>
<p dir="ltr">So not only do we get a focus that is centred on individual units, we make it harder to ever get a better understanding on top of it. This is where concepts such as blamelessness (or <a href="https://dev.to/reinh/beyond-blameless-3oif" rel="nofollow noreferrer noopener">blame-awareness</a>) come from: we realize that blame is an expected reaction to surprising negative events, but also know that post-incident responses that lean into these feelings do not tend to be effective in the long run.</p>
<p dir="ltr">But being blameless isn’t purely a concept for justice to ensure we don’t punish people for being put in a tough situation by a system that doesn’t even realize it—although it certainly can help—it is also a concept that invites a stance that is systems-oriented.</p>
<p dir="ltr">You don’t just <em>avoid</em> blame. It’s a natural feeling to feel blame, but you have to go past it and shift your perspective towards the system “owning” the situation.</p>
<h1 dir="ltr">What Makes Blame Superficial</h1>
<p dir="ltr">Superficial blamelessness will be easiest to spot when retribution is still the norm, whether officially or only informally. People will avoid naming employees or even teams, and internal reports will look as non-specific as if they were intended for an external audience. But even if you take away the “name” bit from the cycle of <em>name</em> → <em>blame</em> → <em>shame</em>, the cycle lives on.</p>
<p dir="ltr">Organizations where blame is less “ambient” or better harnessed will instead consider it safe to name names, and will invite a conversation with the people involved to get their perspective—one they do not have as a bystander—to get a richer view of how the system works. But even in these places, where it might be safe to give your account of what happened, there’s not yet any guarantee that you’re getting what you should out of it all. Blame is only one of many blockers on the way to a better systems perspective.</p>
<p dir="ltr">Be wary of successfully avoiding retribution, yet finding your post-incident process still biased towards an individualistic stance instead of a systemic one. Consider, for example, whether suggestions of what to improve after adverse events mostly focus on what specific people involved need to do better, even without punishment. Common ones are:</p>
<ul>
<li dir="ltr">
<p dir="ltr">Provide more training</p>
</li>
<li dir="ltr">
<p dir="ltr">Adjust a worker’s behavior</p>
</li>
<li dir="ltr">
<p dir="ltr">Write a specific patch or test</p>
</li>
<li dir="ltr">
<p dir="ltr">Be reminded to “pay more attention”</p>
</li>
<li dir="ltr">
<p dir="ltr">Add more reviewers or supervision to catch mistakes</p>
</li>
<li dir="ltr">
<p dir="ltr">Tweak the process or procedures <em>directly</em> related to the incident</p>
</li>
</ul>
<p dir="ltr">The locus of intervention, in these cases, is oriented towards specific people or components. Some of these might be useful and helpful, but if they’re most of what you get, you can suspect a systemic point of view isn’t strongly developed yet.</p>
<p dir="ltr">More systemic interventions are those that would change the conditions that lead to challenging situations. You could, for example, change or clarify broad pressures and goal conflicts. Likewise, the behavior you didn’t like in the context leading up to an incident might be valued in “normal” circumstances. Software development, after all, can have contributing factors that come from other departments too.</p>
<p dir="ltr">You might also find items such as tweaking processes or procedures that go beyond the circumstances of the incident. Maybe someone found out that relevant and useful information came up in informal discussion groups: those could perhaps be encouraged more, or the recipe expanded to other areas important to the organization, because they can help foster a culture that can deal with surprises better. If you find other teams have solutions that exist already, it’s worth asking if they could be borrowed and propagated, but also what could make it easier to figure out if there are ideas worth borrowing. And why not go further and find out under what circumstances that other team figured it out to see if there’s something to learn?</p>
<h1 dir="ltr">Control-centric vs. Empowerment-centric Approaches</h1>
<p dir="ltr">The distinction between systemic and individualistic is usually a good marker, mostly observable once you are looking at a completed review process and its list of actions. It might not be visible yet, because the process isn’t over or continuous, and it might also not be simple: people do what they can given the circumstances.</p>
<p dir="ltr">Another angle in which you can frame this comparison between individualistic and systemic elements is going to be based on an opposition between control and empowerment. If you are approaching the problem from a stance where you need to restrict and control what people do to keep it within specific parameters because they are not operating as you expect them to, then you are taking a control-centric approach. Ask yourself whether this isn’t a subtle way to be blaming people for the problems they’ve been asked to solve.</p>
<p dir="ltr">An empowerment-centric approach would instead ask how you can make the work simpler,&nbsp; safer, easier, clearer, or more manageable. Involve the people impacted in the process, not because they need to do better, but because the system needs to make sure they’re operating in better conditions.</p>
<p>&nbsp; <img src="https://d21hwc2yj2s6ok.cloudfront.net/shrine_store/uploads/networks/3057/communication_news/11502437/compressed-26c34733bbc8569171fb7a678ca2af66.webp" alt="" width="130" height="130"></p>
<p><strong>Fred Hebert</strong></p>
<p>Staff SRE</p></div></div></div></div></div></div></div></div><div class="Box-sc-3e41dc6a-0 nSVk"><div class="Grid__GridStyled-sc-c7f19ef3-0 CbzOM"><div class="Box-sc-3e41dc6a-0 Row__RowStyled-sc-a5c2e20d-0 jSILAH ylcnO"><div tabindex="-1" class="Col__ColStyled-sc-df0bb68b-0 dagzBg"><div class="Box-sc-3e41dc6a-0 Col__ColInnerStyled-sc-df0bb68b-1 kxQFCu jHhhMk"><div class="Box-sc-3e41dc6a-0 goizoB">Other news</div></div></div></div><div class="Box-sc-3e41dc6a-0 Row__RowStyled-sc-a5c2e20d-0 jNYxIR hEDgQU"><div tabindex="-1" class="Col__ColStyled-sc-df0bb68b-0 dagzBg"><div class="Box-sc-3e41dc6a-0 Col__ColInnerStyled-sc-df0bb68b-1 kxQFCu jHhhMk"><a data-testid="default-link-element" href="/news/11475336"><div tabindex="0" class="Box-sc-3e41dc6a-0 Card-sc-2ed53ea2-0 styled__RelatedCardStyled-sc-2c2295e1-11 dQNeud jgrSBy jkJbIz"><div data-testid="news-cover-wrapper" class="Box-sc-3e41dc6a-0 styled__RelatedImgWrapper-sc-2c2295e1-7 hZbbrS cycDCt"><div class="Box-sc-3e41dc6a-0 styled__RelatedImgStyled-sc-2c2295e1-6 ehDvKl gEygVG"></div></div><div class="Box-sc-3e41dc6a-0 styled__RelatedContentWrapper-sc-2c2295e1-4 hrksWC jCJtHJ"><div class="Box-sc-3e41dc6a-0 styled__RelatedAnimatedContentBox-sc-2c2295e1-5 bZeHqR jbrAqA"><div data-testid="link-to-news" class="Box-sc-3e41dc6a-0 eSvYQq"><h3 class="Box-sc-3e41dc6a-0 styled__RelatedLinkStyled-sc-2c2295e1-8 hVyqKD bdXqxJ"><div class="ClampedLinkWorkaround-sc-7be7fc1a-0 jYtrQc">Saturation</div></h3></div><div class="Box-sc-3e41dc6a-0 styled__RelatedDateStyled-sc-2c2295e1-9 jwSNmt">March 2, 2026</div><div class="Box-sc-3e41dc6a-0 styled__RelatedDescription-sc-2c2295e1-10 eSvYQq hfHojJ"><div>SaturationEvery system has its limits. If you keep throwing more and more at a system, at some point it will no longer be able to function properly. The term saturation refers to the state of a system where the demands on the system are high enough that the system is at the limits of its normal performance. Electrical engineering provides a helpful visualization of saturation. Imagine you want to </div></div></div></div></div></a></div></div><div tabindex="-1" class="Col__ColStyled-sc-df0bb68b-0 ckeRsZ"><div class="Box-sc-3e41dc6a-0 Col__ColInnerStyled-sc-df0bb68b-1 kxQFCu jHhhMk"><a data-testid="default-link-element" href="/news/11512183"><div tabindex="0" class="Box-sc-3e41dc6a-0 Card-sc-2ed53ea2-0 styled__RelatedCardStyled-sc-2c2295e1-11 dQNeud jgrSBy jkJbIz"><div data-testid="news-cover-wrapper" class="Box-sc-3e41dc6a-0 styled__RelatedImgWrapper-sc-2c2295e1-7 hZbbrS cycDCt"><div class="Box-sc-3e41dc6a-0 styled__RelatedImgStyled-sc-2c2295e1-6 ehDvKl DaZVh"></div></div><div class="Box-sc-3e41dc6a-0 styled__RelatedContentWrapper-sc-2c2295e1-4 hrksWC jCJtHJ"><div class="Box-sc-3e41dc6a-0 styled__RelatedAnimatedContentBox-sc-2c2295e1-5 bZeHqR jbrAqA"><div data-testid="link-to-news" class="Box-sc-3e41dc6a-0 eSvYQq"><h3 class="Box-sc-3e41dc6a-0 styled__RelatedLinkStyled-sc-2c2295e1-8 hVyqKD bdXqxJ"><div class="ClampedLinkWorkaround-sc-7be7fc1a-0 jYtrQc">“Human Error” Is an Illusion: A Response to Om Malik</div></h3></div><div class="Box-sc-3e41dc6a-0 styled__RelatedDateStyled-sc-2c2295e1-9 jwSNmt">April 27, 2026</div><div class="Box-sc-3e41dc6a-0 styled__RelatedDescription-sc-2c2295e1-10 eSvYQq hfHojJ"><div>Dear Om,I want to begin by stating that I have an immense amount of respect for you—I followed your work at GigaOm while I was a rising editor and conference chair at O&#x27;Reilly Media in the 2010s. I subscribe to your newsletter and appreciate your well-earned, often biting, takes on the current state of our industry. That said, I was sadly disappointed in your recent article &quot;Human Error is OK! 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dir=\"ltr\"\u003eIn 2012, John Allspaw (then CTO of Etsy) wrote a \u003ca href=\"https://www.etsy.com/codeascraft/blameless-postmortems\" rel=\"nofollow noreferrer noopener\"\u003eseminal blog post\u003c/a\u003e on the need for what he called Blameless Postmortems. Built off the notion of a “Just Culture” from the research of \u003ca href=\"https://www.amazon.com/Just-Culture-Sidney-Dekker/dp/147247578X\" rel=\"nofollow noreferrer noopener\"\u003eSidney Dekker\u003c/a\u003e, he summarized Etsy’s approach to balancing accountability in post-incident reviews with a need for avoiding blaming individuals who were involved in the incident:\u0026nbsp;\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003e“Having a \"Just Culture\" means that you’re making [an] effort to balance safety and accountability. It means that by investigating mistakes in a way that focuses on the situational aspects of a failure’s mechanism and the decision-making process of individuals proximate to the failure, an organization can come out safer than it would normally be if it had simply punished the actors involved as a remediation.”\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cp dir=\"ltr\"\u003eHe goes on to explain how engineers involved in incidents can be encouraged to give detailed accounts of what happened without fear of punishment or retribution. The word blamelessness took on a life of its own and became slightly disconnected from Dekker’s research and John’s blog post. Further refinements such as \u003ca href=\"https://dev.to/reinh/beyond-blameless-3oif\" rel=\"nofollow noreferrer noopener\"\u003eblame-awareness\u003c/a\u003e came in to add some nuance to the ongoing discourse as well.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eFor many organizations, some form of \u003cem\u003eblamelessness\u003c/em\u003e has become a more standard practice and \u003cem\u003eblame-awareness \u003c/em\u003ehas been gaining in popularity. However, there is an anti-pattern I have noticed as well, which I like to call superficial (or shallow) blamelessness that I think is important for people to be on the lookout for.\u003c/p\u003e\n\u003ch1 dir=\"ltr\"\u003eWhy Try to Be Blameless?\u003c/h1\u003e\n\u003cp dir=\"ltr\"\u003eResilience Engineering, and many of the connected disciplines it borrows from, aims to leverage incidents and the energy put behind them to better understand how a system works. The idea goes, the better you understand the dynamics in play, the less likely you are to make misguided suggestions, to operate on false assumptions, and to create accidental harm (among many other things).\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eDisciplines that look at complex systems prefer to focus on \u003cem\u003einteractions between components\u003c/em\u003e rather than specific parts themselves (what many consider to be the “root cause”): individual units can be working fine—reliably and in accordance with their goals—but still end up behaving surprisingly \u003cem\u003eas an ensemble.\u003c/em\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eLooking at the parts in isolation may work well enough when your systems are simple: find what broke, replace or fix or tweak it, and move on. But as they scale up and become more connected to other systems, they also necessarily become more complex. As a result, the way we construct explanations about those systems has to change as well. Looking at so-called “faulty” individual components or people that need to be corrected provides diminishing returns and loses its effectiveness.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eEventually, this is why blame hurts. Blame fundamentally implies that someone or something misbehaved, that they are \u003cem\u003eresponsible\u003c/em\u003e for causing the outcomes. Blame, as a concept, invites retribution. And retribution in turn drives people involved in adverse events to protect themselves, which means it becomes harder to learn from what happened.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eSo not only do we get a focus that is centred on individual units, we make it harder to ever get a better understanding on top of it. This is where concepts such as blamelessness (or \u003ca href=\"https://dev.to/reinh/beyond-blameless-3oif\" rel=\"nofollow noreferrer noopener\"\u003eblame-awareness\u003c/a\u003e) come from: we realize that blame is an expected reaction to surprising negative events, but also know that post-incident responses that lean into these feelings do not tend to be effective in the long run.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eBut being blameless isn’t purely a concept for justice to ensure we don’t punish people for being put in a tough situation by a system that doesn’t even realize it—although it certainly can help—it is also a concept that invites a stance that is systems-oriented.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eYou don’t just \u003cem\u003eavoid\u003c/em\u003e blame. It’s a natural feeling to feel blame, but you have to go past it and shift your perspective towards the system “owning” the situation.\u003c/p\u003e\n\u003ch1 dir=\"ltr\"\u003eWhat Makes Blame Superficial\u003c/h1\u003e\n\u003cp dir=\"ltr\"\u003eSuperficial blamelessness will be easiest to spot when retribution is still the norm, whether officially or only informally. People will avoid naming employees or even teams, and internal reports will look as non-specific as if they were intended for an external audience. But even if you take away the “name” bit from the cycle of \u003cem\u003ename\u003c/em\u003e → \u003cem\u003eblame\u003c/em\u003e → \u003cem\u003eshame\u003c/em\u003e, the cycle lives on.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eOrganizations where blame is less “ambient” or better harnessed will instead consider it safe to name names, and will invite a conversation with the people involved to get their perspective—one they do not have as a bystander—to get a richer view of how the system works. But even in these places, where it might be safe to give your account of what happened, there’s not yet any guarantee that you’re getting what you should out of it all. Blame is only one of many blockers on the way to a better systems perspective.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eBe wary of successfully avoiding retribution, yet finding your post-incident process still biased towards an individualistic stance instead of a systemic one. Consider, for example, whether suggestions of what to improve after adverse events mostly focus on what specific people involved need to do better, even without punishment. Common ones are:\u003c/p\u003e\n\u003cul\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003cp dir=\"ltr\"\u003eProvide more training\u003c/p\u003e\n\u003c/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003cp dir=\"ltr\"\u003eAdjust a worker’s behavior\u003c/p\u003e\n\u003c/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003cp dir=\"ltr\"\u003eWrite a specific patch or test\u003c/p\u003e\n\u003c/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003cp dir=\"ltr\"\u003eBe reminded to “pay more attention”\u003c/p\u003e\n\u003c/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003cp dir=\"ltr\"\u003eAdd more reviewers or supervision to catch mistakes\u003c/p\u003e\n\u003c/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003cp dir=\"ltr\"\u003eTweak the process or procedures \u003cem\u003edirectly\u003c/em\u003e related to the incident\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"ltr\"\u003eThe locus of intervention, in these cases, is oriented towards specific people or components. Some of these might be useful and helpful, but if they’re most of what you get, you can suspect a systemic point of view isn’t strongly developed yet.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eMore systemic interventions are those that would change the conditions that lead to challenging situations. You could, for example, change or clarify broad pressures and goal conflicts. Likewise, the behavior you didn’t like in the context leading up to an incident might be valued in “normal” circumstances. Software development, after all, can have contributing factors that come from other departments too.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eYou might also find items such as tweaking processes or procedures that go beyond the circumstances of the incident. Maybe someone found out that relevant and useful information came up in informal discussion groups: those could perhaps be encouraged more, or the recipe expanded to other areas important to the organization, because they can help foster a culture that can deal with surprises better. If you find other teams have solutions that exist already, it’s worth asking if they could be borrowed and propagated, but also what could make it easier to figure out if there are ideas worth borrowing. And why not go further and find out under what circumstances that other team figured it out to see if there’s something to learn?\u003c/p\u003e\n\u003ch1 dir=\"ltr\"\u003eControl-centric vs. Empowerment-centric Approaches\u003c/h1\u003e\n\u003cp dir=\"ltr\"\u003eThe distinction between systemic and individualistic is usually a good marker, mostly observable once you are looking at a completed review process and its list of actions. It might not be visible yet, because the process isn’t over or continuous, and it might also not be simple: people do what they can given the circumstances.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eAnother angle in which you can frame this comparison between individualistic and systemic elements is going to be based on an opposition between control and empowerment. If you are approaching the problem from a stance where you need to restrict and control what people do to keep it within specific parameters because they are not operating as you expect them to, then you are taking a control-centric approach. Ask yourself whether this isn’t a subtle way to be blaming people for the problems they’ve been asked to solve.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eAn empowerment-centric approach would instead ask how you can make the work simpler,\u0026nbsp; safer, easier, clearer, or more manageable. Involve the people impacted in the process, not because they need to do better, but because the system needs to make sure they’re operating in better conditions.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u003cimg src=\"https://d21hwc2yj2s6ok.cloudfront.net/shrine_store/uploads/networks/3057/communication_news/11502437/compressed-26c34733bbc8569171fb7a678ca2af66.webp\" alt=\"\" width=\"130\" height=\"130\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFred Hebert\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStaff SRE\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3b:T24ee,"])</script><script>self.__next_f.push([1,"\u003cp dir=\"ltr\"\u003eIn 2012, John Allspaw (then CTO of Etsy) wrote a \u003ca href=\"https://www.etsy.com/codeascraft/blameless-postmortems\" rel=\"nofollow noreferrer noopener\" target=\"_blank\"\u003eseminal blog post\u003c/a\u003e on the need for what he called Blameless Postmortems. Built off the notion of a “Just Culture” from the research of \u003ca href=\"https://www.amazon.com/Just-Culture-Sidney-Dekker/dp/147247578X\" rel=\"nofollow noreferrer noopener\" target=\"_blank\"\u003eSidney Dekker\u003c/a\u003e, he summarized Etsy’s approach to balancing accountability in post-incident reviews with a need for avoiding blaming individuals who were involved in the incident:\u0026nbsp;\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003e“Having a \"Just Culture\" means that you’re making [an] effort to balance safety and accountability. It means that by investigating mistakes in a way that focuses on the situational aspects of a failure’s mechanism and the decision-making process of individuals proximate to the failure, an organization can come out safer than it would normally be if it had simply punished the actors involved as a remediation.”\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cp dir=\"ltr\"\u003eHe goes on to explain how engineers involved in incidents can be encouraged to give detailed accounts of what happened without fear of punishment or retribution. The word blamelessness took on a life of its own and became slightly disconnected from Dekker’s research and John’s blog post. Further refinements such as \u003ca href=\"https://dev.to/reinh/beyond-blameless-3oif\" rel=\"nofollow noreferrer noopener\" target=\"_blank\"\u003eblame-awareness\u003c/a\u003e came in to add some nuance to the ongoing discourse as well.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eFor many organizations, some form of \u003cem\u003eblamelessness\u003c/em\u003e has become a more standard practice and \u003cem\u003eblame-awareness \u003c/em\u003ehas been gaining in popularity. However, there is an anti-pattern I have noticed as well, which I like to call superficial (or shallow) blamelessness that I think is important for people to be on the lookout for.\u003c/p\u003e\n\u003ch1\u003eWhy Try to Be Blameless?\u003c/h1\u003e\n\u003cp dir=\"ltr\"\u003eResilience Engineering, and many of the connected disciplines it borrows from, aims to leverage incidents and the energy put behind them to better understand how a system works. The idea goes, the better you understand the dynamics in play, the less likely you are to make misguided suggestions, to operate on false assumptions, and to create accidental harm (among many other things).\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eDisciplines that look at complex systems prefer to focus on \u003cem\u003einteractions between components\u003c/em\u003e rather than specific parts themselves (what many consider to be the “root cause”): individual units can be working fine—reliably and in accordance with their goals—but still end up behaving surprisingly \u003cem\u003eas an ensemble.\u003c/em\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eLooking at the parts in isolation may work well enough when your systems are simple: find what broke, replace or fix or tweak it, and move on. But as they scale up and become more connected to other systems, they also necessarily become more complex. As a result, the way we construct explanations about those systems has to change as well. Looking at so-called “faulty” individual components or people that need to be corrected provides diminishing returns and loses its effectiveness.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eEventually, this is why blame hurts. Blame fundamentally implies that someone or something misbehaved, that they are \u003cem\u003eresponsible\u003c/em\u003e for causing the outcomes. Blame, as a concept, invites retribution. And retribution in turn drives people involved in adverse events to protect themselves, which means it becomes harder to learn from what happened.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eSo not only do we get a focus that is centred on individual units, we make it harder to ever get a better understanding on top of it. This is where concepts such as blamelessness (or \u003ca href=\"https://dev.to/reinh/beyond-blameless-3oif\" rel=\"nofollow noreferrer noopener\" target=\"_blank\"\u003eblame-awareness\u003c/a\u003e) come from: we realize that blame is an expected reaction to surprising negative events, but also know that post-incident responses that lean into these feelings do not tend to be effective in the long run.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eBut being blameless isn’t purely a concept for justice to ensure we don’t punish people for being put in a tough situation by a system that doesn’t even realize it—although it certainly can help—it is also a concept that invites a stance that is systems-oriented.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eYou don’t just \u003cem\u003eavoid\u003c/em\u003e blame. It’s a natural feeling to feel blame, but you have to go past it and shift your perspective towards the system “owning” the situation.\u003c/p\u003e\n\u003ch1\u003eWhat Makes Blame Superficial\u003c/h1\u003e\n\u003cp dir=\"ltr\"\u003eSuperficial blamelessness will be easiest to spot when retribution is still the norm, whether officially or only informally. People will avoid naming employees or even teams, and internal reports will look as non-specific as if they were intended for an external audience. But even if you take away the “name” bit from the cycle of \u003cem\u003ename\u003c/em\u003e → \u003cem\u003eblame\u003c/em\u003e → \u003cem\u003eshame\u003c/em\u003e, the cycle lives on.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eOrganizations where blame is less “ambient” or better harnessed will instead consider it safe to name names, and will invite a conversation with the people involved to get their perspective—one they do not have as a bystander—to get a richer view of how the system works. But even in these places, where it might be safe to give your account of what happened, there’s not yet any guarantee that you’re getting what you should out of it all. Blame is only one of many blockers on the way to a better systems perspective.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eBe wary of successfully avoiding retribution, yet finding your post-incident process still biased towards an individualistic stance instead of a systemic one. Consider, for example, whether suggestions of what to improve after adverse events mostly focus on what specific people involved need to do better, even without punishment. Common ones are:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp dir=\"ltr\"\u003eProvide more training\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"ltr\"\u003eAdjust a worker’s behavior\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"ltr\"\u003eWrite a specific patch or test\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"ltr\"\u003eBe reminded to “pay more attention”\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"ltr\"\u003eAdd more reviewers or supervision to catch mistakes\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"ltr\"\u003eTweak the process or procedures \u003cem\u003edirectly\u003c/em\u003e related to the incident\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"ltr\"\u003eThe locus of intervention, in these cases, is oriented towards specific people or components. Some of these might be useful and helpful, but if they’re most of what you get, you can suspect a systemic point of view isn’t strongly developed yet.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eMore systemic interventions are those that would change the conditions that lead to challenging situations. You could, for example, change or clarify broad pressures and goal conflicts. Likewise, the behavior you didn’t like in the context leading up to an incident might be valued in “normal” circumstances. Software development, after all, can have contributing factors that come from other departments too.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eYou might also find items such as tweaking processes or procedures that go beyond the circumstances of the incident. Maybe someone found out that relevant and useful information came up in informal discussion groups: those could perhaps be encouraged more, or the recipe expanded to other areas important to the organization, because they can help foster a culture that can deal with surprises better. If you find other teams have solutions that exist already, it’s worth asking if they could be borrowed and propagated, but also what could make it easier to figure out if there are ideas worth borrowing. And why not go further and find out under what circumstances that other team figured it out to see if there’s something to learn?\u003c/p\u003e\n\u003ch1\u003eControl-centric vs. Empowerment-centric Approaches\u003c/h1\u003e\n\u003cp dir=\"ltr\"\u003eThe distinction between systemic and individualistic is usually a good marker, mostly observable once you are looking at a completed review process and its list of actions. It might not be visible yet, because the process isn’t over or continuous, and it might also not be simple: people do what they can given the circumstances.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eAnother angle in which you can frame this comparison between individualistic and systemic elements is going to be based on an opposition between control and empowerment. If you are approaching the problem from a stance where you need to restrict and control what people do to keep it within specific parameters because they are not operating as you expect them to, then you are taking a control-centric approach. Ask yourself whether this isn’t a subtle way to be blaming people for the problems they’ve been asked to solve.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eAn empowerment-centric approach would instead ask how you can make the work simpler,\u0026nbsp; safer, easier, clearer, or more manageable. Involve the people impacted in the process, not because they need to do better, but because the system needs to make sure they’re operating in better conditions.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u003cimg src=\"https://d21hwc2yj2s6ok.cloudfront.net/shrine_store/uploads/networks/3057/communication_news/11502437/compressed-26c34733bbc8569171fb7a678ca2af66.webp\" style=\"max-width:100%\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFred Hebert\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStaff SRE\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3c:T38cc,"])</script><script>self.__next_f.push([1,"\u003ch1 dir=\"ltr\"\u003eSaturation\u003c/h1\u003e\n\u003cp dir=\"ltr\"\u003eEvery system has its limits. If you keep throwing more and more at a system, at some point it will no longer be able to function properly. The term \u003cem\u003esaturation\u003c/em\u003e refers to the state of a system where the demands on the system are high enough that the system is at the limits of its normal performance.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eElectrical engineering provides a helpful visualization of saturation. Imagine you want to amplify an electrical signal by a factor of four. This is the behavior you want.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cimg src=\"https://resilienceinsoftware.org/storage/4452706/download\" width=\"990\" height=\"390\"\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eHowever, real amplifiers have limits on how much the voltage can swing. With some amplifiers, you get a clipping effect, where the output hits some maximum or minimum voltage. In the graph below, this happens above +3.3V and below -3.3V: the signal goes flat instead of following the shape of the input.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cimg src=\"https://resilienceinsoftware.org/storage/4452707/download\" width=\"990\" height=\"390\"\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eWe say that the amplifier is in saturation when this happens. When it is in saturation, it no longer behaves like a linear amplifier anymore. Instead, it has undesired, non-linear behavior.\u003c/p\u003e\n\u003ch2 dir=\"ltr\"\u003eThe Limits of Software Systems\u003c/h2\u003e\n\u003cp dir=\"ltr\"\u003eWe often think of software as having an ethereal quality to it, “\u003cem\u003eonly slightly removed from pure thought-stuff\u003c/em\u003e” as Fred Brooks puts it. But software needs to execute on hardware, and hardware always has physical limits. The primary physical limits of hardware are CPU cycles, memory, disk space, and network bandwidth. Each of these is a finite resource with fixed, limited capacity.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eVery bad things can happen if you fully deplete these physical resources. For example, if you exhaust the available physical memory on a Linux machine, the dreaded OOM (Out of Memory) Killer will terminate a running process to reclaim some memory, and it may be a process you would prefer to keep running.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eSince bad things like OOM kills happen when you reach the physical limits of these resources, there are also virtual limits that engineers put in place to fail before running out of physical resources. For example, many applications use \u003cem\u003eresource pools\u003c/em\u003e as a resource management strategy: the two I know best are thread pools and database connection pools.\u0026nbsp; Once all of the resources in a pool are in use, new requests are queued, and the requester must wait for a resource to become free. The effect of queueing is that it increases latency, which changes system behavior.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eSpeaking of queues, there are queues everywhere in the system, and they frequently have their own virtual limits in the form of maximum sizes. For example, if you wanted to know maximum size of the queue for incoming TCP socket connections on the Linux system, you can see it by doing:\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-family: 'Courier new';\"\u003e$ sysctl net.core.somaxconn\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-family: 'Courier new';\"\u003enet.core.somaxconn = 4096\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eYou can view various limits by using the \u003cspan style=\"font-family: 'Courier new';\"\u003esysctl -a\u003c/span\u003e and \u003cspan style=\"font-family: 'Courier new';\"\u003eulimit -a\u003c/span\u003e commands, including maximum number of IP ports, maximum number of threads, or and maximum number of open file descriptors.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eEven \u003cspan style=\"font-family: 'Courier new';\"\u003esysctl\u003c/span\u003e and \u003cspan style=\"font-family: 'Courier new';\"\u003eulimit\u003c/span\u003e won’t tell you about all of the limits on your system. I once saw a very confusing “No space left on device” error on a Linux system, even though there was plenty of free disk space. That was the day I learned that there is also a limit on the total number of files and directories that a given filesystem can support, even if these files aren’t consuming all of the space. In my case, the limit had been exhausted by a script that created many small files each time it was executed, but they never got cleaned.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eCloud computing makes it easier for us to provision additional compute, disk, and network resources. We can even automate the process of deploying additional compute resources when we’re running low. Such automated systems are called \u003cem\u003eautoscalers\u003c/em\u003e, because they automatically request or return resources based on a signal that indicates load, such as CPU utilization or request rate. But even though we describe the cloud as being \u003cem\u003eelastic\u003c/em\u003e (that’s the E in Amazon services like EC2 and EKS), cloud providers themselves have a finite amount of resources. For example, you may get an \u003cem\u003einsufficient capacity\u003c/em\u003e error, which means that your cloud provider cannot currently meet your request for additional resources. In practice, autoscalers also have virtual limits, e.g. a configured maximum number of pods or virtual machines that it will scale up to, in order to protect against an expected runaway increase in the number of pods.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eSometimes limits are imposed on us by external systems that we interact with. If your system interacts with a third-party system (such as a cloud provider) over an API, there’s a good chance that they enforce rate limits over those APIs.\u0026nbsp;\u003c/p\u003e\n\u003ch2 dir=\"ltr\"\u003eSystem Behavior Changes at the Limit\u003c/h2\u003e\n\u003cp dir=\"ltr\"\u003eVirtual limits exist to protect the system from breaching its physical limit. The idea is to reduce the potential damage to the system due to overload by failing earlier in a less harmful way. It’s similar to how a circuit breaker protects your house by opening a circuit to prevent the current from reaching a dangerous level. It’s annoying to have to go to the breaker box and flip the breaker closed again, but it’s better than having your house burn down. However, this may be of little consolation if your application falls over when you’ve breached a virtual limit.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eIn some cases, the system doesn’t behave any differently until the limit is actually breached. For example, a system that is writing data to disk will behave perfectly normally right until the disk is absolutely full, at which time it will return write errors. Unless you have an alert explicitly set up to track when your disk is almost full, you won’t find out until it’s too late.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eIn many cases, though, the system behavior starts to change \u003cem\u003eas it nears saturation\u003c/em\u003e. As mentioned earlier, a common behavior change near saturation is an increase in response latency. For example, Java applications that run low on available memory will spend more time on garbage collection (gc), including stop-the-world phases of garbage collection which are known as \u003cem\u003egc pauses\u003c/em\u003e. This means that as a service starts to run out of memory, response latency goes up. If the response latency gets too high, this can result in timeout errors. Similarly, high CPU utilization can also increase response latency, because the application threads have to wait to get access to CPU resources in order to service requests.\u003c/p\u003e\n\u003ch2 dir=\"ltr\"\u003eExamples of Incidents Involving Saturation\u003c/h2\u003e\n\u003cp dir=\"ltr\"\u003eOnce you start thinking of saturation explicitly as a failure mode, you’ll start to see it in many incidents, either as part of the failure mode itself, or as a factor that makes response or recovery more difficult.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eHere are some examples from public incident writeups, my emphasis added.\u003c/p\u003e\n\u003ch3 dir=\"ltr\"\u003eWaymo\u003c/h3\u003e\n\u003cp dir=\"ltr\"\u003eIn December 2025, there was a large power outage in San Francisco. This had the surprising effect of \u003ca href=\"https://surfingcomplexity.blog/2025/12/23/saturation-waymo-edition/\" rel=\"nofollow noreferrer noopener\"\u003eparalyzing Waymos in the city.\u003c/a\u003e It turned out that Waymos are more likely to issue confirmation checks when encountering an intersection when the traffic lights are out. From the \u003ca href=\"https://waymo.com/blog/2025/12/autonomously-navigating-the-real-world\" rel=\"nofollow noreferrer noopener\"\u003eWaymo announcement\u003c/a\u003e (emphasis mine):\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003eWhile we successfully traversed more than 7,000 dark signals on Saturday, the outage created a \u003cstrong\u003econcentrated spike\u003c/strong\u003e in these requests. This created a \u003cstrong\u003ebacklog\u003c/strong\u003e that, in some cases, led to response delays contributing to congestion on already-overwhelmed streets.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003ch3 dir=\"ltr\"\u003eCloudflare\u003c/h3\u003e\n\u003cp dir=\"ltr\"\u003eIn November 2025, Cloudflare \u003ca href=\"https://surfingcomplexity.blog/2025/11/26/brief-thoughts-on-the-recent-cloudflare-outage/\" rel=\"nofollow noreferrer noopener\"\u003eexperienced an outage\u003c/a\u003e that involved a file being larger than a virtual limit on its size. From the \u003ca href=\"https://blog.cloudflare.com/18-november-2025-outage/\" rel=\"nofollow noreferrer noopener\"\u003ewriteup\u003c/a\u003e:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003e\u003cem\u003eThe software\u0026nbsp;\u003cstrong\u003ehad a limit\u003c/strong\u003e on the size of the feature file that was below its doubled size. That caused the software to fail\u003c/em\u003e.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003ch3 dir=\"ltr\"\u003eGoogle Cloud Platform\u003c/h3\u003e\n\u003cp dir=\"ltr\"\u003eIn June 2025, Google Cloud Platform \u003ca href=\"https://surfingcomplexity.blog/2025/06/14/quick-takes-on-the-gcp-public-incident-write-up/\" rel=\"nofollow noreferrer noopener\"\u003eexperienced an outage\u003c/a\u003e where recovery was made more difficult due to saturation. From the \u003ca href=\"https://status.cloud.google.com/incidents/ow5i3PPK96RduMcb1SsW\" rel=\"nofollow noreferrer noopener\"\u003ewriteup\u003c/a\u003e:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003e\u003cem\u003eWithin some of our larger regions, such as us-central-1, as Service Control tasks restarted, it created a herd effect on the underlying infrastructure it depends on (i.e. that Spanner table),\u0026nbsp;\u003cstrong\u003eoverloading\u003c/strong\u003e the infrastructure.\u003c/em\u003e\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003ch3 dir=\"ltr\"\u003eOpenAI\u003c/h3\u003e\n\u003cp dir=\"ltr\"\u003eIn December 2024, OpenAI \u003ca href=\"https://surfingcomplexity.blog/2024/12/14/quick-takes-on-the-recent-openai-public-incident-write-up/\" rel=\"nofollow noreferrer noopener\"\u003eexperienced an outage\u003c/a\u003e that involved their Kubernetes API servers becoming saturated. From the \u003ca href=\"https://status.openai.com/incidents/ctrsv3lwd797\" rel=\"nofollow noreferrer noopener\"\u003ewriteup\u003c/a\u003e:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003e\u003cem\u003eWith thousands of nodes performing these operations simultaneously, the\u0026nbsp;\u003cstrong\u003eKubernetes API servers became overwhelmed\u003c/strong\u003e, taking down the Kubernetes control plane in most of our large clusters.\u003c/em\u003e\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003ch3 dir=\"ltr\"\u003eCanva\u003c/h3\u003e\n\u003cp dir=\"ltr\"\u003eAlso in December 2024, Canva \u003ca href=\"https://surfingcomplexity.blog/2024/12/21/the-canva-outage-another-tale-of-saturation-and-resilience/\" rel=\"nofollow noreferrer noopener\"\u003eexperienced an outage\u003c/a\u003e that was triggered by a deploy. There was no problem with the newly deployed code itself, but clients downloading the new javascript files from the CDN set off a series of events that led to their API gateway getting overloaded. From their \u003ca href=\"https://www.canva.dev/blog/engineering/canva-incident-report-api-gateway-outage/\" rel=\"nofollow noreferrer noopener\"\u003ewriteup\u003c/a\u003e:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003e\u003cem\u003eAPI Gateway tasks begin failing due to\u0026nbsp;\u003cstrong\u003ememory exhaustion\u003c/strong\u003e, leading to a full collapse.\u003c/em\u003e\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003ch3 dir=\"ltr\"\u003eRogers\u003c/h3\u003e\n\u003cp dir=\"ltr\"\u003eIn July 2022, Rogers \u003ca href=\"https://surfingcomplexity.blog/2024/07/06/quick-takes-on-rogers-network-outage-executive-summary/\" rel=\"nofollow noreferrer noopener\"\u003eexperienced an outage\u003c/a\u003e that involved routers getting overloaded. From the \u003ca href=\"https://crtc.gc.ca/eng/publications/reports/xona2024.htm\" rel=\"nofollow noreferrer noopener\"\u003ewriteup\u003c/a\u003e:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003eThe flood of IP routing data from the distribution routers into the core routers \u003cstrong\u003eexceeded their capacity\u003c/strong\u003e to process the information.\u0026nbsp;\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003ch3 dir=\"ltr\"\u003eSlack\u003c/h3\u003e\n\u003cp dir=\"ltr\"\u003eIn January 2021, Slack \u003ca href=\"https://surfingcomplexity.blog/2021/02/08/slacks-jan-2021-outage-a-tale-of-saturation/\" rel=\"nofollow noreferrer noopener\"\u003eexperienced an outage\u003c/a\u003e that involved an internal provisioning system getting overloaded. From their \u003ca href=\"https://slack.engineering/slacks-outage-on-january-4th-2021/\" rel=\"nofollow noreferrer noopener\"\u003ewriteup\u003c/a\u003e:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"ltr\"\u003eThe spike of load from the simultaneous provisioning of so many instances under suboptimal network conditions meant that provision-service hit two separate resource bottlenecks (the most significant one was the \u003cstrong\u003eLinux open files limit\u003c/strong\u003e, but we also exceeded an \u003cstrong\u003eAWS quota limit\u003c/strong\u003e).\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003ch2 dir=\"ltr\"\u003eResilient Systems Deal Effectively with Saturation\u003c/h2\u003e\n\u003cp dir=\"ltr\"\u003eSaturation is a key concern in resilience engineering. In fact, according to the resilience engineering researcher David Woods, \u003ca href=\"https://www.researchgate.net/publication/327427067_The_Theory_of_Graceful_Extensibility_Basic_rules_that_govern_adaptive_systems\" rel=\"nofollow noreferrer noopener\"\u003ethe difference\u003c/a\u003e between a brittle system and a resilient one comes down to how well a system is able to deal with saturation.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eResilient systems are able to anticipate when saturation might happen soon, and take action before the imminent saturation turns into a real problem. As mentioned earlier, in cases like memory pressure, we can see symptoms that the system is getting close to a limit, but it in other cases like a disk filling up or hitting an autoscaling limit, there won’t be any indications that we’re close to a limit unless we know what signals to look for.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eResilient systems are also able to reconfigure themselves to deal with saturation. Incident response is the paradigmatic example of this sort of system reconfiguration activity, which is why resilience engineering is particularly relevant to incident response. When your organization experiences a saturation-related incident,\u0026nbsp; the human responders need to take action. You can think about the actions that they take as literally changing how the system works, in order to bring the system back to health. That’s what resilience is all about.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://resilienceinsoftware.org/storage/4452714/download\" alt=\"\" width=\"160\" height=\"160\"\u003e\u003cstrong\u003eLorin Hochstein\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3d:T299b,"])</script><script>self.__next_f.push([1,"\u003cp dir=\"ltr\"\u003eDear Om,\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eI want to begin by stating that I have an immense amount of respect for you—I followed your work at GigaOm while I was a rising editor and conference chair at O'Reilly Media in the 2010s. I subscribe to your newsletter and appreciate your well-earned, often biting, takes on the current state of our industry. That said, I was sadly disappointed in your recent article \"\u003ca href=\"https://om.co/2026/04/14/human-error-is-ok-machine-madness-is-a-no-no-why/\" rel=\"nofollow noreferrer noopener\"\u003eHuman Error is OK! Machine Madness is a No-No! Why\u003c/a\u003e?\" My goal here is to present enough information to convince you to update your mental model when it comes to \"human error\" because the views you've espoused continue to permeate our industry and have real, significant consequences for how we understand and investigate failure in software systems.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eYou begin with a perfectly reasonable-sounding question: why do we accept human error but not machine/AI error? You assert that \"we forgive human error as if it were weather.\" But as someone who researches incidents and their aftermaths, what I've seen over 20+ years in this industry is that this is categorically untrue. In general, our industry \u003ca href=\"https://www.etsy.com/codeascraft/blameless-postmortems\" rel=\"nofollow noreferrer noopener\"\u003etreats human error as a scapegoat\u003c/a\u003e: a way to avoid looking any deeper into the more thorny aspects of managing complex systems (goal conflicts, financial pressures, organizational dysfunction, etc). And not far into your own post, you demonstrate exactly this: rather than accepting human error like wind or rain, you use it to pin large-scale outages on people. \"Fat fingers, credential theft, misconfiguration, copy-paste mistakes…\" This is important because scapegoating can lead to people getting punished (or even fired) for complex events in which their behavior was almost always an attempt to resolve the situation, not make it worse. This has a knock-on effect of creating cultures of fear and shame where latent issues don’t get reported out of concern for retribution, which is one of the many damning conclusions about the culture that led to the Challenger disaster.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eIt’s also worth noting that it is only possible to make these kinds of claims after everything has happened and you get what feels like a clean and easily-explained linear account that feels tidy thanks to a large serving of hindsight bias. Ask anyone who is regularly involved in these kinds of events and they will quickly disabuse you of the notion that they are this simply and easily explained.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eWe have to consider that there is something to the idea that we do accept human error more so than automation error: collectively, people have internalized people being fallible, and automation/machines/AI being reliable and correct. People can feel guilt, be blamed, be removed from the situation (whether this is a good idea or not); blaming individuals provides a therapeutic illusion of removing the one “bad apple” and moving on.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eGiven this instinct, humans are often framed as chaotic elements in an otherwise safe system (wrongly so; they’re an adaptive element), and machine processes as the embodiment of system priorities and goals. This means that using human error as an explanation shortcircuits our thinking and prevents questioning the system. Forgiving AI errors, perhaps ironically, therefore also shortcircuits our thinking and prevents questioning the system.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eMost dangerously, though, is this idea: \"...more than AI, it is human error that is a clear and present danger.\" This is a claim we've heard repeatedly to justify automation, AI, and self-driving cars, etc. If only we could cut those pesky humans and all their mistakes out of the loop entirely, all would be well. To this point, you invoke the research of James Reason and his Swiss Cheese model, however the broader field of Resilience Engineering (to which Reason was an early contributor) \u003ca href=\"https://www.eurocontrol.int/publication/revisiting-swiss-cheese-model-accidents\" rel=\"nofollow noreferrer noopener\"\u003ehas long debated the merits of that model\u003c/a\u003e. Even if one fully agreed with Reason, your interpretation of his Swiss Cheese model is inaccurate—Reason himself considered human error only as a triggering element, and insisted that it was an inadequate stopping point for an investigation. He considered errors to be outcomes of the environment and not an explanation by themselves, and urged us to recognise that human variability is consistently a force to harness in averting errors.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eDr. Richard Cook, in his foundational summary \u003ca href=\"https://how.complexsystems.fail/\" rel=\"nofollow noreferrer noopener\"\u003eHow Complex Systems Fail\u003c/a\u003e, is unambiguous: post-incident attribution to any root cause (including \"human error\") is fundamentally wrong. Because overt failure in complex systems requires multiple faults co-occurring, there is no isolated cause of an incident. The search for a single cause, and \"human error\" is almost always the answer that search produces, does not reflect a technical understanding of failure. It reflects, in Cook's words, \"the social, cultural need to blame specific, localized forces or events for outcomes.\"\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eThis matters because complex systems don't operate in a safe, neutral state waiting to be disrupted by careless people (or mischievous machines). They are, as Cook puts it, always running in degraded mode: containing ever-changing mixtures of latent failures at any given moment, held together not despite their human operators but because of them. Practitioners are the adaptable element of these complex systems, constantly making real-time adjustments that regularly prevent those latent failures from compounding into catastrophe. The person who seemingly \"caused\" the incident is almost certainly the same person who prevented a dozen others that nobody ever wrote about, because all practitioner actions are gambles taken under uncertainty, and we only call them errors when the outcome is bad.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eThis is what system safety researcher \u003ca href=\"https://www.youtube.com/watch?v=Xd4U53Z1WoE\" rel=\"nofollow noreferrer noopener\"\u003eSidney Dekker\u003c/a\u003e calls the Old View: the assumption that systems work fine until a person breaks them, and that the fix is to find that person and correct or replace them. In his words: “There is an almost irresistible belief that we are custodians of already safe systems that need protection from unreliable, erratic human beings.\" The failures you catalogued (some of which didn’t even invoke human error in their own analyses)—the exposed password, the unreviewed command, the dormant VPN account—were not human intrusions into healthy systems. They were signals that those systems were already operating under conditions that made those outcomes possible, even predictable, but only in hindsight. Those are organizational and systemic failures. “An old VPN account with no multi-factor authentication, used by a human who had left the company” is not human error. Calling that human error doesn't explain or fix it. It obscures the deeper issues.\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eI’m also caught off-guard by your framing of things like post-incident reports as “failure theater.” This is disingenuous at best. Only if people involved in these incidents keep blaming surface elements and not looking deeper at their systems would I be willing to label these efforts as such. Many people involved in reviewing and analyzing incidents are deeply committed to looking beyond surface elements and temptingly simple “root causes” to better understand how their system as a whole led to what happened. And yes, while our industry has at times been ham-fisted in its approach to learning from failure and incidents, many of these practices come from other industries (aviation, healthcare, nuclear power) that have spent significantly more time and effort than we have grappling with the notion of failure in complex systems. I will concede that most public incident reports that we have access to as the public contain an element of theater, and are often written more to appease internal marketing/PR departments and shareholders, but let’s not throw the baby out with the bathwater please. The true danger in your argument is creating a false equivalency between humans and AI, which leads to philosophies (and, increasingly, real world products) based on the question “how could we tolerate so many human errors, and can’t we see that technology would let us get rid of their frustrating lack of reliability?”\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003eThere is a real and important conversation to be had about the novel risks of AI failure: its potential to replicate errors at scale, its opacity, and our current lack of AI-specific incident history. You're right that we're early in understanding how AI-generated failure behaves. But the solution is not to weigh our AI anxiety against a supposedly mature tolerance for human failure. That tolerance was never maturity. It was, and remains, a habit of naming things instead of understanding them. Safety, Cook reminds us, is not a property of any component of a system, human or machine. It is an emergent property of the system as a whole. Until we investigate both successes \u003cem\u003eand\u003c/em\u003e failures at that level, we will keep producing comfortable narratives and calling them explanations.\u003c/p\u003e\n\u003chr\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eCourtney Nash\u003c/strong\u003e, Vice President, Resilience in Software Foundation (RISF)\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003eWith contribution and review by:\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eFred Hebert\u003c/strong\u003e, Board Member, RISF\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eJohn Allspaw\u003c/strong\u003e, Principal, Adaptive Capacity Labs\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eMaria Jackson\u003c/strong\u003e, RISF Member\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eRachel Silber\u003c/strong\u003e, Complex Systems Group\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eSheeri Cabral\u003c/strong\u003e, Director of Enterprise Architecture, myKaarma\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eKurt Andersen\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eRobert Barron\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan style=\"font-size: 12px;\"\u003e\u003cstrong\u003eThomas Depierre\u003c/strong\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e"])</script><script>self.__next_f.push([1,"5:[\"$\",\"$L39\",null,{\"news\":{\"id\":11502437,\"og_url\":null,\"pinned_to_feed\":false,\"pinned_to_index_page\":false,\"public\":true,\"publication_timezone\":\"America/Los_Angeles\",\"published_at\":\"2026-04-15T22:30:00Z\",\"rss_url\":null,\"seo_canonical_url\":null,\"seo_description\":null,\"seo_title\":null,\"social_media_list\":[\"linkedin\"],\"visible_on_feed\":false,\"visible_on_index_page\":true,\"type\":\"news\",\"subject\":\"Superficial Blamelessness\",\"content\":\"$3a\",\"sanitized_content\":\"In 2012, John Allspaw (then CTO of Etsy) wrote a seminal blog post on the need for what he called Blameless Postmortems. 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