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Facebook Outage Reveals Critical DevOps Lessons … Again

Mehdi Daoudi
Catchpoint

If you live in the United States, there’s a good chance you had no idea that the Internet turned into a wide-ranging traffic accident last week when Facebook went down for half an hour. This is because the outage occurred on Thursday morning at around 3:50 am EDT, meaning that West Coast night owls were the only group on the continent that was really affected.

Elsewhere, however, it was a different story. Due to the time difference, Europe experienced the outage during early business hours, and much of Asia saw it happen in the late afternoon, resulting in widespread website failures during critical points in the day.

Now you may be asking why a social media site experiencing problems would be that big of an issue for business. Heck, given how much people procrastinate on Facebook, one might even wonder if the outage led to an increase in productivity.

The answer lies with the massive Internet footprint that Facebook carries. Many sites rely on the social media giant for third party services like login, commenting, and sharing platforms, so when Facebook is completely unavailable, it can wreak havoc on thousands of other sites as well. We saw plenty of examples of this last week during the outage.


Every one of those red dots in the above graphic represents a document complete from a specific location that took 30+ seconds. Because Facebook was blocking the document complete, the user experience was dramatically impacted, resulting in many infuriating pinwheels and hourglasses spinning over and over.

This is a perfect example of what is known in the DevOps world as a Single Point of Failure (SPOF). When one component of a website can render the entire thing completely unavailable if not functioning properly, it becomes a weak link that compromises the strength of the entire chain.

From a DevOps perspective, what is needed is a detailed plan in place to serve as a backup in case the third party service goes down. In the case of this latest Facebook outage, the problem lay with the fact that many sites, rather than using the asynchronous tags that Facebook provides, were using outdated ones that block document complete. These new tags, had they been applied to the affected sites, would have prevented any bad user experience and allowed the rest of the site to continue to function normally even if the Facebook components weren’t working.

This risk is not exclusive to Facebook, however; it’s one that is an inherent aspect of all third party services. Facebook may be one of the largest providers of these services, but they’re hardly alone.

The lesson learned from this experience – and one that most European or Asian sites are likely more aware of since the outage had a much greater effect on their businesses – is to build processes that ensure that you stay up to date with vendor changes. For example, Facebook began offering their asynchronous tags in late 2012, but nearly a year and a half later, many sites were clearly not yet using them due to the widespread performance issues that we saw during that half-hour window on Thursday morning.

Facebook’s login API, however, is a separate matter altogether. While asynchronous tags will prevent an entire page from being slowed down by a single non-critical element like sharing or commenting, if your site is inaccessible without a properly functioning login system, you’re facing a much greater problem. The solution here, therefore, is to have an alternative in-house login system in place so that your site is not relying on a single third party component that is ultimately outside of your control.

Identifying a SPOF is only the first step. Once located, implementing asynchronous tags or alternative solutions will prevent the SPOF from existing, thus proving a reliable and fast website.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

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Facebook Outage Reveals Critical DevOps Lessons … Again

Mehdi Daoudi
Catchpoint

If you live in the United States, there’s a good chance you had no idea that the Internet turned into a wide-ranging traffic accident last week when Facebook went down for half an hour. This is because the outage occurred on Thursday morning at around 3:50 am EDT, meaning that West Coast night owls were the only group on the continent that was really affected.

Elsewhere, however, it was a different story. Due to the time difference, Europe experienced the outage during early business hours, and much of Asia saw it happen in the late afternoon, resulting in widespread website failures during critical points in the day.

Now you may be asking why a social media site experiencing problems would be that big of an issue for business. Heck, given how much people procrastinate on Facebook, one might even wonder if the outage led to an increase in productivity.

The answer lies with the massive Internet footprint that Facebook carries. Many sites rely on the social media giant for third party services like login, commenting, and sharing platforms, so when Facebook is completely unavailable, it can wreak havoc on thousands of other sites as well. We saw plenty of examples of this last week during the outage.


Every one of those red dots in the above graphic represents a document complete from a specific location that took 30+ seconds. Because Facebook was blocking the document complete, the user experience was dramatically impacted, resulting in many infuriating pinwheels and hourglasses spinning over and over.

This is a perfect example of what is known in the DevOps world as a Single Point of Failure (SPOF). When one component of a website can render the entire thing completely unavailable if not functioning properly, it becomes a weak link that compromises the strength of the entire chain.

From a DevOps perspective, what is needed is a detailed plan in place to serve as a backup in case the third party service goes down. In the case of this latest Facebook outage, the problem lay with the fact that many sites, rather than using the asynchronous tags that Facebook provides, were using outdated ones that block document complete. These new tags, had they been applied to the affected sites, would have prevented any bad user experience and allowed the rest of the site to continue to function normally even if the Facebook components weren’t working.

This risk is not exclusive to Facebook, however; it’s one that is an inherent aspect of all third party services. Facebook may be one of the largest providers of these services, but they’re hardly alone.

The lesson learned from this experience – and one that most European or Asian sites are likely more aware of since the outage had a much greater effect on their businesses – is to build processes that ensure that you stay up to date with vendor changes. For example, Facebook began offering their asynchronous tags in late 2012, but nearly a year and a half later, many sites were clearly not yet using them due to the widespread performance issues that we saw during that half-hour window on Thursday morning.

Facebook’s login API, however, is a separate matter altogether. While asynchronous tags will prevent an entire page from being slowed down by a single non-critical element like sharing or commenting, if your site is inaccessible without a properly functioning login system, you’re facing a much greater problem. The solution here, therefore, is to have an alternative in-house login system in place so that your site is not relying on a single third party component that is ultimately outside of your control.

Identifying a SPOF is only the first step. Once located, implementing asynchronous tags or alternative solutions will prevent the SPOF from existing, thus proving a reliable and fast website.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

Hot Topics

The Latest

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

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Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

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