Meta outage: A System Design analysis

As frustrating as they are, service outages are among my favorite excuses for discussing System Design. Nothing like a widespread outage to underscore the critical nature of robust System Design in large-scale systems. 

Yesterday’s Meta outage (lasting several hours) is a case study of how even the most robust architectures can face critical failures. Despite the scale of the disruption, Meta’s engineering team leveraged the strengths of their architecture to quickly bring the platform back online.

Meta has yet to share details about the cause beyond “technical issues,” but we can certainly make some educated guesses on what may have caused this issue — and what we can learn as developers.

So, grab a coffee or a tea, as we discuss:

• This year’s Meta outage (and Meta outages of the past)

• Vulnerabilities of Meta’s infrastructure 

• Potential causes behind Meta’s outage

• Techniques engineers use to mitigate risks

How the Meta outage played out#

Yesterday’s global outage affected Instagram, Facebook, and WhatsApp, with millions of users unable to access services. Issues began around 09:50 a.m. PST (more than 100,000 Facebook users reported issues by 10:11 a.m.).

Because Meta’s platforms were affected, we have some indication that the technical issue concerned some shared infrastructure.  

Luckily, Meta was able to resolve the issue slowly throughout the afternoon. By 2:30 p.m., they announced they were 99% done with fixes. 

Cisco ThousandEyes, a network intelligence tool, also shared insights that hinted toward issues with backend services. 

They announced on X: “ThousandEyes is detecting internal server errors and time-outs, which may indicate issues with Meta’s backend services. Network connectivity to Meta’s frontend web servers remains unaffected.”¹

While Meta seems to be doing business as usual, no further details on what may have happened have been released. 

However, we might get hints from Meta’s past outages, which all concerned issues in configuration or backend servers:

• March 2024 (Facebook, Instagram, and Messenger):

  • Meta also attributed this vaguely to a “technical issue.” 

  • Meta’s web servers were accessible and responding to users, hinting toward issues in backend servers such as authentication or misconfiguration.

• October 2021 (Facebook, Instagram, and WhatsApp): 

  • A misconfiguration in the backbone routers disrupted DNS and BGP functionality, causing cascading failures. 

  • Even internal systems at Facebook were affected, requiring manual intervention at data centers.

• March 2019 (Facebook, Instagram, and WhatsApp):

  • Caused by a server configuration change

  • This 14-hour disruption was among the longest in Meta’s history, raising questions about redundancy in critical systems.

What caused yesterday’s Meta outage?#

While Meta hasn’t released the exact details, we can speculate. Here, I’ll consider different scenarios—from least likely to most likely.#

DNS misconfiguration#

A failure in DNS configuration or servers could prevent users from accessing any of Meta’s services.

Likelihood: As reported by Cisco, the frontend servers remained unaffected and were accessible to users, so this couldn’t be the reason for today’s failure.

Automatic error handling#

As convenient as it may seem, error handling is a tough skill to master. Ironically, error handling mechanisms designed to protect systems can sometimes worsen issues, and overly aggressive fail-safes can cause unnecessary disruptions. 

Likelihood: Unless the error handling system is common to all of Meta’s offerings, I doubt this could be the reason.

A traffic surge beyond the limit#

Modern systems like Meta are designed to handle immense traffic, but unexpected spikes can push even resilient architectures to their limits. A sudden surge in traffic—perhaps triggered by a viral post, an event, or even automated bots—could overwhelm backend servers or APIs.

Likelihood: Unexpected peaks are not uncommon to overwhelm systems (as we saw with the recent Paul vs. Tyson fight on Netflix). However, as all of Meta’s applications (Facebook, Instagram, WhatsApp, Thread) went down, it is highly unlikely that a sudden traffic spike caused the issue.

Network routing issues#

Meta’s global reach depends on its proprietary fiber network and extensive routing protocols. A misconfigured update could have disconnected parts of the infrastructure from the internet.

Likelihood: As this was the reason behind Meta’s 2021 outage when its BGP routes were accidentally removed, it could also be a reason this time.

Backend server error#

Meta’s architecture relies on countless microservices, each powering key features like the News Feed, Messenger, and Notifications. However, if one service (e.g., authentication) fails, it might time out and cascade, causing dependent services to crash.

Likelihood: This can be a potential reason, as a fault in any of the microservices (either authentication, configuration, error handling, or any other service) can interrupt normal operations.

Database deadlocks or shard failures

Meta’s databases process billions of reads and writes every second. A minor locking issue in a critical database shard could snowball into a system-wide outage.

Likelihood: Spikes in write operations (say, from viral content or a backend bug) might have triggered locks or even resource exhaustion.

Misconfiguration

Human errors in configuration cause most outages in distributed systems. Meta will likely encounter such an issue with its frequent updates to DNS records, load balancers, and routing protocols.

Likelihood: I believe this can be the most likely reason, as we have observed Meta’s outages due to similar issues. 

A System Design perspective on Meta’s recovery#

While Meta hasn’t disclosed specific details about the outage, one thing is clear: the speed of their recovery highlights the strength of their robust and scalable System Design. 

Let’s explore how foundational design principles likely helped Meta restore services.

• Redundancy and failover mechanisms: Strong systems are designed with redundancy at multiple levels—databases, services, and even entire data centers. When failures occur, systems can reroute traffic or rely on backup resources to minimize disruption. Meta’s ability to isolate and recover from the issue suggests these mechanisms were in play.

• Microservices architecture: Meta leverage microservices, which decouple functionalities into smaller, independent components. Meta’s engineering team likely leveraged this modularity to restore services iteratively.

• Configuration management: Configuration changes are a frequent cause of outages, but robust systems implement safeguards like staging environments, automated rollbacks, and canary deployments to limit impact. Even if the root cause was related to configuration, Meta’s ability to quickly fix and deploy changes demonstrates strong practices.

• Scalability and monitoring: Meta likely utilized advanced monitoring tools and scalable resources to diagnose the problem in real time. Such tools empower engineering teams to identify bottlenecks and respond promptly.

Takeaways from the Meta outage#

Service outages have no single reason, from overload to a simple configuration oversight or safeguards. If Meta releases details about the root cause of this outage, it will allow the engineering community to gain deeper insights into building more resilient shared architectures.

Outages are inevitable, but strong design ensures swift recovery and minimizes harm. Meta’s outage is a perfect example of how robust design principles—redundancy, failover, and scalability—translate into real-world impact. 

Here are some takeaways we can learn from yesterday’s event:

• Prepare for the worst: Design for extreme cases, unprecedented traffic, or unexpected bugs.

• Automate but verify: While automation reduces manual errors, it’s crucial to validate that automated responses don’t overreact.

• Continuously learn: Every outage is an opportunity to refine processes and build more resilient systems.

Design. Build. Repeat.#

As a developer, understanding System Design is essential for keeping up with an increasingly distributed world.

To build your skills, you can learn fundamentals, practice designing real-world systems, and avoid outages based on real-world case studies in our Grokking the Modern System Design Interview course.