Title

AWS re:Invent 2023 - Surviving overloads: How Amazon Prime Day avoids congestion collapse (NET402)

Summary

• Jim Roskind's Presentation:

  • Jim Roskind, a distinguished engineer, discusses strategies to avoid congestion collapse, a phenomenon where a system becomes overloaded, leading to zero productive work despite high resource utilization.
  • He provides examples of congestion collapse from various domains, including highway traffic, telephone networks, and TCP/IP networking.
  • Roskind emphasizes the importance of testing beyond expected loads, identifying hidden queues, and implementing retries judiciously.
  • He shares Amazon's experience with Prime Day 2018, where a distributed hash table overload led to a significant outage, and the subsequent measures taken to prevent future occurrences, such as reducing retries and crush testing.

• Enki Chadha's Presentation:

  • Enki Chadha, a solutions architect, explains how AWS tools can be used to detect, avoid, and test for congestion collapse.
  • He recommends using Amazon CloudWatch for monitoring, AWS Shield Advanced and WAF for security, and AWS Fault Injection Simulator for chaos engineering.
  • Chadha also discusses the use of Amazon CloudFront for content delivery, AWS WAF for rate limiting, and Amazon SQS for decoupling system components to manage load effectively.
  • He advises on creating a small-scale model of applications for crush testing and using real-world traffic patterns for accurate testing.

Insights

• Congestion Collapse:

  • Congestion collapse is not unique to computing and can occur in any system where demand exceeds capacity, leading to a state where increased effort results in diminishing returns or no productive output.
  • The phenomenon is stateful, meaning once a system enters congestion collapse, it can take a significant amount of time to recover, even if demand decreases.

• Testing and Monitoring:

  • Testing should not only cover expected loads but also exceed them to identify potential points of failure that could lead to congestion collapse.
  • Monitoring is crucial for early detection of symptoms indicating a system is heading towards congestion collapse. CloudWatch metrics can be used to monitor system health and trigger alarms for proactive intervention.

• System Design:

  • Designing systems to handle overloads involves not just scaling up resources but also implementing intelligent mechanisms like rate limiting, retries, and decoupling components to prevent cascading failures.
  • Decoupling system components using services like Amazon SQS can prevent one component from overwhelming another, similar to how metering lights on highways prevent traffic congestion.

• User Experience:

  • Communicating effectively with users during high load situations can influence their behavior and prevent them from exacerbating the problem. Custom error pages or rate limit messages can deter users from repeatedly trying to access overloaded services.

• Security Measures:

  • Security services like AWS Shield Advanced and WAF not only protect against malicious attacks but also play a role in managing system load by filtering out unwanted traffic before it reaches the application layer.

• Chaos Engineering:

  • Adopting chaos engineering principles by intentionally introducing faults into the system can help teams understand how their applications behave under failure conditions and improve resilience against real-world incidents.