Category: Resilience

Modern distributed systems must be resilient to unexpected disruptions to maintain availability, performance, and stability. Chaos engineering helps teams uncover hidden weaknesses by deliberately injecting faults into a system and observing how it recovers. While traditional testing validates expected behavior, chaos engineering tests system resilience during failures. AWS Fault Injection Service (AWS FIS) is a […]

In today’s fast-paced digital world, business continuity isn’t just a goal — it’s an achievable reality. As organizations continue to innovate and grow, their cloud-based applications have become the beating heart of modern business operations, delivering value to customers around the clock. Companies are taking their cloud strategy to the next level by embracing multi-Region […]

In the first two parts of our series, we explored how to scale AWS Fault Injection Service (FIS) across AWS Organizations. Part one focused on implementing FIS in a single AWS account environment, introducing the concept of standardized IAM roles and Service Control Policies (SCPs) as guardrails for controlled chaos engineering experiments, particularly in centralized […]

Welcome to part two of our series where we focus on scaling AWS Fault Injection Service (FIS) within your organization. In part one, we learned how customers can enable individual accounts within organizations by introducing a Service Control Policies (SCPs) rule to run network experiments when operating with a centralized networking infrastructure. In this blog, […]

AWS Fault Injection Service (FIS) empowers you to adopt chaos engineering at scale within your AWS environment. Chaos engineering injects real-world, controlled failures into a system to verify resilience and reliability, ultimately improving the customer experience. This proactive, resilience-focused approach increases your confidence in a system’s ability to respond to adverse conditions in production. You […]

We’re excited to announce that AWS Fault Injection Service (FIS) now supports a recovery action for Amazon Application Recovery Controller (ARC) zonal autoshift. With this integration, you can now perform more comprehensive testing by creating disruptive events and trigger a zonal autoshift as part of the same experiment. That way, you can observe how your application […]

Generative AI can streamline the Correction of Errors process, saving time and resources. By using generative AI to leverage large language models, combined with the Correction of Errors process, businesses can expedite the identification and documentation of the cause of errors, while saving time and resources. Purpose and set-up The purpose of this blog is […]

This blog post will walk you through an example of creating a Correction of Errors (COE) document. At Amazon, operational excellence is in our DNA. One best practice that we have learned at Amazon is to have a standard mechanism for post-incident analysis. The COE process facilitates learning from an event to avoid reoccurrences in […]

You may have encountered a situation in the past where a single user or small subset of users of your system are reporting an event that is impacting their experience, but your observability systems didn’t show any clear impact. The discrepancy between the customer’s experience and the system’s observation of its health is referred to […]

Application reliability is critical. Service interruptions result in a negative customer experience, thereby reducing customer trust and business value. One best practice that we have learned at Amazon, is to have a standard mechanism for post-incident analysis. This lets us analyze a system after an incident in order to avoid reoccurrences in the future. These […]