Chaos Engineering
Chaos engineering is the discipline of experimentally injecting failures into a system in order to build confidence in the system's capability to withstand unexpected disruptions in production.
Goal
The goal of chaos engineering is to identify weaknesses and potential points of failure in software systems before they lead to outages, ensuring the system's resilience and reliability.
Context
As systems grow in complexity, the interconnectedness of components increases, and it becomes increasingly difficult to predict how they will behave under failure conditions. Chaos engineering provides a structured approach to understanding system behaviour under stress and identifying areas for improvement.
Chaos Test Types
| Type | Description | Examples |
|---|---|---|
| Fault Injection | This is the core technique of chaos engineering, where you deliberately introduce faults or errors into the system. Tools like Gremlin, Chaos Monkey (Netflix), or Hey!Chaos can be used to automate fault injection at various layers of the system (network, infrastructure, application). |
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| State Transitions | This approach focuses on manipulating the state of system components to trigger unexpected behaviours. |
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| Network Partitioning | This technique simulates network disruptions by isolating parts of the system from each other. This can expose issues with communication or distributed functionalities. |
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| Limit Testing | This approach involves pushing the system beyond its normal operating limits to identify potential bottlenecks or resource constraints. |
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| Lack of Observability: Failing to properly monitor system behaviour during experiments can prevent the identification of issues. | Overlooking Post-Experiment Analysis: Not conducting thorough analysis after experiments misses opportunities for learning and improvement. | Overly aggressive experiments: Conducting experiments that are too disruptive can lead to unnecessary risk and potential damage to the system. |