Chaos Engineering

Chaos Engineering involves observing how a system behaves as experiments are ran against the application/system to simulate errors, outages and other unexpected scenarios. It is a disciplined approach that helps organisations gain confidence in the reliability and resilience of their Cloud Native architecture.

Cloud Resliliency Challenges

By simulating real world disruptions, teams can validate their systems’ ability to withstand and recover from failures, thereby resolving the following common challenges:

• Unanticipated Failures: Without deliberate testing, latent vulnerabilities may remain undetected until they cause significant disruptions.
• Dynamic Environments: The ephemeral nature of cloud resources necessitates continuous validation of system resilience amidst constant changes.
• Complexity of Distributed Systems: Modern Cloud Native applications often consist of numerous interconnected services, making it challenging to predict how a system will behave when one or more services are failing.

Chaos Engineering Benefits

1. Improved Fault Tolerance & System Reliability: Identifying and addressing potential points of failure ensure services remain operational and performant, even during unexpected disruptions.
2. Enhanced Team Confidence: Empowering engineering teams with insights into system behaviour and valuable information that can be used to resolve incidents.
3. Enhanced Observability & Monitoring: Observability and monitoring tools will be continuously be validated as errors, outages and other unexpected scenarios are simulated. Any gaps in the observability and monitoring tools identified during testing must be addressed.

Robust and Resilient Cloud Native Systems.

Through the strategic application of Chaos Engineering, organisations can achieve a deeper understanding of their systems’ behaviours under stress, leading to the development of more resilient and dependable Cloud Native applications.

Implementation Steps

1. Establish a Baseline of System Performance

Understand normal operating metrics to identify deviations during experiments.

Chaos Engineering - Implementation Details:

• Monitor key metrics by utilising observability tools (e.g. Prometheus, Grafana, or Datadog) to track performance indicators such as latency, throughput, and error rates.
• Define normal behaviour in your documentation, including the expected system responses under standard conditions to serve as a reference point.

2. Formulate Hypotheses on Potential Failures

Predict how systems should behave under specific failure scenarios.

Implementation Details:

• Identify critical components to determine which services or resources are vital to operations.
• Anticipate failure modes by considering all possible disruptions, such as network latency, service crashes, or resource exhaustion.

3. Design & Execute Controlled Experiments

Introduce failures in a controlled manner to observe system responses.

Implementation Details:

• Utilise specifically designed chaos engineering tools (e.g. LitmusChaos) to orchestrate and manage experiments within Kubernetes environments.
• Limit the blast radius by starting with small scale tests to minimise any potential impact, then gradually expand the scope as confidence grows.

4. Analyse Results & Implement Improvements

Assess outcomes to identify weaknesses and enhance system resilience.

Implementation Details:

• Review system behaviour, and compare the observed responses to your expected outcomes to pinpoint any discrepancies.
• Review the data provided by your observability and monitoring tools during the experiment to identify any missing data the tools should or could have provided during simulated scenario.
• Prioritise your remediation efforts to address the identified vulnerabilities based on their potential impact on operations.

5. Automate & Integrate Continuous Testing

Embed Chaos Engineering practices into regular development and operational workflows.

Implementation Details:

• Incorporate chaos engineering into your CI/CD Pipelines to automate testing procedures alongside existing processes.
• Encourage teams to regularly engage in chaos testing to maintain an ongoing focus on platform reliability and foster a culture of continuous improvement.