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Chaos Engineering Overview

Chaos Engineering is the practice of proactively introducing faults into your applications or infrastructure and test the resilience of business services. Developers, QA teams, Performance test teams and SREs run chaos experiments to measure the resilience of the systems and find the weaknesses in that process.

Harness Chaos Engineering provides end-to-end tooling to resilience testing via the chaos engineering principles. Enterprises can build highly scalable resilience testing practice with Harness because of the following capabilities:

  • Experiments - faults and probes
  • ChaosGuard for governance
  • Delegates - scalability
  • Connectors for integration
  • Resilience management - Resilience scores, coverages, weaknesses and mitigation plans
  • AI Powered: Recommendations

In addition, the Harness platform provides the required enterprise capabilities like RBACs, SSO, logs and auditing making the entire solution scalable and easy to implement.

For information about general Harness Platform concepts and features, go to Harness Platform key concepts.

Why Harness Chaos Engineering?​

Enterprise-Ready Platform​

  • Scalable Architecture: Handle experiments across large, distributed systems
  • Security First: Enterprise-grade security and compliance features
  • Multi-Cloud Support: Works across AWS, Azure, GCP, and on-premises infrastructure

Comprehensive Fault Library​

  • Infrastructure Faults: CPU, memory, network, and disk-level failures
  • Application Faults: Service failures, latency injection, and error simulation
  • Platform Faults: Kubernetes and cloud provider-specific experiments

Advanced Automation​

  • Scheduled Experiments: Automate chaos testing as part of your regular operations
  • CI/CD Integration: Embed resilience testing in your deployment pipelines
  • Intelligent Rollback: Automatic experiment termination when safety thresholds are breached

Key Benefits​

Improved System Reliability​

  • Identify single points of failure before they impact users
  • Validate disaster recovery procedures and failover mechanisms
  • Build confidence in system architecture and design decisions

Reduced Mean Time to Recovery (MTTR)​

  • Train teams to handle failures through controlled practice
  • Improve incident response procedures and runbooks
  • Build muscle memory for handling production incidents

Cost Optimization​

  • Prevent costly outages through proactive testing
  • Optimize resource allocation and capacity planning
  • Reduce over-provisioning by understanding actual failure modes

How It Works​

  1. Hypothesis Formation: Define what you expect to happen during the experiment
  2. Experiment Design: Choose appropriate faults and target systems
  3. Safety Measures: Set up monitoring, alerts, and rollback mechanisms
  4. Execution: Run the experiment in a controlled manner
  5. Analysis: Review results and system behavior
  6. Learning: Document findings and improve system resilience

Getting Started​

Ready to begin your chaos engineering journey? Explore the following sections:

Next Steps​

Once you understand the basics, you can:

  • Explore our Key Concepts section for deeper technical knowledge
  • Follow our Tutorials for hands-on experience
  • Check out Integrations to connect with your existing tools