Chaos Engineering

Chaos Engineering is like a fire drill for your software—you break things on purpose to make sure they don’t break when it matters most

Chaos Engineering

Chaos Engineering is a proactive discipline in software reliability that involves intentionally injecting controlled failures into systems to uncover weaknesses before they cause real-world outages. By simulating disruptions—such as server crashes, network latency, or dependency failures—teams can observe how their systems respond under stress and validate whether they behave as expected.

Cours Overview

Trainer

Professionals

Schedule

8.00 PM - 10.00 PM

Module 1: Chaos Fundamentals

Start with the core philosophy and lifecycle of Chaos Engineering, including key terminologies and its importance for distributed systems.

  • Introduction to Chaos Engineering
  • Principles & Philosophy
  • History, Resilience, Fault Injection, Blast Radius
  • System Complexity & Failure Modes
  • Chaos Lifecycle: Hypothesis → Experiment → Learn → Improve
  • Benefits for Cloud-Native & Distributed Systems

Module 2: Tooling & Integration

Explore leading chaos tools and configure them across various environments with integrated observability setups.

  • Chaos Mesh, Gremlin, LitmusChaos, AWS FIS Overview
  • Installing & Configuring in Kubernetes/Cloud/Hybrid
  • Observability Stack: Prometheus, Grafana, ELK, Jaeger
  • Safe Experiment Environments (Staging vs Production)
  • CI/CD Pipeline Integration

Module 3: Experiment Design

Learn how to identify risks and design targeted chaos experiments that validate system behavior under failure.

  • Identifying Critical Workflows & Dependencies
  • Hypothesis Creation & Controlled Experiment Design
  • Fault Injection Types: Latency, Pod Kill, CPU/Memory Stress, DNS Failures, Service Blackhole
  • Metrics & KPIs for Success
  • Executing & Documenting Chaos Experiments

Module 4: Resilience Patterns

Analyze experiment outcomes and reinforce systems with proven resilience strategies and postmortem practices.

  • Root Cause Analysis & Learning Capture
  • Circuit Breakers, Retries, Bulkheads, Rate Limiting
  • Postmortem Documentation Practices
  • SLO/SLA Alignment & Business Impact Assessment
  • Continuous Resilience Improvement

Module 5: Advanced Chaos Practices

Move chaos into production responsibly, automate recovery, and introduce AI/ML-powered anomaly detection.

  • Chaos in Production & Progressive Rollouts
  • Blast Radius Management & Experiment Safety
  • Self-Healing Systems & Automated Chaos
  • Predictive Analysis & AI/ML Integration
  • Chaos in Serverless & Edge Computing
  • Shift-Left Chaos: Early Lifecycle Introduction

Module 6: Final Project & Graduation

Apply all concepts in a full-scale chaos engineering project with peer reviews, certification, and presentation.

  • End-to-End Chaos Project Execution
  • Case Studies & Success Stories
  • Real-Time Reviews & Expert Feedback
  • Certification Preparation & Final Assessment
  • Final Presentation & Knowledge Sharing
  • Graduation Ceremony