By completing this course, learners will:

• Understand the core philosophy of Chaos Engineering.

• Plan and execute chaos experiments.

• Apply chaos practices in Kubernetes, containers, and cloud platforms.

• Integrate chaos with monitoring and alerting systems.

• Build a culture of reliability and resilience in engineering teams.

Course Syllabus

Module 1: Introduction to Chaos Engineering

• What is Chaos Engineering?

• History and evolution (Netflix’s Chaos Monkey)

• Benefits and challenges

Module 2: Principles & Methodology

• The Chaos Engineering process

• Defining steady state hypotheses

• Designing safe chaos experiments

Module 3: Chaos Tools Overview

• Chaos Monkey

• Gremlin

• LitmusChaos

• Other open-source tools

Module 4: Failure Injection Scenarios

• CPU and memory exhaustion

• Network latency and outages

• Service crashes and dependency failures

Module 5: Chaos in Kubernetes

• LitmusChaos setup in Kubernetes clusters

• Pod deletion, node failure, and resource stress tests

• Observing Kubernetes workloads under chaos

Module 6: Observability & Monitoring

• Integrating chaos with Prometheus and Grafana

• Logs, traces, and metrics correlation

• Alerting during chaos experiments

Module 7: Chaos in Cloud Environments

• Running chaos on AWS, Azure, GCP

• Simulating regional outages

• Cloud-native failure testing strategies

Module 8: Automating Chaos

• Integrating chaos into CI/CD pipelines

• GitOps-driven chaos experiments

• Continuous resilience testing

Module 9: Real-World Projects

• Microservices e-commerce chaos testing

• Kubernetes service resilience validation

• Cloud outage simulation and recovery

Module 10: Best Practices & Culture

• Running safe chaos experiments

• Communicating results to stakeholders

• Building a reliability-first culture

Learners will receive a Certificate of Completion from Uplatz, validating expertise in Chaos Engineering, reliability testing, and resilience-building practices. This certificate demonstrates readiness for roles in DevOps, SRE, and cloud infrastructure engineering.

Chaos Engineering skills open career paths in:

• Site Reliability Engineer (SRE)

• DevOps Engineer (Resilience & Observability)

• Cloud Infrastructure Engineer

• Reliability Architect

• Platform Engineer

With organizations prioritizing uptime, fault tolerance, and customer trust, Chaos Engineering expertise is increasingly sought-after.

1. What is Chaos Engineering?
   It is the practice of introducing controlled failures to test system resilience and reliability.

2. What is the role of a steady state hypothesis?
   It defines the expected normal behavior of the system before chaos experiments.

3. What tools are used in Chaos Engineering?
   Popular tools include Chaos Monkey, Gremlin, and LitmusChaos.

4. What is the difference between Chaos Monkey and Gremlin?
   Chaos Monkey is Netflix’s open-source tool for random instance termination, while Gremlin provides a commercial platform with broader failure scenarios.

5. What types of failures can be simulated?
   CPU spikes, memory leaks, network outages, pod crashes, and cloud service failures.

6. How is Chaos Engineering applied in Kubernetes?
   By using tools like LitmusChaos to inject failures into pods, nodes, and workloads.

7. How does observability support Chaos Engineering?
   Metrics, logs, and traces help measure system response and recovery during chaos.

8. What is the difference between load testing and chaos testing?
   Load testing measures performance under stress, while chaos testing validates resilience under failures.

9. Can Chaos Engineering be used in production?
   Yes, but only with careful planning, safety mechanisms, and monitoring.

10. Why is Chaos Engineering important in microservices?
    Microservices are distributed and failure-prone; chaos tests uncover weaknesses before real incidents occur.