This document provides an overview of chaos engineering, including what it is, how it differs from testing, how to design chaos experiments, and what chaos lambda is. Specifically, it explains that chaos engineering involves intentionally introducing failures into systems to test their resilience and identify weaknesses, unlike testing which checks for known issues. It also outlines the steps to design chaos experiments and describes chaos lambda as an open source tool from the BBC to simulate EC2 instance failures in auto scaling groups.

1. Chaos Engineering
Anshul Patel

2. What and Why Chaos Engineering?
● In IT, it(no puns intended) began at Netflix.
● Murphy’s law.
● Builds confidence in overall distributed systems to withstand turbulent &
unexpected conditions.
● Highlights weakness of the complex system proactively.
● Minimal downtime -> Less SLA breaches -> Less revenue loss.
● Improves the resilience of the system. Key areas:
○ Infrastructure Failures
○ Network Failures
○ Application Failures

3. How Chaos Engineering differs from Testing?
● In testing, assertions are made.
● Assertions are typically binary, whether property is correct or not.
● Testing breaks the system in preconceived way.
● Chaos Engineering doesn’t test known properties, it tests hypothesis.
● Chaos Engineering generates new knowledge.
○ Examples:
■ Simulating failure of entire AZ, region, datacenter.
■ Injecting latencies between services.
■ Forcing system clocks out of sync.

4. Designing Chaos Experiments
● Identify the steady state of the system.
● Pick a hypothesis.
● Choose the scope.
● Identify the operational metrics.
● Notify concerned members.
● Run the experiment.
● Analyze the results.
● Increase the scope.
● Automate.

5. What is Chaos Lambda?
● Open sourced by BBC.
● EC2 instances are volatile(99.99% SLA).
● AWS recommends to place EC2 instance under Autoscaling groups.
● Chaos Lambda simulates the failure of EC2 instance in Autoscaling group(s).

6. How it works?
● Schedule
○ Default Value: cron(0 10-16 ? * MON-FRI *)
○ Possible Values: cron(0 10-16 ? * MON-FRI *)
● Default Probability
○ Default Value: 0.166
○ Possible Values: 0.0 - 1.0
● Regions
○ Default Value: Current Region
○ Possible Values: List of Regions

7. Demo

8. Thank You & QA
Reference: https://github.com/dastergon/awesome-chaos-engineering