Chaos Engineering & Resilience
Principles and practices for injecting failures, validating recovery, and designing resilient serverless systems.
Simple Explanation
What it is
Chaos engineering is controlled failure testing. You break things on purpose to prove your system can recover.
Why we need it
If you only test when everything is healthy, you do not know how the system behaves during real incidents.
Benefits
- Higher confidence in recovery plans.
- Fewer surprises during outages.
- Stronger resilience under stress.
Tradeoffs
- Requires careful guardrails to avoid real damage.
- Needs time to plan and analyze experiments.
Real-world examples (architecture only)
- Disable a region -> Verify failover.
- Slow database -> Confirm graceful degradation.
What This Lesson Covers
- Chaos principles and safety guardrails
- Experiment design and blast radius control
- Resilience patterns for serverless systems
- Recovery metrics and success criteria
- Game days and continuous learning
Core Principles
-
Start small
- Single service, limited impact
- Test during low-traffic windows
-
Define success
- Error rate, latency, and recovery time
-
Control blast radius
- Feature flags, canary traffic, quick rollback
Python Example: Controlled Fault Injection
import os
import random
def handler(event, context):
if os.getenv("CHAOS_MODE") == "true":
# Inject failure 10% of the time during tests.
if random.random() < 0.1:
raise RuntimeError("Injected failure for chaos test")
return {"status": "ok"}
Resilience Patterns to Validate
- Timeouts and retries with backoff
- Circuit breakers for unstable dependencies
- Idempotency for repeatable actions
- Graceful degradation for non-critical paths
Project
Design a chaos experiment for a critical workflow.
Deliverables:
- Experiment plan and safety guardrails
- Success metrics (RTO, error rate, latency)
- Rollback and recovery steps
Email your work to maarifaarchitect@gmail.com.
References
- AWS Fault Injection Simulator: https://aws.amazon.com/fis/
- Google Cloud Resilience Testing: https://cloud.google.com/architecture/reliability
- Principles of Chaos Engineering: https://principlesofchaos.org/