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Why DNS failures, expired certificates, label selector mismatches, and network policy blocks cause more outages than packet loss — and how to debug them.
Why partial failures and latency cause more production incidents than crashes — cascading slowdowns, retry storms, and exhausted thread pools.
How to use LocalStack, Moto, and Azurite to test cloud failure scenarios locally — emulate S3, DynamoDB, SQS, and Azure Storage without cloud costs.
How IAM propagation delays, API throttling, and global service outages cascade through cloud control planes — and how to design resilient systems around them.
How to debug CrashLoopBackOff in Kubernetes: the six real causes — startup failures, OOMKills, bad probes, image pulls, volumes, and rollouts.
Pods stuck Pending in Kubernetes? Learn the 7 scheduler failures — from insufficient CPU to affinity deadlocks — and how to diagnose them fast.
Test API throttling, RBAC denials, and admission webhook failures locally — without a real cluster. Faster, cheaper, and more targeted than chaos engineering.
A practical taxonomy of Kubernetes failure modes — control plane, workload, config, networking, storage — from real production incidents and benchmark data.
Learn how to set SLOs, define SLIs from user journeys, and run error budget policies that actually shape engineering decisions — without chasing impossible nines.
64% of outages come from config and change errors, not dead disks. Learn the semantic/physical failure split and why you can simulate most of them locally.
A failure catalog enumerates the failure modes that actually take down production — control plane, dependencies, config, observability — so you can test each one.
Chaos experiments test the dramatic failures that rarely happen. A failure catalog targets the config, dependency, and control-plane bugs that actually take you down.
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