Technical deep-dives, tutorials, and insights on AIOps, Kubernetes, and DevOps automation.
The average Kubernetes incident takes 45 minutes to resolve. 80% of that time is diagnosis, not fixing. Here's how AI-powered root-cause analysis cuts MTTR to under 5 minutes.
A step-by-step incident response playbook for Kubernetes. From alert to resolution: triage, diagnosis, fix, and post-mortem — with the exact kubectl commands you need.
Kubernetes can heal itself — if you configure it correctly. These 5 patterns (Liveness Probes, PDB, HPA, Resource Limits, Readiness Probes) reduce incidents by up to 60%.
Auto-remediation means AI diagnoses the issue AND ships a validated fix. Here's how it works: from root-cause analysis to auto-generated pull requests with kubectl dry-run, Helm, and Terraform validation.
How much do Kubernetes incidents actually cost your team? We break down engineer time, MTTR, tool costs, and opportunity cost — with a formula you can plug your own numbers into.
OpenTelemetry is the new standard for traces, metrics, and logs. Here's how to set up OTel in your Kubernetes cluster in under 10 minutes — no vendor lock-in.
SaaS observability tools send your cluster data to someone else's cloud. Self-hosted AI with BYOK keeps everything on your infrastructure. Here's why that matters — and what it costs.
Rule-based alerts create noise. AIOps uses ML and LLMs to cluster incidents, find root causes, and deliver human-readable summaries. Here's the before/after with real numbers.