Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
A practical guide to AIOps and self-healing infrastructure: the maturity ladder from alert to autonomous remediation, observability as the foundation, anomaly detection, Kubernetes-native self-healing, an operator-driven remediation loop, agentic SRE, and the guardrails that keep automation safe.
The observability market is huge and the pricing is a minefield. This is the map to the tools that matter, what each is best at, and how to avoid a runaway bill.
A practitioner's guide to tracing, cost tracking, and evaluating LLM apps in production with Langfuse, Helicone, Arize Phoenix, and LangSmith.
One tool is built to answer questions you didn't know you had. The other watches everything at once. Here is how they actually differ in practice.
Datadog bills climb quietly until finance forwards the invoice. Here's the playbook we run to cut spend hard while keeping every signal that matters.
OTel promises no lock-in, vendor agents promise zero-config depth. Here is where each one actually earns its keep once you run it in production.
The bill arrives three weeks late. By then the runaway logging pipeline has already burned $9,000. Here is how we catch spikes in hours, not weeks.
Datadog does everything and bills you for all of it. SigNoz covers the core APM story on your own ClickHouse. Here's when the trade is worth it.
Edge code runs in hundreds of PoPs, lives for milliseconds, and gives you no shell. Here's how we get logs, traces, and metrics out of it anyway.
New Relic's pricing swings and feature gaps push teams to shop around. Here's a field-tested look at seven alternatives, who each one fits, and how to move.
Grafana pulls metrics from anywhere, Kibana lives and dies with Elasticsearch. Here's how we pick between them without ending up running both by accident.
Datadog's bill has a way of tripling the quarter you actually start using it. Here are eight alternatives we've run in production and what each one costs you.
