Guides

Walkthroughs for observability, incident response, and AI-assisted operations.

AIOps fundamentals

Start with what AI can do for operations, and where judgment still matters.

Make metrics, logs, and traces work together.

Build an incident response practice that learns.

Instructions, examples, and implementation notes.

Use a curated notebook to compare runbooks and incident evidence, while keeping citations, freshness, and operational authority in view.

February 12, 20264 min read

A design guide for an incident assistant that handles duplicate events, partial failures, and reviewed AI summaries across tools.

April 6, 20254 min read

A reusable prompt pattern for incident analysis, with checks for missing facts, unsafe recommendations, and unsupported certainty.

March 31, 20253 min read

Use Python logging to capture useful context without swallowing errors, duplicating exceptions, or exposing sensitive data.

September 30, 20233 min read

Validate the source data, preserve useful denominators, and distinguish a failed collection from a real zero before aggregating metrics.

September 30, 20234 min read

Build a ticket-routing evaluation around real ownership, uncertain cases, and correction cost. Start with an honest baseline before adding a model.

September 28, 20233 min read