A practical guide to API chaos engineering for resilient APIs: principles, experiments, tooling, metrics, and CI/CD automation with examples.
Design and automate safe API canary deployments with traffic shaping, metrics, rollback, and real-world configs for gateways, meshes, and CI/CD.
A practical guide to API consumer analytics: what to track, how to instrument, and how to turn raw API calls into product and revenue insights.
A practical blueprint of safety patterns, architecture, and policies to keep agentic AI reliable, secure, and aligned in production.
A practical blueprint for building scalable, safe AI support chatbots—from NLU and RAG to orchestration, guardrails, and observability.
A practical guide to structured API logging and observability: schemas, tracing, metrics, correlation IDs, pipelines, and cost-efficient practices.
