A five-stage operating model — Define, Prevent, Observe, Validate, and Improve — for keeping multi-account cloud environments aligned with architectural intent.
Learn about graph databases by building an F1 teammate network from real Formula 1 data and using Cypher to connect Max Verstappen to Juan Manuel Fangio.
Build self-healing SQL pipelines where LLMs propose repairs while deterministic validation, guardrails, and execution controls protect production systems.
A hands-on guide to Microsoft Foundry Document Intelligence SDK for extracting text, structured fields, and document data from PDFs for RAG and AI pipelines.
Learn how to test POST API requests in Playwright with TypeScript using static JSON objects and arrays, JSON.stringify(), JSON files, and the Faker library.
A graph models customers, products, categories and tags, making collaborative filtering, co-purchase analysis, content similarity, and trending queries graph traversals.
Temporal owns coordination, LangGraph owns agent state, and external systems own outcomes. Stable IDs and idempotency keep retries and recovery consistent.
Cloud-native platforms need more than mature infrastructure. Learn how shared standards, platform engineering, and self-service can reduce delivery friction at scale.
Six techniques to cut LLM API costs by up to 90%: prompt caching, model routing, batch processing, and more. (Includes a pip-installable Python library.)
To maintain sub-second search freshness, logistics systems must actively manage eventual consistency across Kafka ordering, search indexing, and cache invalidation.
Learn how forgotten internet-facing assets expand your attack surface and how continuous asset discovery, inventory, and ownership can reduce security risks.
Edge inference thrives on-device for real-time, private AI. Advances in hardware and compression cut latency and costs, pushing AI away from the cloud.