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Series · 4 chapters · ~27 min total

Agents explained for cloud engineers: what agents actually are, MCP, and when an agent beats a script

Define what an agent really is (policy + LLM + memory + tools), how it differs from scripts and microservices, and where it fits in modern Azure architectures. Set foundations for the rest of the series.

Start with Part 1 →

Part 1 · 7 min readChapter 1 — Agents, not magic: a cloud engineer’s mental modelDefine what an agent really is (policy + LLM + memory + tools), how it differs from scripts and microservices, and where it fits in modern Azure architectures. Set foundations for the rest of the series.

Part 2 · 6 min readChapter 2 — MCP in practice: wiring agents to real infrastructure safelyA practical tour of Model Context Protocol (MCP): what it is, how MCP servers expose tools/resources, and how to use MCP to give agents safe access to your Azure world. Sets up the plumbing you’ll reuse in later chapters.

Part 3 · 7 min readChapter 3 — Build it: a production-ready Azure agent with real toolsStep-by-step: stand up an agent using Azure AI Foundry and wire it to MCP-exposed tools running on Azure Functions/Container Apps, with API Management, Managed Identity, and Application Insights. You’ll finish with a deployable reference.

Part 4 · 7 min readChapter 4 — When an agent beats a script (and when it doesn’t)A decision framework with real examples: where agents shine (ambiguous, multi-tool, human-in-the-loop) and where scripts win (deterministic, low-latency, strict SLAs). Wrap up the series with operational playbooks and rollout patterns.