Most Datadog problems are configuration problems wearing a disguise. The agent that stopped reporting, the bill that doubled, the alert that never fired: trace them back and you usually find a default nobody revisited. Setting the platform up deliberately, once, removes a whole category of future incidents.
Installation first: the Datadog Agent on Linux and Windows, the Agent under Docker Compose, and the DD_ environment variables that configure containerised agents. Then configuration proper: datadog.yaml basics and the broader set of configuration best practices we apply in every environment we run. When an agent misbehaves, it is usually permissions.
Tagging deserves special attention: it is the layer every other feature depends on, from dashboards to cost attribution, and retrofitting a tag strategy is far harder than starting with one.
For programmatic control, the API is the route: the Datadog API from Python, real-time ingestion through the APIs, and the practical business of handling and monitoring rate limits. Governance closes the loop: user roles, access control and the Audit Trail are what make the estate defensible when the compliance questions arrive. New to the platform entirely? Start with the beginner's guide and the training resources worth your time.