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Datadog — From Zero to Hero

A standalone, developer-focused course on Datadog — the unified observability platform. From the Agent and unified service tagging to metrics, log management, APM, and the correlation model that ties them into one view per service — taught through real Agent config, DogStatsD, and Terraform. Every layered detail (ingestion vs. retention sampling, exclusion filters vs. archives) is verified against current docs.

Foundations

What Datadog is, the Agent and integrations, unified service tagging, and a tour of the UI. Start →

Infrastructure & Metrics

Agent-collected metrics, custom metrics via DogStatsD, Metrics without Limits, and dashboards. Measure →

Log Management

Collection and processing pipelines, indexes vs. exclusion filters, log-based metrics, and archives. Collect →

APM & Distributed Tracing

Traces, spans and the service map, ingestion vs. retention sampling, trace metrics, and profiling. Trace →

Correlating Logs, Traces & Metrics

Trace-log injection, unified service tagging in practice, the Service Catalog, and RUM context. Connect →

Monitors, Alerting & SLOs

Monitor types and thresholds, composite monitors, SLO error budgets and burn rates, and Synthetics. Alert →

Production & Ecosystem

Datadog as code with Terraform, cost governance, security basics, and a production rollout checklist. Ship it →

Layered pipelines, not one dial

Metrics, logs, and traces are separate pipelines, each with its own ingestion, retention, and cost controls — this course teaches every layer instead of treating “sampling” or “retention” as one setting.

Current behavior, verified

Written against current Datadog behavior and checked against the official docs via context7 — including the split between log ingestion and indexing, and APM’s ingestion-vs-retention-filter distinction that a lot of tutorials collapse into one.

One tag triple, three pipelines

Not just “add some tags” but the full picture: how env/service/version — unified service tagging — let you pivot between a service’s metrics, traces, and logs instead of hunting through three disconnected tools.

Diagrams that explain

The Agent’s data paths, the log pipeline from intake to index, APM’s ingestion/retention split, and the SLO error-budget model as theme-aware Mermaid diagrams. Bilingual (English / ไทย) with saved quiz progress.