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