Datadog Learning Roadmap

Goal: From zero Datadog experience to production-ready observability engineering

Learning Phases

Phase 1: Datadog Basics (2-3 days)

•Agent architecture and deployment (Kubernetes DaemonSet, host, Docker)

•Metrics vs Logs vs APM traces — the three pillars

•Infrastructure List and Host Map navigation

•Datadog vs Prometheus+Grafana+ELK — the mapping mindset

Phase 2: Metrics, Dashboards, Monitors (3-4 days)

•Datadog Query Language syntax and metric queries

•Building dashboards with template variables

•Monitors (alerts) — thresholds, notification routing

•SLO tracking — UI-configured and Terraform-as-code

Phase 3: APM and Distributed Tracing (4-5 days)

•Auto-instrumentation vs manual instrumentation

•Service Map and dependency visualization

•Log-trace correlation (dd.trace_id/dd.span_id injection)

•Continuous Profiler

Phase 4: Production Operations (1 week)

•Cost control — trace sampling, log exclusion filters, cardinality management

•Security — PII scrubbing, API/App key scoping

•Meta-monitoring — alerting on the Agent's own health

•Terraform-managed SLOs and Monitors as code

Phase 5: Migration and Team Onboarding (ongoing)

•Mapping an existing Prometheus/Grafana/ELK stack to Datadog equivalents

•Building the PromQL → Datadog query translation habit

•Onboarding a team used to open-source tooling

Job Roles This Enables

•Observability/Monitoring Engineer

•Site Reliability Engineer

•DevOps Engineer (monitoring-focused)

•Platform Engineer

Target Certifications

See certification.md in this guide for Datadog's current certification track — treat any specific exam details there as (needs verification — recheck against current source) given how frequently vendor certification programs change.

How to Use This Roadmap

1.Work through phases in order — APM (Phase 3) assumes the metrics/dashboards mental model from Phase 2 is already solid

2.Use the free trial for hands-on practice — this technology doesn't have a separate Labs tab, so the Fundamentals/Intermediate/Advanced code blocks and the Installation section's verification steps are the hands-on material

3.If you already run Prometheus/Grafana/ELK in production, treat Phase 1's Module 04 mapping table as your fastest on-ramp, not optional review

4.Build the portfolio projects in projects.md after Phase 3 to cement APM and cost-control skills specifically

5.Use the Interview Prep section's PSR-format answers to practice explaining tradeoffs (cost vs. operational overhead), not just features

Prerequisites

See prerequisites.md in this section for what you should know before starting.

Revision Notes

Total time: 3-4 weeks (part-time)
Datadog's biggest learning curve isn't the tool itself — it's translating
observability concepts you may already know from Prometheus/Grafana/ELK
into Datadog's specific query syntax and UI layout
Track a real cost lever early (sampling rate, log exclusion) — cost
control is a recurring interview topic, not just an operational afterthought

Datadog — Roadmap