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Datadog: from discovery to expertise

Complete Datadog course: agent and integrations, metrics and unified tagging, logs and cost control, APM and OpenTelemetry, monitors, SLOs and configuration as code with Terraform.

12 chapters26 lessonsEN
At your pace, through practice.

By the end of this course you will be able to

  • Install the agent and enable integrations
  • Use metrics and unified tagging while keeping cardinality under control
  • Structure logs and control their cost
  • Instrument APM and link logs and traces
  • Manage monitors, SLOs and dashboards as code
  • Deploy Datadog on Kubernetes with the Operator
  • Measure user experience with RUM and Synthetics
  • Manage incidents, security, costs and governance

🎯 Level : Intermediate👥 Who it is for : SREs, DevOps engineers, developers and operators who use or are evaluating Datadog

LEARNING PATH

Course curriculum

0Course overview1 lesson
  1. Assessment quizQuiz · ⏱ 10 min
1Introduction and architecture2 lessons

Platform, sites, keys and data model.

  1. Datadog at a glanceArticle · ⏱ 3 min
  2. Datadog platform architectureArticle · ⏱ 4 min
2Agent, integrations and Kubernetes4 lessons

Installation, integrations, Operator and Autodiscovery.

  1. Agent and integrationsArticle · ⏱ 7 min
  2. Lab: Install the Datadog agent and enable an integrationHands-on lab · ⏱ 35 min · Level 2/5
  3. Datadog on KubernetesArticle · ⏱ 7 min
  4. Lab: Monitor a Kubernetes cluster with the Datadog OperatorHands-on lab · ⏱ 45 min · Level 3/5
3Metrics, tags and dashboards4 lessons

Types, aggregations, cardinality and visualisation.

  1. Metrics and tagsArticle · ⏱ 5 min
  2. Advanced metrics and cardinalityArticle · ⏱ 3 min
  3. Lab: Custom metrics with DogStatsD and a dashboardHands-on lab · ⏱ 40 min · Level 3/5
  4. Dashboards and notebooksArticle · ⏱ 4 min
4Logs4 lessons

Pipelines, indexes, costs and sensitive data.

  1. Logs in DatadogArticle · ⏱ 5 min
  2. Advanced logs: indexes, Flex and archivesArticle · ⏱ 4 min
  3. Lab: Log pipeline, facets and volume controlHands-on lab · ⏱ 45 min · Level 3/5
  4. Lab: Python APM and log-trace correlationHands-on lab · ⏱ 45 min · Level 3/5
5APM and OpenTelemetry2 lessons

Traces, sampling, profiler and catalog.

  1. APM and OpenTelemetryArticle · ⏱ 4 min
  2. Advanced APM: sampling and profilerArticle · ⏱ 4 min
6User experience2 lessons

RUM and Synthetic Monitoring.

  1. RUM and Synthetic MonitoringArticle · ⏱ 4 min
  2. Lab: Synthetic tests with Terraform and CIHands-on lab · ⏱ 35 min · Level 3/5
7Advanced infrastructure1 lesson

Network, cloud and databases.

  1. Network, cloud and databasesArticle · ⏱ 4 min
8Security1 lesson

Cloud SIEM, Cloud Security and application protection.

  1. Security with DatadogArticle · ⏱ 3 min
9Monitors, SLOs, incidents and as code3 lessons

Alerting, incident management and automation.

  1. Monitors, SLOs and TerraformArticle · ⏱ 6 min
  2. Incidents and automationArticle · ⏱ 3 min
  3. Final Lab: Monitors and SLOs in TerraformHands-on lab · ⏱ 50 min · Level 3/5
10Costs and governance1 lesson

Usage, attribution, RBAC and tags.

  1. Costs and governanceArticle · ⏱ 3 min
11Best practices1 lesson

Recommended practices to run the product in production.

  1. Datadog best practicesArticle · ⏱ 4 min

LEARN BY DOING

Use cases & applications

Turnkey observability

Infrastructure, logs and APM in a few hours.

Keeping the bill under control

Logs, custom metrics and traces under control.

Diagnosing an incident

Go from an alert to the trace and the logs.

Governing configuration

Monitors and SLOs in Terraform.

What next?

Dynatrace: From Discovery to ExpertiseOpenTelemetry: From Discovery to ExpertiseSRE in practice: SLIs, SLOs and error budgets

Frequently asked questions

Do I need a paid account to follow the course?

No: the 14-day free trial is enough for all the labs.

Does Datadog support OpenTelemetry?

Yes, the agent receives OTLP and Datadog converts standard attributes into tags.

How do I keep the bill from spiralling?

Control metric cardinality, filter and sample logs, and track usage with dedicated monitors.

Datadog or Dynatrace?

Both are complete SaaS platforms; Datadog focuses on flexibility and its ecosystem of integrations, Dynatrace on automation and causal AI. See also the Dynatrace course.