Datadog Core Skills for Developers

Modern software teams juggle a fragmented toolchain: code lives in one place, CI/CD pipeline data in another, and production telemetry somewhere else entirely. Developers context-switch between tools, which slows delivery and makes it harder to catch problems before they reach customers. This workshop demonstrates how Datadog unifies the software delivery life cycle—from pre-release checks to production troubleshooting—in a single platform.

In this hands-on workshop, you'll play the role of a developer shipping a new discount feature for an e-commerce app. Before release, you'll use Datadog to confirm the feature meets your team's production requirements: verifying code coverage, finding and fixing a flaky test, and setting up an APM latency monitor to catch regressions. You'll use Datadog's Software Catalog, APM traces, and Continuous Profiler to investigate an alert, tracking down and fixing the issue.

Finally, when a new error surfaces in production, you'll use Bits Code, Datadog's AI-powered coding assistant, to investigate the root cause directly from an APM trace, generate a fix, and open a pull request, building an audit trail from incident to resolution.

By the end of the workshop, you'll have a practical, end-to-end blueprint for using Datadog across the software delivery life cycle, from pre-release quality checks to production debugging and AI-assisted remediation.

A GitHub account is required for the hands-on lab.