Eric Metaj
Mark Azer
Developers and SREs who rely on GitLab to develop their services often face significant friction when troubleshooting errors or fixing issues that degrade code quality. To understand the context of a problem, they resort to tab-hopping between observability tools and GitLab, connecting stack traces, spans, and profiles back to the right files and commits. At the same time, many teams lack the visibility to detect security vulnerabilities, infrastructure misconfigurations, and flaky tests early in the software development lifecycle. This often results in fixes that cost much more than they would have if the issues had been discovered and addressed earlier.
We’re excited to announce the general availability of our [GitLab Source Code integration](https://docs.data…
Eric Metaj
Mark Azer
Developers and SREs who rely on GitLab to develop their services often face significant friction when troubleshooting errors or fixing issues that degrade code quality. To understand the context of a problem, they resort to tab-hopping between observability tools and GitLab, connecting stack traces, spans, and profiles back to the right files and commits. At the same time, many teams lack the visibility to detect security vulnerabilities, infrastructure misconfigurations, and flaky tests early in the software development lifecycle. This often results in fixes that cost much more than they would have if the issues had been discovered and addressed earlier.
We’re excited to announce the general availability of our GitLab Source Code integration. By connecting your GitLab repositories to Datadog, you can bring rich source code context directly into your observability workflows and shift key insights left into everyday development. This integration unifies your source code with Datadog’s broader developer ecosystem, enhancing Datadog APM, CI Visibility, Code Security, Test Optimization, and other Datadog tools you use to observe modern applications.
In this post, we’ll look at how the GitLab Source Code integration helps you:
- Gain immediate visibility into code health and security
- Accelerate troubleshooting with code-aware APM
- Automate code reviews and shift left with Merge Request feedback
When you connect your GitLab.com or self-managed instance to Datadog, the GitLab Source Code integration can immediately analyze your repositories for vulnerabilities, code quality issues, and infrastructure-as-code misconfigurations. Because it connects to your repositories directly, you can start detecting these problems earlier and with less manual effort, without redesigning or instrumenting your CI pipelines.
From there, you can review findings in Datadog with direct links back to the relevant files and lines in GitLab. This gives security, platform, and development teams a shared view of code health across services and environments, helping them quickly understand where issues originate and which repositories and services to prioritize.
Accelerate troubleshooting with code-aware APM
With the GitLab Source Code integration enabled, APM surfaces inline code snippets directly inside Datadog Error Tracking, Live Debugger, Continuous Profiler, and more. When an error or performance issue appears, APM shows GitLab code snippets that match stack traces or hot paths without requiring you to search for filenames and functions in GitLab manually.
With this context provided, APM users no longer need to jump between tools to understand failures. They can follow a trace to a representative error, inspect the associated code right in Datadog, and then jump straight to the corresponding file in GitLab. This helps teams identify root causes faster and move directly from detection to making the right code change.
Automate code reviews and shift left with merge request feedback
The GitLab Source Code integration also helps you catch issues before they reach production by posting actionable comments on GitLab merge requests (MRs). When combined with CI Visibility, Code Security, Code Coverage, and Test Optimization, Datadog can flag risky or insecure changes in the diff and add targeted feedback where it is most useful alongside the code under review.
The automated MR comments encourage earlier detection of problems such as flaky tests, regressions in coverage, and new vulnerabilities, while reducing back-and-forth review cycles. Reviewers and authors can determine whether a change is ready to merge based on concrete telemetry data, then follow links from the comments back to detailed test runs or security findings in Datadog when deeper investigation is needed. In certain cases, Datadog can help resolve issues by suggesting fixes that can be applied directly in the MR interface, further reducing the context-switching needed to complete remediation.
Get started with the GitLab Source Code integration
The GitLab Source Code integration brings GitLab repositories into Datadog, giving your teams a single, code-aware view across APM, CI Visibility, Code Security, Test Optimization, and more. By connecting to your GitLab projects, you can analyze code health, debug incidents faster with inline code snippets, and surface automated feedback directly in merge requests so that problems are addressed before they impact users.
To get started, install the GitLab Source Code integration from the Datadog Integrations page and connect your GitLab.com or self-managed instance. For more information, see the GitLab Source Code integration documentation and the Datadog Source Code Integration guide. And if you’re new to Datadog, you can sign up for a 14-day free trial.