Grafana and GitLab Introduce Serverless CI/CD Observability Integration

Write for InfoQ

In a move to streamline development workflows, Daniel Fritzgerald of GrafanaLabs has published a new open-source solution that links GitLab CI/CD events into Grafana's observability stack via a serverless architecture. The integration enables teams to channel GitLab webhooks, such as pushes, merge requests, and pipeline completions, directly into Grafana Cloud Logs (built on Grafana Loki) for real-time visibility and correlation between deploy events and performance metrics.

The core challenge addressed is the fragmentation between source control, CI/CD tooling, and observability systems. Many teams struggle with disconnected dashboards: developers may check GitLab for pipeline status; operations review logs in Grafana; and neither view is tied directly to underlying metrics or deployments, causing slower incident response and manual correlation. The GitLab-Grafana integration closes that gap by funneling structured CI/CD events into a unified log stream, enabling teams to monitor pipeline health, deployment frequencies, and correlate changes with system metrics.

From a technical standpoint, the solution relies on a lightweight serverless function (such as an AWS Lambda) that receives GitLab webhooks via an API Gateway endpoint, formats the payload as structured logs, and ships them into Grafana Cloud Logs. Users can then use LogQL queries to analyze CI/CD activity by project, deployment success rates, or build times. Furthermore, these logs can be combined with application performance data in Grafana dashboards, for example, seeing error rates plotted alongside specific deploys or code changes.

The introduction of this serverless observability pipeline effectively makes CI/CD telemetry first-class in monitoring platforms. Teams can now create alerts based on deployment trends (e.g., build failures, long pipeline times, reduced deployment cadence), visualize developer productivity and release velocity, and drive compliance or audit reporting on change-failure rates and deployment recovery times. Grafana notes that this style of integration reflects a broader shift toward unified visibility where code changes, metrics, logs, and traces operate as part of a single workflow.

For organizations seeking to adopt this model, compatible setups typically follow four steps: deploy the Lambda function with Grafana Cloud credentials, create an API endpoint for GitLab webhooks, configure GitLab to send events to that endpoint, and begin building dashboards in Grafana. With minimal code, reportedly around 69 lines of Python, teams can set up the integration in under 30 minutes, according to the blog post.

For those interested in this observability approach, here are some additional templates that can help achieve something similar and be utilized to showcase CI/CD observability, especially with GitLab + Prometheus:

GitLab CI Pipelines dashboard (ID: 10620): This dashboard visualizes metrics from GitLab's CI pipelines, using Prometheus as a data source. It includes panels for pipeline durations, success/fail counts, jobs metrics, etc.

Dashboard JSON from GitLab CI Pipelines Exporter: The gitlab-ci-pipelines-exporter project provides an example dashboard JSON, which you can import or customize.

GitLab Self-managed Grafana Dashboards repo: GitLab maintains a repository of sample dashboards (for GitLab metrics) that include performance, CI metrics, etc.

GitLab Runner Dashboard (ID: 21662): This dashboard focuses on runner metrics, which can complement pipeline dashboards by showing the health, concurrency, and performance of runner infrastructure.

One Reddit user described how they consume CI/CD pipeline events or deployment webhooks and feed them into Grafana Logs panels. For instance, they published a webhook service, used a Grafana data-source plugin, and showed GitLab pipeline events in Grafana logs.

Overall, this integration marks an advance in linking development workflows with observability tooling. By treating CI/CD events as structured logs and making them queryable alongside metrics and traces, teams gain a more holistic view of their software delivery lifecycle - reducing the time to detect issues, improving incident response, and aligning developer actions with operational outcomes.

Related Topics:

• DevOps
• Serverless
• Continuous Deployment
• GitLab
• Grafana
• Continuous Integration

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