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How to build CI/CD observability at scale
GitLab leverages Prometheus, Grafana, and custom pipeline exporters to achieve scalable CI/CD observability, which helps optimize pipeline performance, job efficiency, and infrastructure capacity planning for its enterprise self-managed environments.
What: GitLab's approach to CI/CD observability involves collecting metrics from pipelines using Prometheus, visualizing them with Grafana, and employing custom exporters. This setup enables monitoring job efficiency, identifying infrastructure bottlenecks, and performing capacity planning to ensure optimal performance for large-scale, self-managed instances.
Why it matters: The emphasis on using established open-source tools like Prometheus and Grafana for CI/CD observability at scale demonstrates a practical, extensible strategy for managing the performance and cost of complex development pipelines in enterprise environments.
Takeaway: If you manage self-managed GitLab CI/CD, consider integrating Prometheus and Grafana with pipeline exporters to gain deeper insights into your pipeline performance and resource utilization.
Decoder
- CI/CD (Continuous Integration/Continuous Delivery): A methodology for frequent, automated code changes, building, testing, and deployment.
- Observability: The ability to understand the internal states of a system by examining its external outputs (logs, metrics, traces).
- Prometheus: An open-source monitoring system with a time series database.
- Grafana: An open-source platform for monitoring and observability, often used to visualize data from Prometheus.
Original article
CI/CD optimization for GitLab relies on observability using Prometheus, Grafana, and pipeline exporters to measure pipeline performance, job efficiency, and infrastructure bottlenecks, enabling scalable visibility, deployment optimization, and capacity planning for enterprise self-managed environments.
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