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A typical deployment includes:\n*   **Pipeline Overview Dashboard:** A top-level view showing total pipeline runs, success/failure rates over time (as stacked bar or time-series charts), and average pipeline duration trends. Panels use color-coded status indicators (green for success, red for failure, amber for cancelled) so platform teams can spot degradation at a glance.\n*   **Job Performance Dashboard:** Drill-down panels showing individual job duration distributions (histogram), the top 10 slowest jobs by average duration, and job failure heatmaps by project and stage. This is where teams identify specific bottleneck jobs worth optimizing.\n*   **Runner & Infrastructure Dashboard:** Combines Node Exporter host metrics (CPU, memory, disk) with pipeline queue-time data to correlate infrastructure saturation with pipeline wait times. Useful for capacity planning decisions such as scaling runner pools or upgrading instance sizes.\n*   **Deployment Frequency Dashboard:** Tracks deployment count and deployment duration over time per environment, aligned with DORA metrics. Helps engineering leadership assess delivery throughput and environment drift (commits behind main).\n\nEach dashboard is provisioned automatically via Grafana's file-based provisioning, so it deploys consistently across environments. The dashboards can be further customized with Grafana variables to filter by project, ref/branch, or time range.\n\n![Solution architecture](https://res.cloudinary.com/about-gitlab-com/image/upload/v1777382608/Blog/Imported/blog-building-ci-cd-observability-stack-for-gitlab-self-managed/image1.png)\n\nThe solution requires two exporters:\n*   **Pipeline Exporter:** Collects CI/CD metrics via GitLab API (pipeline duration, job status, deployments)\n*   **Node Exporter:** Collects host-level metrics (CPU, memory, disk) for infrastructure correlation\n\n**Prerequisites:**\n*   GitLab Self-Managed Version 18.1+\n*   **Container orchestration platform:** A Kubernetes cluster (recommended for enterprise deployments) or a container runtime such as Docker/Podman for smaller scale or proof-of-concept environments. The primary deployment guide below targets Kubernetes; a Docker Compose alternative is provided in the appendix for local testing and evaluation\n*   GitLab Personal Access Token (**read_api** scope)\n\n## Kubernetes deployment (recommended)\nFor enterprise environments, deploy each component as a separate Deployment within a dedicated namespace. This approach integrates with existing cluster infrastructure, secrets management, and network policies.\n\n### 1. Create namespace and secret\n```bash\nkubectl create namespace gitlab-observability\n\n# Create the GitLab token secret (see Secrets Management section below\n# for enterprise-grade approaches using external secret operators)\nkubectl create secret generic gitlab-token \\\n  --from-literal=token=glpat-xxxxxxxxxxxx \\\n  -n gitlab-observability\n```\n\n\n### 2. Deploy the Pipeline Exporter\n```yaml\n# exporter-deployment.yaml\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: gitlab-ci-pipelines-exporter\n  namespace: gitlab-observability\nspec:\n  replicas: 1\n  selector:\n    matchLabels:\n      app: gitlab-ci-pipelines-exporter\n  template:\n    metadata:\n      labels:\n        app: gitlab-ci-pipelines-exporter\n    spec:\n      containers:\n        - name: exporter\n          image: mvisonneau/gitlab-ci-pipelines-exporter:latest\n          ports:\n            - containerPort: 8080\n          env:\n            - name: GCPE_GITLAB_TOKEN\n              valueFrom:\n                secretKeyRef:\n                  name: gitlab-token\n                  key: token\n            - name: GCPE_CONFIG\n              value: /etc/gcpe/config.yml\n          volumeMounts:\n            - name: config\n              mountPath: /etc/gcpe\n      volumes:\n        - name: config\n          configMap:\n            name: gcpe-config\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: gitlab-ci-pipelines-exporter\n  namespace: gitlab-observability\nspec:\n  selector:\n    app: gitlab-ci-pipelines-exporter\n  ports:\n    - port: 8080\n      targetPort: 8080\n```\n\n### 3. Deploy Node Exporter (DaemonSet)\n```yaml\n# node-exporter-daemonset.yaml\napiVersion: apps/v1\nkind: DaemonSet\nmetadata:\n  name: node-exporter\n  namespace: gitlab-observability\nspec:\n  selector:\n    matchLabels:\n      app: node-exporter\n  template:\n    metadata:\n      labels:\n        app: node-exporter\n    spec:\n      containers:\n        - name: node-exporter\n          image: prom/node-exporter:latest\n          ports:\n            - containerPort: 9100\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: node-exporter\n  namespace: gitlab-observability\nspec:\n  selector:\n    app: node-exporter\n  ports:\n    - port: 9100\n      targetPort: 9100\n```\n\n### 4. Deploy Prometheus\n```yaml\n# prometheus-deployment.yaml\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: prometheus\n  namespace: gitlab-observability\nspec:\n  replicas: 1\n  selector:\n    matchLabels:\n      app: prometheus\n  template:\n    metadata:\n      labels:\n        app: prometheus\n    spec:\n      containers:\n        - name: prometheus\n          image: prom/prometheus:latest\n          ports:\n            - containerPort: 9090\n          volumeMounts:\n            - name: config\n              mountPath: /etc/prometheus\n      volumes:\n        - name: config\n          configMap:\n            name: prometheus-config\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: prometheus\n  namespace: gitlab-observability\nspec:\n  selector:\n    app: prometheus\n  ports:\n    - port: 9090\n      targetPort: 9090\n```\n\n### 5. Deploy Grafana\nThe Grafana deployment below starts with authentication disabled (`GF_AUTH_ANONYMOUS_ENABLED: true`) for initial setup convenience.\n\n**This setting allows anyone with network access to view all dashboards without logging in.** For production deployments, remove this variable or set it to false and configure a proper authentication provider (LDAP, SAML/SSO, or OAuth) to restrict access to authorized users.\n```yaml\n# grafana-deployment.yaml\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: grafana\n  namespace: gitlab-observability\nspec:\n  replicas: 1\n  selector:\n    matchLabels:\n      app: grafana\n  template:\n    metadata:\n      labels:\n        app: grafana\n    spec:\n      containers:\n        - name: grafana\n          image: grafana/grafana:10.0.0\n          ports:\n            - containerPort: 3000\n          env:\n            # REMOVE or set to 'false' for production.\n            # When 'true', any user with network access can\n            # view dashboards without authentication.\n            - name: GF_AUTH_ANONYMOUS_ENABLED\n              value: 'true'\n          volumeMounts:\n            - name: dashboards-provider\n              mountPath: /etc/grafana/provisioning/dashboards\n            - name: datasources\n              mountPath: /etc/grafana/provisioning/datasources\n            - name: dashboards\n              mountPath: /var/lib/grafana/dashboards\n      volumes:\n        - name: dashboards-provider\n          configMap:\n            name: grafana-dashboards-provider\n        - name: datasources\n          configMap:\n            name: grafana-datasources\n        - name: dashboards\n          configMap:\n            name: grafana-dashboards\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: grafana\n  namespace: gitlab-observability\nspec:\n  selector:\n    app: grafana\n  ports:\n    - port: 3000\n      targetPort: 3000\n```\n\n### 6. Set network policy\nRestrict inter-pod traffic to only the required communication paths:\n```yaml\n# network-policy.yaml\napiVersion: networking.k8s.io/v1\nkind: NetworkPolicy\nmetadata:\n  name: observability-policy\n  namespace: gitlab-observability\nspec:\n  podSelector: {}\n  policyTypes:\n    - Ingress\n  ingress:\n    # Prometheus scrapes exporter and node-exporter\n    - from:\n        - podSelector:\n            matchLabels:\n              app: prometheus\n      ports:\n        - port: 8080\n        - port: 9100\n    # Grafana queries Prometheus\n    - from:\n        - podSelector:\n            matchLabels:\n              app: grafana\n      ports:\n        - port: 9090\n```\n\n### 7. Validate\n```bash\nkubectl get pods -n gitlab-observability\nkubectl port-forward svc/grafana 3000:3000 -n gitlab-observability\ncurl http://localhost:3000/api/health\n```\n\n## Configuration reference\n### Exporter configuration\n```yaml\n# gitlab-ci-pipelines-exporter.yml (ConfigMap: gcpe-config)\nlog:\n  level: info\ngitlab:\n  url: https://gitlab.your-domain.com\n  maximum_requests_per_second: 10\nproject_defaults:\n  pull:\n    pipeline:\n      jobs:\n        enabled: true\nwildcards:\n  - owner:\n      name: your-group-name\n      kind: group\n    archived: false\n```\n\n### Prometheus configuration\n```yaml\n# prometheus.yml (ConfigMap: prometheus-config)\nglobal:\n  scrape_interval: 15s\nscrape_configs:\n  - job_name: 'gitlab-ci-pipelines-exporter'\n    static_configs:\n      - targets: ['gitlab-ci-pipelines-exporter:8080']\n  - job_name: 'node-exporter'\n    static_configs:\n      - targets: ['node-exporter:9100']\n```\n\n### Grafana data sources\n```yaml\n# datasources.yml (ConfigMap: grafana-datasources)\napiVersion: 1\ndatasources:\n  - name: Prometheus\n    type: prometheus\n    access: proxy\n    url: http://prometheus:9090\n    isDefault: true\n# dashboards.yml (ConfigMap: grafana-dashboards-provider)\napiVersion: 1\nproviders:\n  - name: 'default'\n    folder: 'GitLab CI/CD'\n    type: file\n    options:\n      path: /var/lib/grafana/dashboards\n```\n\n## Key metrics\n### Pipeline Exporter metrics\n| Metric | Description |\n| :---- | :---- |\n| `gitlab_ci_pipeline_duration_seconds` | Pipeline execution time |\n| `gitlab_ci_pipeline_status` | Pipeline success/failure by project |\n| `gitlab_ci_pipeline_job_duration_seconds` | Individual job execution time |\n| `gitlab_ci_pipeline_job_status` | Job success/failure status |\n| `gitlab_ci_pipeline_job_artifact_size_bytes` | Artifact storage consumption |\n| `gitlab_ci_pipeline_coverage` | Code coverage percentage |\n| `gitlab_ci_environment_deployment_count` | Deployment frequency |\n| `gitlab_ci_environment_deployment_duration_seconds` | Deployment execution time |\n| `gitlab_ci_environment_behind_commits_count` | Environment drift from main |\n\n### Node Exporter metrics\n| Metric | Description |\n| :---- | :---- |\n| `node_cpu_seconds_total` | CPU utilization |\n| `node_memory_MemAvailable_bytes` | Available memory |\n| `node_filesystem_avail_bytes` | Disk space available |\n| `node_load1` | 1-minute load average |\n\n## Troubleshooting\n### Air-gapped Grafana plugin installation\nFor offline environments, install plugins manually. Example for Kubernetes:\n```bash\n# Copy plugin zip into the Grafana pod\nkubectl cp grafana-polystat-panel-2.1.16.zip \\\n  gitlab-observability/grafana-\u003Cpod-id>:/tmp/\n# Extract plugin\nkubectl exec -it -n gitlab-observability deploy/grafana -- \\\n  sh -c \"unzip /tmp/grafana-polystat-panel-2.1.16.zip -d /var/lib/grafana/plugins/\"\n# Restart Grafana pod\nkubectl rollout restart deployment/grafana -n gitlab-observability\n# Verify installation\nkubectl exec -it -n gitlab-observability deploy/grafana -- \\\n  ls -al /var/lib/grafana/plugins/\n```\n\n## Enterprise considerations\nFor regulated industries, ensure:\n*   **Token security:** Store GitLab Personal Access Tokens in a dedicated secrets manager rather than hardcoded in ConfigMaps. Enforce token rotation policies and limit scope to **read\\_api** only.\n*   **Network segmentation:** Deploy behind a reverse proxy with TLS termination. In Kubernetes, use an Ingress controller with automated certificate provisioning.\n*   **Authentication:** Configure Grafana with your organization's identity provider (SAML, LDAP, or OAuth/OIDC) to enforce role-based access control on dashboards.\n\n## Why GitLab?\nGitLab's API-first design enables custom observability solutions that complement native capabilities like Value Stream Analytics and DORA metrics. The open architecture allows organizations to integrate proven open-source tooling — like the gitlab-ci-pipelines-exporter — directly with their existing enterprise infrastructure, without disrupting established workflows.\n\nAs your observability maturity grows, GitLab's built-in Observability capabilities provide a natural next step — offering deeper, integrated visibility without additional tooling. Learn more about what's available natively in the platform for [GitLab Observability](https://docs.gitlab.com/operations/observability/observability/).\n",{"featured":10,"template":693,"slug":694},"BlogPost","how-to-build-ci-cd-observability-at-scale",{"title":686,"description":696,"authors":697,"heroImage":698,"date":699,"body":691,"category":9,"tags":700},"This practical guide to GitLab pipeline analytics helps self-managed users gain operational insights using Prometheus and Grafana.",[690],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1774465167/n5hlvrsrheadeccyr1oz.png","2026-04-28",[89,701,702],"product","tutorial",{},"/en-us/blog/how-to-build-ci-cd-observability-at-scale","seo:\n  config:\n    noIndex: false\n  title: How to build CI/CD observability at scale\n  description: This practical guide to GitLab pipeline analytics helps\n    self-managed users gain operational insights using Prometheus and Grafana.\ncontent:\n  title: How to build CI/CD observability at scale\n  description: This practical guide to GitLab pipeline analytics helps\n    self-managed users gain operational insights using Prometheus and Grafana.\n  authors:\n    - Paul Meresanu\n  heroImage: https://res.cloudinary.com/about-gitlab-com/image/upload/v1774465167/n5hlvrsrheadeccyr1oz.png\n  date: 2026-04-28\n  body: |\n    CI/CD optimization starts with visibility. Building a successful DevOps platform at enterprise scale **should include** understanding pipeline performance, job execution patterns, and quantifiable operational insights — especially for organizations running GitLab self-managed instances.\n\n    To help GitLab customers maximize their platform investments, we developed the GitLab CI/CD Observability solution as part of our Platform Excellence program, which transforms raw pipeline metrics into actionable operational insights.\n\n    A leading financial services organization partnered with GitLab's customer success architect to gain visibility into their GitLab self-managed deployment. Together, we implemented a containerized observability solution combining the open-source gitlab-ci-pipelines-exporter with enterprise-grade Prometheus and Grafana infrastructure.\n\n    In this article, you'll learn the challenges they faced managing pipelines at scale and how GitLab CI/CD Observability addressed them with a practical, end-to-end implementation.\n\n    ## The challenge: Measuring CI/CD performance\n    Before implementing any observability solution, define your measurement landscape:\n    *   **What metrics matter?** Pipeline duration, job success rates, queue times, runner utilization\n    *   **Who needs visibility?** Developers, DevOps engineers, platform teams, leadership\n    *   **What decisions will this drive?** Infrastructure investment, bottleneck remediation, capacity planning\n\n    ## Solution architecture: A full set of dashboards for observability\n    Once deployed, the observability stack provides a set of Grafana dashboards that give real-time and historical visibility into your CI/CD platform. A typical deployment includes:\n    *   **Pipeline Overview Dashboard:** A top-level view showing total pipeline runs, success/failure rates over time (as stacked bar or time-series charts), and average pipeline duration trends. Panels use color-coded status indicators (green for success, red for failure, amber for cancelled) so platform teams can spot degradation at a glance.\n    *   **Job Performance Dashboard:** Drill-down panels showing individual job duration distributions (histogram), the top 10 slowest jobs by average duration, and job failure heatmaps by project and stage. This is where teams identify specific bottleneck jobs worth optimizing.\n    *   **Runner & Infrastructure Dashboard:** Combines Node Exporter host metrics (CPU, memory, disk) with pipeline queue-time data to correlate infrastructure saturation with pipeline wait times. Useful for capacity planning decisions such as scaling runner pools or upgrading instance sizes.\n    *   **Deployment Frequency Dashboard:** Tracks deployment count and deployment duration over time per environment, aligned with DORA metrics. Helps engineering leadership assess delivery throughput and environment drift (commits behind main).\n\n    Each dashboard is provisioned automatically via Grafana's file-based provisioning, so it deploys consistently across environments. The dashboards can be further customized with Grafana variables to filter by project, ref/branch, or time range.\n\n    ![Solution architecture](https://res.cloudinary.com/about-gitlab-com/image/upload/v1777382608/Blog/Imported/blog-building-ci-cd-observability-stack-for-gitlab-self-managed/image1.png)\n\n    The solution requires two exporters:\n    *   **Pipeline Exporter:** Collects CI/CD metrics via GitLab API (pipeline duration, job status, deployments)\n    *   **Node Exporter:** Collects host-level metrics (CPU, memory, disk) for infrastructure correlation\n\n    **Prerequisites:**\n    *   GitLab Self-Managed Version 18.1+\n    *   **Container orchestration platform:** A Kubernetes cluster (recommended for enterprise deployments) or a container runtime such as Docker/Podman for smaller scale or proof-of-concept environments. The primary deployment guide below targets Kubernetes; a Docker Compose alternative is provided in the appendix for local testing and evaluation\n    *   GitLab Personal Access Token (**read_api** scope)\n\n    ## Kubernetes deployment (recommended)\n    For enterprise environments, deploy each component as a separate Deployment within a dedicated namespace. This approach integrates with existing cluster infrastructure, secrets management, and network policies.\n\n    ### 1. Create namespace and secret\n    ```bash\n    kubectl create namespace gitlab-observability\n\n    # Create the GitLab token secret (see Secrets Management section below\n    # for enterprise-grade approaches using external secret operators)\n    kubectl create secret generic gitlab-token \\\n      --from-literal=token=glpat-xxxxxxxxxxxx \\\n      -n gitlab-observability\n    ```\n\n\n    ### 2. Deploy the Pipeline Exporter\n    ```yaml\n    # exporter-deployment.yaml\n    apiVersion: apps/v1\n    kind: Deployment\n    metadata:\n      name: gitlab-ci-pipelines-exporter\n      namespace: gitlab-observability\n    spec:\n      replicas: 1\n      selector:\n        matchLabels:\n          app: gitlab-ci-pipelines-exporter\n      template:\n        metadata:\n          labels:\n            app: gitlab-ci-pipelines-exporter\n        spec:\n          containers:\n            - name: exporter\n              image: mvisonneau/gitlab-ci-pipelines-exporter:latest\n              ports:\n                - containerPort: 8080\n              env:\n                - name: GCPE_GITLAB_TOKEN\n                  valueFrom:\n                    secretKeyRef:\n                      name: gitlab-token\n                      key: token\n                - name: GCPE_CONFIG\n                  value: /etc/gcpe/config.yml\n              volumeMounts:\n                - name: config\n                  mountPath: /etc/gcpe\n          volumes:\n            - name: config\n              configMap:\n                name: gcpe-config\n    ---\n    apiVersion: v1\n    kind: Service\n    metadata:\n      name: gitlab-ci-pipelines-exporter\n      namespace: gitlab-observability\n    spec:\n      selector:\n        app: gitlab-ci-pipelines-exporter\n      ports:\n        - port: 8080\n          targetPort: 8080\n    ```\n\n    ### 3. Deploy Node Exporter (DaemonSet)\n    ```yaml\n    # node-exporter-daemonset.yaml\n    apiVersion: apps/v1\n    kind: DaemonSet\n    metadata:\n      name: node-exporter\n      namespace: gitlab-observability\n    spec:\n      selector:\n        matchLabels:\n          app: node-exporter\n      template:\n        metadata:\n          labels:\n            app: node-exporter\n        spec:\n          containers:\n            - name: node-exporter\n              image: prom/node-exporter:latest\n              ports:\n                - containerPort: 9100\n    ---\n    apiVersion: v1\n    kind: Service\n    metadata:\n      name: node-exporter\n      namespace: gitlab-observability\n    spec:\n      selector:\n        app: node-exporter\n      ports:\n        - port: 9100\n          targetPort: 9100\n    ```\n\n    ### 4. Deploy Prometheus\n    ```yaml\n    # prometheus-deployment.yaml\n    apiVersion: apps/v1\n    kind: Deployment\n    metadata:\n      name: prometheus\n      namespace: gitlab-observability\n    spec:\n      replicas: 1\n      selector:\n        matchLabels:\n          app: prometheus\n      template:\n        metadata:\n          labels:\n            app: prometheus\n        spec:\n          containers:\n            - name: prometheus\n              image: prom/prometheus:latest\n              ports:\n                - containerPort: 9090\n              volumeMounts:\n                - name: config\n                  mountPath: /etc/prometheus\n          volumes:\n            - name: config\n              configMap:\n                name: prometheus-config\n    ---\n    apiVersion: v1\n    kind: Service\n    metadata:\n      name: prometheus\n      namespace: gitlab-observability\n    spec:\n      selector:\n        app: prometheus\n      ports:\n        - port: 9090\n          targetPort: 9090\n    ```\n\n    ### 5. Deploy Grafana\n    The Grafana deployment below starts with authentication disabled (`GF_AUTH_ANONYMOUS_ENABLED: true`) for initial setup convenience.\n\n    **This setting allows anyone with network access to view all dashboards without logging in.** For production deployments, remove this variable or set it to false and configure a proper authentication provider (LDAP, SAML/SSO, or OAuth) to restrict access to authorized users.\n    ```yaml\n    # grafana-deployment.yaml\n    apiVersion: apps/v1\n    kind: Deployment\n    metadata:\n      name: grafana\n      namespace: gitlab-observability\n    spec:\n      replicas: 1\n      selector:\n        matchLabels:\n          app: grafana\n      template:\n        metadata:\n          labels:\n            app: grafana\n        spec:\n          containers:\n            - name: grafana\n              image: grafana/grafana:10.0.0\n              ports:\n                - containerPort: 3000\n              env:\n                # REMOVE or set to 'false' for production.\n                # When 'true', any user with network access can\n                # view dashboards without authentication.\n                - name: GF_AUTH_ANONYMOUS_ENABLED\n                  value: 'true'\n              volumeMounts:\n                - name: dashboards-provider\n                  mountPath: /etc/grafana/provisioning/dashboards\n                - name: datasources\n                  mountPath: /etc/grafana/provisioning/datasources\n                - name: dashboards\n                  mountPath: /var/lib/grafana/dashboards\n          volumes:\n            - name: dashboards-provider\n              configMap:\n                name: grafana-dashboards-provider\n            - name: datasources\n              configMap:\n                name: grafana-datasources\n            - name: dashboards\n              configMap:\n                name: grafana-dashboards\n    ---\n    apiVersion: v1\n    kind: Service\n    metadata:\n      name: grafana\n      namespace: gitlab-observability\n    spec:\n      selector:\n        app: grafana\n      ports:\n        - port: 3000\n          targetPort: 3000\n    ```\n\n    ### 6. Set network policy\n    Restrict inter-pod traffic to only the required communication paths:\n    ```yaml\n    # network-policy.yaml\n    apiVersion: networking.k8s.io/v1\n    kind: NetworkPolicy\n    metadata:\n      name: observability-policy\n      namespace: gitlab-observability\n    spec:\n      podSelector: {}\n      policyTypes:\n        - Ingress\n      ingress:\n        # Prometheus scrapes exporter and node-exporter\n        - from:\n            - podSelector:\n                matchLabels:\n                  app: prometheus\n          ports:\n            - port: 8080\n            - port: 9100\n        # Grafana queries Prometheus\n        - from:\n            - podSelector:\n                matchLabels:\n                  app: grafana\n          ports:\n            - port: 9090\n    ```\n\n    ### 7. Validate\n    ```bash\n    kubectl get pods -n gitlab-observability\n    kubectl port-forward svc/grafana 3000:3000 -n gitlab-observability\n    curl http://localhost:3000/api/health\n    ```\n\n    ## Configuration reference\n    ### Exporter configuration\n    ```yaml\n    # gitlab-ci-pipelines-exporter.yml (ConfigMap: gcpe-config)\n    log:\n      level: info\n    gitlab:\n      url: https://gitlab.your-domain.com\n      maximum_requests_per_second: 10\n    project_defaults:\n      pull:\n        pipeline:\n          jobs:\n            enabled: true\n    wildcards:\n      - owner:\n          name: your-group-name\n          kind: group\n        archived: false\n    ```\n\n    ### Prometheus configuration\n    ```yaml\n    # prometheus.yml (ConfigMap: prometheus-config)\n    global:\n      scrape_interval: 15s\n    scrape_configs:\n      - job_name: 'gitlab-ci-pipelines-exporter'\n        static_configs:\n          - targets: ['gitlab-ci-pipelines-exporter:8080']\n      - job_name: 'node-exporter'\n        static_configs:\n          - targets: ['node-exporter:9100']\n    ```\n\n    ### Grafana data sources\n    ```yaml\n    # datasources.yml (ConfigMap: grafana-datasources)\n    apiVersion: 1\n    datasources:\n      - name: Prometheus\n        type: prometheus\n        access: proxy\n        url: http://prometheus:9090\n        isDefault: true\n    # dashboards.yml (ConfigMap: grafana-dashboards-provider)\n    apiVersion: 1\n    providers:\n      - name: 'default'\n        folder: 'GitLab CI/CD'\n        type: file\n        options:\n          path: /var/lib/grafana/dashboards\n    ```\n\n    ## Key metrics\n    ### Pipeline Exporter metrics\n    | Metric | Description |\n    | :---- | :---- |\n    | `gitlab_ci_pipeline_duration_seconds` | Pipeline execution time |\n    | `gitlab_ci_pipeline_status` | Pipeline success/failure by project |\n    | `gitlab_ci_pipeline_job_duration_seconds` | Individual job execution time |\n    | `gitlab_ci_pipeline_job_status` | Job success/failure status |\n    | `gitlab_ci_pipeline_job_artifact_size_bytes` | Artifact storage consumption |\n    | `gitlab_ci_pipeline_coverage` | Code coverage percentage |\n    | `gitlab_ci_environment_deployment_count` | Deployment frequency |\n    | `gitlab_ci_environment_deployment_duration_seconds` | Deployment execution time |\n    | `gitlab_ci_environment_behind_commits_count` | Environment drift from main |\n\n    ### Node Exporter metrics\n    | Metric | Description |\n    | :---- | :---- |\n    | `node_cpu_seconds_total` | CPU utilization |\n    | `node_memory_MemAvailable_bytes` | Available memory |\n    | `node_filesystem_avail_bytes` | Disk space available |\n    | `node_load1` | 1-minute load average |\n\n    ## Troubleshooting\n    ### Air-gapped Grafana plugin installation\n    For offline environments, install plugins manually. Example for Kubernetes:\n    ```bash\n    # Copy plugin zip into the Grafana pod\n    kubectl cp grafana-polystat-panel-2.1.16.zip \\\n      gitlab-observability/grafana-\u003Cpod-id>:/tmp/\n    # Extract plugin\n    kubectl exec -it -n gitlab-observability deploy/grafana -- \\\n      sh -c \"unzip /tmp/grafana-polystat-panel-2.1.16.zip -d /var/lib/grafana/plugins/\"\n    # Restart Grafana pod\n    kubectl rollout restart deployment/grafana -n gitlab-observability\n    # Verify installation\n    kubectl exec -it -n gitlab-observability deploy/grafana -- \\\n      ls -al /var/lib/grafana/plugins/\n    ```\n\n    ## Enterprise considerations\n    For regulated industries, ensure:\n    *   **Token security:** Store GitLab Personal Access Tokens in a dedicated secrets manager rather than hardcoded in ConfigMaps. Enforce token rotation policies and limit scope to **read\\_api** only.\n    *   **Network segmentation:** Deploy behind a reverse proxy with TLS termination. In Kubernetes, use an Ingress controller with automated certificate provisioning.\n    *   **Authentication:** Configure Grafana with your organization's identity provider (SAML, LDAP, or OAuth/OIDC) to enforce role-based access control on dashboards.\n\n    ## Why GitLab?\n    GitLab's API-first design enables custom observability solutions that complement native capabilities like Value Stream Analytics and DORA metrics. The open architecture allows organizations to integrate proven open-source tooling — like the gitlab-ci-pipelines-exporter — directly with their existing enterprise infrastructure, without disrupting established workflows.\n\n    As your observability maturity grows, GitLab's built-in Observability capabilities provide a natural next step — offering deeper, integrated visibility without additional tooling. Learn more about what's available natively in the platform for [GitLab Observability](https://docs.gitlab.com/operations/observability/observability/).\n  category: engineering\n  tags:\n    - CI/CD\n    - product\n    - tutorial\nconfig:\n  featured: false\n  template: BlogPost\n  slug: how-to-build-ci-cd-observability-at-scale\n",{"config":707,"title":686,"description":696},{"noIndex":10},"en-us/blog/how-to-build-ci-cd-observability-at-scale",[531,701,702],[89,701,702],"bNaT8snsF96LPUH0nRZRNHDLiuh8ypxL3hg7dMqvmJk",[713,722,731,740,748,758,767,777,786],{"content":714,"config":720},{"title":715,"heroImage":716,"category":9,"description":717,"authors":718},"5 ways GitLab pipeline logic solves real engineering problems","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772721753/frfsm1qfscwrmsyzj1qn.png","Learn how to scale CI/CD with composable patterns for monorepos, microservices, environments, and governance.",[719],"Omid Khan",{"externalUrl":-1,"slug":721},"5-ways-gitlab-pipeline-logic-solves-real-engineering-problems",{"content":723,"config":729},{"title":724,"heroImage":725,"category":9,"description":726,"authors":727},"How to use GitLab Container Virtual Registry with Docker Hardened Images","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772111172/mwhgbjawn62kymfwrhle.png","Learn how to simplify container image management with this step-by-step guide.",[728],"Tim Rizzi",{"externalUrl":-1,"slug":730},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":732,"config":738},{"title":733,"heroImage":734,"category":9,"description":735,"authors":736},"How IIT Bombay students are coding the future with GitLab","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099013/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2814%29_6VTUA8mUhOZNDaRVNPeKwl_1750099012960.png","At GitLab, we often talk about how software accelerates innovation. But sometimes, you have to step away from the Zoom calls and stand in a crowded university hall to remember why we do this.",[737],"Nick Veenhof",{"externalUrl":-1,"slug":739},"how-iit-bombay-students-code-future-with-gitlab",{"content":741,"config":746},{"title":742,"heroImage":743,"category":9,"description":744,"authors":745},"Artois University elevates research and curriculum with GitLab Ultimate for Education","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099203/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2820%29_2bJGC5ZP3WheoqzlLT05C5_1750099203484.png","Artois University's CRIL leveraged the GitLab for Education program to gain free access to Ultimate, transforming advanced research and computer science curricula.",[737],{"externalUrl":-1,"slug":747},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":749,"config":756},{"title":750,"heroImage":751,"category":9,"description":752,"authors":753},"Guide: Migrate from Azure DevOps to GitLab","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png","Learn how to carry out the full migration from Azure DevOps to GitLab using GitLab Professional Services migration tools — from planning and execution to post-migration follow-up tasks.",[754,755],"Evgeny Rudinsky","Michael Leopard",{"externalUrl":-1,"slug":757},"migration-from-azure-devops-to-gitlab",{"content":759,"config":765},{"title":760,"heroImage":761,"category":9,"description":762,"authors":763},"How we deploy the largest GitLab instance 12 times daily","https://res.cloudinary.com/about-gitlab-com/image/upload/v1764108112/tyntnsy3xotlmehtnfkb.png","Take a deep technical dive into GitLab.com's deployment pipeline, including progressive rollouts, Canary strategies, database migrations, and multiversion compatibility.",[764],"John Skarbek",{"externalUrl":-1,"slug":766},"continuously-deploying-the-largest-gitlab-instance",{"content":768,"config":775},{"title":769,"heroImage":770,"category":9,"description":771,"authors":772},"Variable and artifact sharing in GitLab parent-child pipelines","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664198/Blog/Hero%20Images/Self-Hosted_1800x945.png","Learn how to simplify complex CI/CD pipelines with these best practices for sharing data in more modular pipeline setups. ",[773,774],"William Arias","Daniel Helfand",{"externalUrl":-1,"slug":776},"variable-and-artifact-sharing-in-gitlab-parent-child-pipelines",{"content":778,"config":784},{"title":779,"heroImage":780,"category":9,"description":781,"authors":782},"How we built a structured Streamlit Application Framework in Snowflake","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097447/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%284%29_3LZkiDjHLjhqEkvOvBsVKp_1750097447404.png","Want to transform development from chaos to compliance? Learn how we implemented governance early on rather than retrofitting when maintenance costs climb exponentially.",[783],"Radovan Bacovic",{"externalUrl":-1,"slug":785},"how-we-built-a-structured-streamlit-application-framework-in-snowflake",{"content":787,"config":793},{"title":788,"heroImage":743,"category":9,"description":789,"authors":790},"How GitLab transforms embedded systems testing cycles","Discover how managed lifecycle environments streamline and automate virtual testing, delivering rapid feedback without environment sprawl or cost overruns.",[791,792],"Matt DeLaney","Darwin Sanoy",{"externalUrl":-1,"slug":794},"how-gitlab-transforms-embedded-systems-testing-cycles",1777493594035]