Access Metrics

Harbor exposes some key metrics needed for operators and administrators to monitor how your Harbor instance is running in real time. Observability is a key feature for operating a service in production and using this data you can identify abnormal statuses and make informed decisions to fix issues when an error occurs. Harbor exposes metrics using the Prometheus data model so you can easily start scraping your Harbor instance’s metrics using Prometheus.

In Harbor v2.2 and later you are able to enable metrics in your Harbor configuration file. Harbor metrics are available at <harbor_instance>:<metrics_port>/<metrics_path> based on your configured values.

Harbor metrics show data related to

  • Runtime information from the GO library
  • Performance metrics about all API requests in core
  • Number of requests in flight in core
  • Metrics provided by the docker distribution itself
  • Some data related to business logic which already exist in the Harbor database

Metrics are exposed by several Harbor components: exporter, core, jobservice, and registry. In addition to runtime and performance data, these components also expose Harbor specific metrics. The following sections list the available Harbor metrics.

Harbor Exporter Metrics

The exporter component metrics relate to your Harbor instance configuration and collects some data from the Harbor database. Metrics are available at <harbor_instance>:<metrics_port>/<metrics_path>.

Metrics exposed by the Harbor Exporter
Name Description Labels (Values) Metric type
harbor_project_total Total number of public and private projects public (true,false) gauge
harbor_project_repo_total Total number of repositories in a project public (true,false), project_name gauge
harbor_project_member_total Total number of members in a project project_name gauge
harbor_project_quota_usage_byte Total used resources of a project project_name gauge
harbor_project_quota_byte Quota set in a project project_name gauge
harbor_artifact_pulled Number of images pulled in a project project_name gauge
harbor_project_artifact_total Total number of artifacts type in a project artifact_type , project_name, public (true,false) gauge
harbor_health Current status of Harbor gauge
harbor_system_info Information about your Harbor instance auth_mode (db_auth, ldap_auth, uaa_auth, http_auth, oidc_auth), harbor_version, self_registration(true,false) gauge
harbor_up Running status of Harbor components component (chartmuseum, core, database, jobservice, portal, redis, registry, registryctl, trivy) gauge
harbor_task_queue_size The total number of tasks per type in the queue instance, job, type gauge
harbor_task_queue_latency How long ago the next job to be processed was enqueued per type instance, job, type gauge
harbor_task_scheduled_total Number of scheduled tasks instance, job gauge
harbor_task_concurrency Total number of concurrent tasks per type on a pool instance, job, pool, type gauge

Harbor Core Metrics

The following are metrics pulled from the Harbor core pod and are available at <harbor_instance>:<metrics_port>/<metrics_path>?comp=core.

Metrics exposed by Harbor Core
Name Description Labels (Values) Metric type
harbor_core_http_inflight_requests The total number of requests operation (values from operationId in Harbor API. Some legacy endpoints do not have an operationId, so the label value is unknown) gauge
harbor_core_http_request_duration_seconds The time duration of the requests method (GET, POST, HEAD, PATCH, PUT), operation (values from operationId in Harbor API. Some legacy endpoints do not have an operationId, so the label value is unknown), quantile summary
harbor_core_http_request_total The total number of requests method (GET, POST, HEAD, PATCH, PUT), operation (values from operationId in Harbor API. Some legacy endpoints do not have an operationId, so the label value is unknown) counter

Registry Metrics

The following are metrics pulled from the Docker distribution and are available at <harbor_instance>:<metrics_port>/<metrics_path>?comp=registry.

Metrics exposed by Harbor Core
Name Description Labels (Values) Metric type
registry_http_in_flight_requests The in-flight HTTP requests handler gauge
registry_http_request_duration_seconds The HTTP request latencies in seconds handler, method (GET, POST, HEAD, PATCH, PUT), le histogram
registry_http_request_size_bytes The HTTP request sizes in bytes. handler, le histogram

Harbor Jobservice metrics

The following are metrics pulled from the Harbor Jobservice and are available at <harbor_instance>:<metrics_port>/<metrics_path>?comp=jobservice.

Metrics exposed by Harbor Jobservice
Name Description Labels (Values) Metric type
harbor_jobservice_info The information of Jobservice instance, job, node, pool, workers gauge
harbor_jobservice_task_total The number of processed tasks per job type instance, job, status, type counter
harbor_jobservice_task_process_time_seconds The duration of the task processing time instance, job, quantile, status, type summary

Scraping Metrics with Prometheus

To begin accessing your Harbor instance’s metrics with Prometheus,

  1. Enable exposing metrics in your harbor.yml configuration file and set the port and path for metrics to be exposed on. Also see more about reconfiguring your Harbor instance.

  2. Set up a Prometheus server, see the Prometheus documentation for more information on installing.

  3. Configure your Prometheus config file to scrape Harbor metrics exposed at your configured port and path. Below is an example scrape config, see the Prometheus documentation for all available scrape configuration options.

      scrape_configs:
    
        - job_name: 'harbor-exporter'
          scrape_interval: 20s
          static_configs:
            # Scrape metrics from the Harbor exporter component
            - targets: ['<harbor_instance>:<metrics_port>']
    
        - job_name: 'harbor-core'
          scrape_interval: 20s
          params:
            # Scrape metrics from the Harbor core component
            comp: ['core']
          static_configs:
            - targets: ['<harbor_instance>:<metrics_port>']
    
        - job_name: 'harbor-registry'
          scrape_interval: 20s
          params:
            # Scrape metrics from the Harbor registry component
            comp: ['registry']
          static_configs:
            - targets: ['<harbor_instance>:<metrics_port>']
    
        - job_name: 'harbor-jobservice'
          scrape_interval: 20s
          params:
            # Scrape metrics from the Harbor jobservice component
            comp: ['jobservice']
          static_configs:
            - targets: ['<harbor_instance>:<metrics_port>']
    
  4. Once you have configured your Prometheus server to collect your Harbor metrics, you can use Grafana to visualize your data. An example Grafana dashboard is available in the Harbor repo to help you get started visualizing Harbor metrics.

From a Kubernetes cluster

You can also use Prometheus to collect metrics from a Harbor instance deployed in your Kubernetes cluster. You should already have installed Prometheus and set up to pull metrics from your cluster.

  1. Create a ServiceMonitor in Prometheus for Harbor.

    apiVersion: monitoring.coreos.com/v1
    kind: ServiceMonitor
    metadata:
      name: harbor
      labels:
        app: harbor
    spec:
      selector:
        matchLabels:
          app: harbor
      endpoints:
      - port: metrics
    
  2. Enable Harbor to expose metrics by updating your harbor-helm values.yaml file and set metrics.enabled to true. You can also edit the port and path the metrics are exposed on by updating the available harbor-helm chart configuration options for metrics.

Prometheus should now show your Harbor instance’s metrics.