Available metrics

Debusine supports Prometheus monitoring using the /api/1.0/open-metrics/ endpoint. By default this is available to anyone who can access the instance, and will reveal information such as valid scope names and queue sizes; administrators whose instances have significant commercially-sensitive activity may wish to restrict public access to that endpoint in their front-end load balancer configuration.

Note that the metric names below may have an additional suffix depending on the metric type and the library being used to parse the raw metrics output: counter metrics have a _total suffix, while histogram metrics have a _bucket suffix.

Database metrics

The following metrics measure various kinds of objects in Debusine’s database:

Name	Labels	Type	Description
artifacts	category, scope	gauge	number of artifacts of each category in each scope
assets	category, scope	gauge	number of assets of each category in each scope
collections	category, scope	gauge	number of collections of each category in each scope
file_store_max_size	backend, name	gauge	configured maximum sizes of file stores
file_store_size	backend, name	gauge	total sizes of file stores
groups	ephemeral, scope	gauge	number of groups in each scope; ephemeral groups will be garbage-collected when empty
tokens	enabled, user, worker	gauge	number of tokens associated with users and workers
users	active	gauge	number of users, excluding the system user
user_activity	scope	histogram	number of users who have created a workflow in each scope over the last N days
user_identities	active, issuer	gauge	number of user single-sign-on identities by issuer
user_identities_activity	issuer, scope	histogram	number of single-sign-on identities by issuer for users who have created a workflow in each scope over the last N days
work_requests	task_type, task_name, scope, status, build_architecture, backend	gauge	number of work requests broken down in various ways
workers	connected, busy, worker_type, worker_pool, native_architecture, architecture_*	gauge	number of workers broken down in various ways
worker_pool_runtime	worker_pool	gauge	time in seconds spent running tasks per worker pool
workflow_templates	task_name, scope	gauge	number of workflow templates for each task name in each scope
workspaces	private, expires, scope	gauge	number of workspaces in each scope

Operational metrics

Debusine exports many metrics provided by django-prometheus, which are generally self-documented by HELP lines in the raw metrics output. Some particularly useful ones are:

Name	Labels	Type	Description
django_http_requests_latency_seconds_by_view_method		histogram	Request processing time (including middleware)
django_http_responses_total_by_status_view_method	method, status, view	counter	Count of responses by method, status, and view

Other operational metrics are provided by Debusine itself:

Name	Labels	Type	Description
debusine_active_websocket_connections	view	gauge	Active connections to the Debusine server websocket
debusine_signon_oidc_callbacks	issuer, activated	counter	OpenID Connect authentication callbacks by issuer and whether the identity activation succeeded
debusine_websocket_connect_requests	view	counter	Total connections to the Debusine server websocket
debusine_work_request_start_latency	task_type, task_name, priority	histogram	Time in seconds that work requests spent waiting to start
debusine_workflow_orchestrator_duration	task_name	histogram	Time in seconds that workflow orchestrators took to run