Developing code monitoring

What are code monitors?

In the simplest case, a code monitor runs a user-defined query and alerts the user whenever a new search result appears. In more general terms, a code monitor lets a user define one trigger and at least one action. A trigger defines a condition and if that condition evaluates to true, the trigger triggers the actions.


term description example
code monitor A code monitor is a group of 1 trigger and possibly multiple actions
trigger A trigger defines a condition which is checked regularly. New results for a diff/commit query
event If a condition evaluates to true we call this an event. New results found
action Events trigger actions. Send email

Starting up your environment

Code monitoring is an enterprise functionality. To run it locally you need to start Sourcegraph as enterprise service:

sg start # which defaults to `sg start enterprise`

Code monitoring is still experimental which means you have to enable it in the settings to be visible in the UI. Open your local instance of Sourcegraph and go to settings > User account > settings.

  "experimentalFeatures": {
    "codeMonitoring": true

Database layout

Table Description
cm_monitors Holds metadata of a code monitor.
cm_queries Contains data for each (trigger) query.
cm_emails Contains data for each (action) email.
cm_recipients Each email action can have multiple recipients. Each recipient can either be a user or an organization. Each row in this table corresponds to one reciepient.
cm_trigger_jobs Contains jobs (past, present, future) to run triggers. Trigger jobs are linked to their triggers via a foreign key.
cm_actions_jobs Contains jobs (past, present, future) to run actions. Actions jobs are linked to their action and to the event that triggered them via foreign keys.

Each type of trigger or type of action is represented by its own table in the database; queries are represented by cm_queries, and emails are represented by cm_emails and cm_recipients. The job tables (cm_trigger_jobs and cm_action_jobs) on the other hand contain the jobs for all types of triggers and actions.

For example: Each type of action is represented by a separate nullable column in cm_action_jobs. The dequeue worker reads a record and dispatches based on which of the columns is filled. The table below shows cm_action_jobswith two jobs enqueued, one for sending emails (id=1) and one for posting to a webhook (id=2). The details for each action are contained in the records linked to with the foreign keys in columns email and webhook.


id email webhook state
1 1 null queued
2 null 1 queued

For more details, see

Life of a code monitor

Let's follow the life of a code monitor with a query as a trigger and 1 email action.

  1. After you have created a code monitor, the following tables are filled:
    1. cm_monitors (1 entry)
    2. cm_queries (1 entry)
    3. cm_actions (at least 1 entry)
    4. cm_recipients (at least 1 entry)
  2. Enqueue trigger: Periodically, a background job enqueues queries, i.e. for each active query (column enabled=true in cm_queries), we create an entry in cm_trigger_jobs.
  3. Dequeue trigger/enqueue actions: Periodically, a background worker dequeues the trigger job and processes it. In our case the query is run. The last_result and next_run are logged to cm_queries, the num_results and the query are logged to cm_query_jobs. If the query returned at least 1 result, we call it an event. For each event the corresponding actions are enqueued in cm_actions_jobs.
  4. Dequeue actions: Periodically, a background worker dequeues the action jobs queued in cm_action_jobs and processes them. In our cases we retrieve all relevant information from cm_monitors, cm_trigger_jobs, cm_query, cm_emails, cm_recipients and send out an email to the recipients.
  5. Clean-up: Job logs are deleted after a predefined retention period. Job logs without search results, are deleted soon after the trigger jobs ran.


The back end of code monitoring is split into two parts, the GraphQL API, running on frontend, and the background workers, running on repo-updater. Both rely on the store to access the database.


The GraphQL API is defined here. The interfaces and stub-resolvers are defined here, while the enterprise resolvers are defined here.

Background workers

The background workers utilize our internal/workerutil framework to run as background jobs on repo-updater.

Diving into the code as a backend developer

  1. A good start is to visualize the GraphQL schema and interact with it via the UI Console. Start from the node user and go to monitors from there.
  2. Check out the interfaces and stub resolvers and understand how they relate to the GraphQL schema.
  3. Do the same for the enterprise resolvers.
  4. Take a look at the background workers and look through each of the jobs that run in the background.
  5. Start up Sourcegraph locally, connect to your local db instance, create a code monitor from the UI and follow its life cycle in the db. Start by looking at cm_queries and cm_trigger_jobs. Depending on the search query you defined you might have to wait a long time before the first action is enqueued in cm_action_jobs. You can accelerate the process by backdating columns last_result and next_run to the past.