path: root/doc/administration/job_artifacts_troubleshooting.md

---
stage: Verify
group: Pipeline Security
info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://handbook.gitlab.com/handbook/product/ux/technical-writing/#assignments
---

# Job artifact troubleshooting for administrators

When administering job artifacts, you might encounter the following issues.

## Job artifacts using too much disk space

Job artifacts can fill up your disk space quicker than expected. Some possible
reasons are:

- Users have configured job artifacts expiration to be longer than necessary.
- The number of jobs run, and hence artifacts generated, is higher than expected.
- Job logs are larger than expected, and have accumulated over time.
- The file system might run out of inodes because
  [empty directories are left behind by artifact housekeeping](https://gitlab.com/gitlab-org/gitlab/-/issues/17465).
  [The Rake task for _orphaned_ artifact files](../raketasks/cleanup.md#remove-orphan-artifact-files)
  removes these.
- Artifact files might be left on disk and not deleted by housekeeping. Run the
  [Rake task for _orphaned_ artifact files](../raketasks/cleanup.md#remove-orphan-artifact-files)
  to remove these. This script should always find work to do, as it also removes empty directories (see above).
- [Artifact housekeeping was changed significantly](#housekeeping-disabled-in-gitlab-146-to-152),
  and you might need to enable a feature flag to use the updated system.
- The [keep latest artifacts from most recent success jobs](../ci/jobs/job_artifacts.md#keep-artifacts-from-most-recent-successful-jobs)
  feature is enabled.

In these and other cases, identify the projects most responsible
for disk space usage, figure out what types of artifacts are using the most
space, and in some cases, manually delete job artifacts to reclaim disk space.

### Artifacts housekeeping

Artifacts housekeeping is the process that identifies which artifacts are expired
and can be deleted.

#### Housekeeping disabled in GitLab 14.6 to 15.2

Artifact housekeeping was disabled in GitLab 14.6. It was significantly improved
in GitLab 14.10, and the changes were back ported to patch versions of GitLab 14.6 and later,
introduced behind [feature flags](feature_flags.md) disabled by default. The flags were
enabled by default [in GitLab 15.3](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/92931).

If artifacts housekeeping does not seem to be working in GitLab 14.6 to GitLab 15.2,
you should check if the feature flags are enabled.

To check if the feature flags are enabled:

1. Start a [Rails console](operations/rails_console.md#starting-a-rails-console-session).

1. Check if the feature flags are enabled.

   - GitLab 14.10 and earlier:

     ```ruby
     Feature.enabled?(:ci_detect_wrongly_expired_artifacts, default_enabled: :yaml)
     Feature.enabled?(:ci_update_unlocked_job_artifacts, default_enabled: :yaml)
     Feature.enabled?(:ci_job_artifacts_backlog_work, default_enabled: :yaml)
     ```

   - GitLab 15.0 and later:

     ```ruby
     Feature.enabled?(:ci_detect_wrongly_expired_artifacts)
     Feature.enabled?(:ci_update_unlocked_job_artifacts)
     Feature.enabled?(:ci_job_artifacts_backlog_work)
     ```

1. If any of the feature flags are disabled, enable them:

   ```ruby
   Feature.enable(:ci_detect_wrongly_expired_artifacts)
   Feature.enable(:ci_update_unlocked_job_artifacts)
   Feature.enable(:ci_destroy_unlocked_job_artifacts)
   ```

These changes include switching artifacts from `unlocked` to `locked` if
they [should be retained](../ci/jobs/job_artifacts.md#keep-artifacts-from-most-recent-successful-jobs).

#### Artifacts with `unknown` status

Artifacts created before housekeeping was updated have a status of `unknown`. After they expire,
these artifacts are not processed by the new housekeeping.

You can check the database to confirm if your instance has artifacts with the `unknown` status:

1. Start a database console:

   ::Tabs

   :::TabTitle Linux package (Omnibus)

   ```shell
   sudo gitlab-psql
   ```

   :::TabTitle Helm chart (Kubernetes)

   ```shell
   # Find the toolbox pod
   kubectl --namespace <namespace> get pods -lapp=toolbox
   # Connect to the PostgreSQL console
   kubectl exec -it <toolbox-pod-name> -- /srv/gitlab/bin/rails dbconsole --include-password --database main
   ```

   :::TabTitle Docker

   ```shell
   sudo docker exec -it <container_name> /bin/bash
   gitlab-psql
   ```

   :::TabTitle Self-compiled (source)

   ```shell
   sudo -u git -H psql -d gitlabhq_production
   ```

   ::EndTabs

1. Run the following query:

   ```sql
   select expire_at, file_type, locked, count(*) from ci_job_artifacts
   where expire_at is not null and
   file_type != 3
   group by expire_at, file_type, locked having count(*) > 1;
   ```

If records are returned, then there are artifacts which the housekeeping job
is unable to process. For example:

```plaintext
           expire_at           | file_type | locked | count
-------------------------------+-----------+--------+--------
 2021-06-21 22:00:00+00        |         1 |      2 |  73614
 2021-06-21 22:00:00+00        |         2 |      2 |  73614
 2021-06-21 22:00:00+00        |         4 |      2 |   3522
 2021-06-21 22:00:00+00        |         9 |      2 |     32
 2021-06-21 22:00:00+00        |        12 |      2 |    163
```

Artifacts with locked status `2` are `unknown`. Check
[issue #346261](https://gitlab.com/gitlab-org/gitlab/-/issues/346261#note_1028871458)
for more details.

#### Clean up `unknown` artifacts

The Sidekiq worker that processes all `unknown` artifacts is enabled by default in
GitLab 15.3 and later. It analyzes the artifacts returned by the above database query and
determines which should be `locked` or `unlocked`. Artifacts are then deleted
by that worker if needed.

The worker can be enabled on self-managed instances running GitLab 14.10 and later:

1. Start a [Rails console](operations/rails_console.md#starting-a-rails-console-session).

1. Check if the feature is enabled.

   - GitLab 14.10:

     ```ruby
     Feature.enabled?(:ci_job_artifacts_backlog_work, default_enabled: :yaml)
     ```

   - GitLab 15.0 and later:

     ```ruby
     Feature.enabled?(:ci_job_artifacts_backlog_work)
     ```

1. Enable the feature, if needed:

   ```ruby
   Feature.enable(:ci_job_artifacts_backlog_work)
   ```

The worker processes 10,000 `unknown` artifacts every seven minutes, or roughly two million
in 24 hours.

There is a related `ci_job_artifacts_backlog_large_loop_limit` feature flag
which causes the worker to process `unknown` artifacts
[in batches that are five times larger](https://gitlab.com/gitlab-org/gitlab/-/issues/356319).
This flag is not recommended for use on self-managed instances.

### List projects and builds with artifacts with a specific expiration (or no expiration)

Using a [Rails console](operations/rails_console.md), you can find projects that have job artifacts with either:

- No expiration date.
- An expiration date more than 7 days in the future.

Similar to [deleting artifacts](#delete-job-artifacts-from-jobs-completed-before-a-specific-date), use the following example time frames
and alter them as needed:

- `7.days.from_now`
- `10.days.from_now`
- `2.weeks.from_now`
- `3.months.from_now`

Each of the following scripts also limits the search to 50 results with `.limit(50)`, but this number can also be changed as needed:

```ruby
# Find builds & projects with artifacts that never expire
builds_with_artifacts_that_never_expire = Ci::Build.with_downloadable_artifacts.where(artifacts_expire_at: nil).limit(50)
builds_with_artifacts_that_never_expire.find_each do |build|
  puts "Build with id #{build.id} has artifacts that don't expire and belongs to project #{build.project.full_path}"
end

# Find builds & projects with artifacts that expire after 7 days from today
builds_with_artifacts_that_expire_in_a_week = Ci::Build.with_downloadable_artifacts.where('artifacts_expire_at > ?', 7.days.from_now).limit(50)
builds_with_artifacts_that_expire_in_a_week.find_each do |build|
  puts "Build with id #{build.id} has artifacts that expire at #{build.artifacts_expire_at} and belongs to project #{build.project.full_path}"
end
```

### List projects by total size of job artifacts stored

List the top 20 projects, sorted by the total size of job artifacts stored, by
running the following code in the [Rails console](operations/rails_console.md):

```ruby
include ActionView::Helpers::NumberHelper
ProjectStatistics.order(build_artifacts_size: :desc).limit(20).each do |s|
  puts "#{number_to_human_size(s.build_artifacts_size)} \t #{s.project.full_path}"
end
```

You can change the number of projects listed by modifying `.limit(20)` to the
number you want.

### List largest artifacts in a single project

List the 50 largest job artifacts in a single project by running the following
code in the [Rails console](operations/rails_console.md):

```ruby
include ActionView::Helpers::NumberHelper
project = Project.find_by_full_path('path/to/project')
Ci::JobArtifact.where(project: project).order(size: :desc).limit(50).map { |a| puts "ID: #{a.id} - #{a.file_type}: #{number_to_human_size(a.size)}" }
```

You can change the number of job artifacts listed by modifying `.limit(50)` to
the number you want.

### List artifacts in a single project

List the artifacts for a single project, sorted by artifact size. The output includes the:

- ID of the job that created the artifact
- artifact size
- artifact file type
- artifact creation date
- on-disk location of the artifact

```ruby
p = Project.find_by_id(<project_id>)
arts = Ci::JobArtifact.where(project: p)

list = arts.order(size: :desc).limit(50).each do |art|
    puts "Job ID: #{art.job_id} - Size: #{art.size}b - Type: #{art.file_type} - Created: #{art.created_at} - File loc: #{art.file}"
end
```

To change the number of job artifacts listed, change the number in `limit(50)`.

### Delete job artifacts from jobs completed before a specific date

WARNING:
These commands remove data permanently from database and storage. Before running them, we highly recommend seeking guidance from a Support Engineer, or running them in a test environment with a backup of the instance ready to be restored, just in case.

You can manually remove job artifacts associated with multiple completed jobs while
**retaining their job logs** from the [Rails console](operations/rails_console.md).
A completed job is any job with the status of success, failed, canceled, or skipped.

To delete jobs completed before a specific date:

1. Select jobs to be deleted:

   To select all jobs with artifacts for a single project:

   ```ruby
   project = Project.find_by_full_path('path/to/project')
   builds_with_artifacts =  project.builds.with_downloadable_artifacts
   ```

   To select all jobs with artifacts across the entire GitLab instance:

   ```ruby
   builds_with_artifacts = Ci::Build.with_downloadable_artifacts
   ```

1. Delete job artifacts older than a specific date:

   NOTE:
   This step also erases artifacts that users have chosen to
   ["keep"](../ci/jobs/job_artifacts.md#download-job-artifacts).

   ```ruby
   builds_to_clear = builds_with_artifacts.where("finished_at < ?", 1.year.ago)
   builds_to_clear.find_each do |build|
     Ci::JobArtifacts::DeleteService.new(build).execute
     build.update!(artifacts_expire_at: Time.now)
   end
   ```

   In [GitLab 15.3 and earlier](https://gitlab.com/gitlab-org/gitlab/-/issues/372537), use the following instead:

   ```ruby
   builds_to_clear = builds_with_artifacts.where("finished_at < ?", 1.year.ago)
   builds_to_clear.find_each do |build|
     build.artifacts_expire_at = Time.now
     build.erase_erasable_artifacts!
   end
   ```

   `1.year.ago` is a Rails [`ActiveSupport::Duration`](https://api.rubyonrails.org/classes/ActiveSupport/Duration.html) method.
   Start with a long duration to reduce the risk of accidentally deleting artifacts that are still in use.
   Rerun the deletion with shorter durations as needed, for example `3.months.ago`, `2.weeks.ago`, or `7.days.ago`.

   `erase_erasable_artifacts!` is a synchronous method, and upon execution the artifacts are immediately removed;
   they are not scheduled by a background queue.

### Delete job artifacts and logs from jobs completed before a specific date

WARNING:
These commands remove data permanently from both the database and from disk. Before running them, we highly recommend seeking guidance from a Support Engineer, or running them in a test environment with a backup of the instance ready to be restored, just in case.

You can manually remove job artifacts associated with multiple completed jobs while
**retaining their job logs** from the [Rails console](operations/rails_console.md).
A completed job is any job with the status of success, failed, canceled, or skipped.

To delete jobs completed before a specific date:

1. Select the jobs to be deleted:

   To select jobs with artifacts for a single project:

   ```ruby
   project = Project.find_by_full_path('path/to/project')
   builds_with_artifacts =  project.builds.with_downloadable_artifacts
   ```

   To select jobs with artifacts across the entire GitLab instance:

   ```ruby
   builds_with_artifacts = Ci::Build.with_downloadable_artifacts
   ```

   Occasionally, when choosing jobs with artifacts, there could be a risk of the process being terminated due to selecting a large number of rows. This can result in high memory usage and eventually lead to the process being killed due to an Out-of-Memory (OOM) error. To resolve this, you can run in small batches. The example below limits each batch to 1000.

   To select jobs with artifacts for a single project:

   ```ruby
   project = Project.find_by_full_path('path/to/project')
   builds_with_artifacts =  project.builds.with_downloadable_artifacts.find_each(batch_size: 1000)
   ```

   To select jobs with artifacts across the entire GitLab instance:

   ```ruby
   builds_with_artifacts = Ci::Build.with_downloadable_artifacts.find_each(batch_size: 1000)
   ```

1. Select the user which is mentioned in the web UI as erasing the job:

   ```ruby
   admin_user = User.find_by(username: 'username')
   ```

1. Erase the job artifacts and logs older than a specific date:

   ```ruby
   builds_to_clear = builds_with_artifacts.where("finished_at < ?", 1.year.ago)
   builds_to_clear.find_each do |build|
     print "Ci::Build ID #{build.id}... "

     if build.erasable?
       Ci::BuildEraseService.new(build, admin_user).execute
       puts "Erased"
     else
       puts "Skipped (Nothing to erase or not erasable)"
     end
   end
   ```

   In [GitLab 15.3 and earlier](https://gitlab.com/gitlab-org/gitlab/-/issues/369132), replace
   `Ci::BuildEraseService.new(build, admin_user).execute` with `build.erase(erased_by: admin_user)`.

   `1.year.ago` is a Rails [`ActiveSupport::Duration`](https://api.rubyonrails.org/classes/ActiveSupport/Duration.html) method.
   Start with a long duration to reduce the risk of accidentally deleting artifacts that are still in use.
   Rerun the deletion with shorter durations as needed, for example `3.months.ago`, `2.weeks.ago`, or `7.days.ago`.

## Job artifact upload fails with error 500

If you are using object storage for artifacts and a job artifact fails to upload,
review:

- The job log for an error message similar to:

  ```plaintext
  WARNING: Uploading artifacts as "archive" to coordinator... failed id=12345 responseStatus=500 Internal Server Error status=500 token=abcd1234
  ```

- The [workhorse log](logs/index.md#workhorse-logs) for an error message similar to:

  ```json
  {"error":"MissingRegion: could not find region configuration","level":"error","msg":"error uploading S3 session","time":"2021-03-16T22:10:55-04:00"}
  ```

In both cases, you might need to add `region` to the job artifact [object storage configuration](object_storage.md).

## Job artifact upload fails with `500 Internal Server Error (Missing file)`

Bucket names that include folder paths are not supported with [consolidated object storage](object_storage.md#configure-a-single-storage-connection-for-all-object-types-consolidated-form).
For example, `bucket/path`. If a bucket name has a path in it, you might receive an error similar to:

```plaintext
WARNING: Uploading artifacts as "archive" to coordinator... POST https://gitlab.example.com/api/v4/jobs/job_id/artifacts?artifact_format=zip&artifact_type=archive&expire_in=1+day: 500 Internal Server Error (Missing file)
FATAL: invalid argument
```

If a job artifact fails to upload with the above error when using consolidated object storage, make sure you are [using separate buckets](object_storage.md#use-separate-buckets) for each data type.

## Job artifacts fail to upload with `FATAL: invalid argument` when using Windows mount

If you are using a Windows mount with CIFS for job artifacts, you may see an
`invalid argument` error when the runner attempts to upload artifacts:

```plaintext
WARNING: Uploading artifacts as "dotenv" to coordinator... POST https://<your-gitlab-instance>/api/v4/jobs/<JOB_ID>/artifacts: 500 Internal Server Error  id=1296 responseStatus=500 Internal Server Error status=500 token=*****
FATAL: invalid argument
```

To work around this issue, you can try:

- Switching to an ext4 mount instead of CIFS.
- Upgrading to at least Linux kernel 5.15 which contains a number of important bug fixes
  relating to CIFS file leases.
- For older kernels, using the `nolease` mount option to disable file leasing.

For more information, [see the investigation details](https://gitlab.com/gitlab-org/gitlab/-/issues/389995).

## Usage quota shows incorrect artifact storage usage

> [Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/238536) in GitLab 14.10.

Sometimes the [artifacts storage usage](../user/usage_quotas.md) displays an incorrect
value for the total storage space used by artifacts. To recalculate the artifact
usage statistics for all projects in the instance, you can run this background script:

```shell
gitlab-rake gitlab:refresh_project_statistics_build_artifacts_size[https://example.com/path/file.csv]
```

The `https://example.com/path/file.csv` file must list the project IDs for
all projects for which you want to recalculate artifact storage usage. Use this format for the file:

```csv
PROJECT_ID
1
2
```

The artifact usage value can fluctuate to `0` while the script is running. After
recalculation, usage should display as expected again.