9.9 KiB
stage | group | info | type |
---|---|---|---|
Verify | Runner | To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/product/ux/technical-writing/#assignments | reference |
Job logs (FREE SELF)
Job logs are sent by a runner while it's processing a job. You can see logs in job pages, pipelines, email notifications, and so on.
Data flow
In general, there are two states for job logs: log
and archived log
.
In the following table you can see the phases a log goes through:
Phase | State | Condition | Data flow | Stored path |
---|---|---|---|---|
1: patching | log | When a job is running | Runner => Puma => file storage | #{ROOT_PATH}/gitlab-ci/builds/#{YYYY_mm}/#{project_id}/#{job_id}.log |
2: archiving | archived log | After a job is finished | Sidekiq moves log to artifacts folder | #{ROOT_PATH}/gitlab-rails/shared/artifacts/#{disk_hash}/#{YYYY_mm_dd}/#{job_id}/#{job_artifact_id}/job.log |
3: uploading | archived log | After a log is archived | Sidekiq moves archived log to object storage (if configured) | #{bucket_name}/#{disk_hash}/#{YYYY_mm_dd}/#{job_id}/#{job_artifact_id}/job.log |
The ROOT_PATH
varies per environment:
- For the Linux package it's
/var/opt/gitlab
. - For self-compiled installations it's
/home/git/gitlab
.
Changing the job logs local location
NOTE: For Docker installations, you can change the path where your data is mounted. For the Helm chart, use object storage.
To change the location where the job logs are stored:
::Tabs
:::TabTitle Linux package (Omnibus)
-
Optional. If you have existing job logs, pause continuous integration data processing by temporarily stopping Sidekiq:
sudo gitlab-ctl stop sidekiq
-
Set the new storage location in
/etc/gitlab/gitlab.rb
:gitlab_ci['builds_directory'] = '/mnt/gitlab-ci/builds'
-
Save the file and reconfigure GitLab:
sudo gitlab-ctl reconfigure
-
Use
rsync
to move job logs from the current location to the new location:sudo rsync -avzh --remove-source-files --ignore-existing --progress /var/opt/gitlab/gitlab-ci/builds/ /mnt/gitlab-ci/builds/
Use
--ignore-existing
so you don't override new job logs with older versions of the same log. -
If you opted to pause the continuous integration data processing, you can start Sidekiq again:
sudo gitlab-ctl start sidekiq
-
Remove the old job logs storage location:
sudo rm -rf /var/opt/gitlab/gitlab-ci/builds
:::TabTitle Self-compiled (source)
-
Optional. If you have existing job logs, pause continuous integration data processing by temporarily stopping Sidekiq:
# For systems running systemd sudo systemctl stop gitlab-sidekiq # For systems running SysV init sudo service gitlab stop
-
Edit
/home/git/gitlab/config/gitlab.yml
to set the new storage location:production: &base gitlab_ci: builds_path: /mnt/gitlab-ci/builds
-
Save the file and restart GitLab:
# For systems running systemd sudo systemctl restart gitlab.target # For systems running SysV init sudo service gitlab restart
-
Use
rsync
to move job logs from the current location to the new location:sudo rsync -avzh --remove-source-files --ignore-existing --progress /home/git/gitlab/builds/ /mnt/gitlab-ci/builds/
Use
--ignore-existing
so you don't override new job logs with older versions of the same log. -
If you opted to pause the continuous integration data processing, you can start Sidekiq again:
# For systems running systemd sudo systemctl start gitlab-sidekiq # For systems running SysV init sudo service gitlab start
-
Remove the old job logs storage location:
sudo rm -rf /home/git/gitlab/builds
::EndTabs
Uploading logs to object storage
Archived logs are considered as job artifacts. Therefore, when you set up the object storage integration, job logs are automatically migrated to it along with the other job artifacts.
See "Phase 3: uploading" in Data flow to learn about the process.
Prevent local disk usage
If you want to avoid any local disk usage for job logs, you can do so using one of the following options:
- Enable the incremental logging feature.
- Set the job logs location to an NFS drive.
How to remove job logs
There isn't a way to automatically expire old job logs, but it's safe to remove them if they're taking up too much space. If you remove the logs manually, the job output in the UI is empty.
For example, to delete all job logs older than 60 days, run the following command from a shell in your GitLab instance.
NOTE: For the Helm chart, use the storage management tools provided with your object storage.
WARNING: The following command permanently deletes the log files and is irreversible.
::Tabs
:::TabTitle Linux package (Omnibus)
find /var/opt/gitlab/gitlab-rails/shared/artifacts -name "job.log" -mtime +60 -delete
:::TabTitle Docker
Assuming you mounted /var/opt/gitlab
to /srv/gitlab
:
find /srv/gitlab/gitlab-rails/shared/artifacts -name "job.log" -mtime +60 -delete
:::TabTitle Self-compiled (source)
find /home/git/gitlab/shared/artifacts -name "job.log" -mtime +60 -delete
::EndTabs
After the logs are deleted, you can find any broken file references by running the Rake task that checks the integrity of the uploaded files. For more information, see how to delete references to missing artifacts.
Incremental logging architecture
- Introduced in GitLab 10.8 with a flag named
ci_enable_live_trace
. Disabled by default.- Enabled on GitLab.com in GitLab 13.6.
- Recommended for production use in GitLab 13.6.
- Recommended for production use with AWS S3 in GitLab 13.7.
- To use in GitLab self-managed instances, ask a GitLab administrator to enable it.
By default, job logs are sent from the GitLab Runner in chunks and cached temporarily on disk. After the job completes, a background job archives the job log. The log is moved to the artifacts directory by default, or to object storage if configured.
In a scaled-out architecture with Rails and Sidekiq running on more than one server, these two locations on the file system have to be shared using NFS, which is not recommended. Instead:
- Configure object storage for storing archived job logs.
- Enable the incremental logging feature, which uses Redis instead of disk space for temporary caching of job logs.
Enable or disable incremental logging
Before you enable the feature flag:
To enable incremental logging:
-
Open a Rails console.
-
Enable the feature flag:
Feature.enable(:ci_enable_live_trace)
Running jobs' logs continue to be written to disk, but new jobs use incremental logging.
To disable incremental logging:
-
Open a Rails console.
-
Disable the feature flag:
Feature.disable(:ci_enable_live_trace)
Running jobs continue to use incremental logging, but new jobs write to the disk.
Technical details
The data flow is the same as described in the data flow section with one change: the stored path of the first two phases is different. This incremental log architecture stores chunks of logs in Redis and a persistent store (object storage or database) instead of file storage. Redis is used as first-class storage, and it stores up-to 128 KB of data. After the full chunk is sent, it is flushed to a persistent store, either object storage (temporary directory) or database. After a while, the data in Redis and a persistent store is archived to object storage.
The data are stored in the following Redis namespace: Gitlab::Redis::TraceChunks
.
Here is the detailed data flow:
- The runner picks a job from GitLab
- The runner sends a piece of log to GitLab
- GitLab appends the data to Redis
- After the data in Redis reaches 128 KB, the data is flushed to a persistent store (object storage or the database).
- The above steps are repeated until the job is finished.
- After the job is finished, GitLab schedules a Sidekiq worker to archive the log.
- The Sidekiq worker archives the log to object storage and cleans up the log in Redis and a persistent store (object storage or the database).
Limitations
- Redis Cluster is not supported.
- You must configure object storage for CI/CD artifacts, logs, and builds before you enable the feature flag. After the flag is enabled, files cannot be written to disk, and there is no protection against misconfiguration.
- There is an epic tracking other potential limitations and improvements.