Commit 68aaab1b authored by Alexander Diewald's avatar Alexander Diewald

Add debugging hints.

Signed-off-by: Alexander Diewald's avatarAlexander Diewald <diewald@fortiss.org>
parent 83cfcdf4
Pipeline #21234 failed with stages
in 19 minutes and 41 seconds
......@@ -24,3 +24,34 @@
Contains the product descriptions by they are built, such as AF3.
* releng
Contains common configuration shared by all plugins, update site configs, and
*Debugging Build Failures*
Whenever a CI job fails, it may be caused by a problematic source code change, a
bug in the maven-releng configuration, the docker image, or related to the
gitlab CI pipeline. The following pieces of information shall provides hints to
debug such issues.
* As a first measure, ensure that the AF3 and Kernel builds in your local AF3
AF3 developer installation. Ensure that you are on the branches that you want
to test.
* If this test succeeds, do a local AF3 maven build following the instructions
for a [local build](https://af3-developer.fortiss.org/projects/autofocus3/wiki/AF3_Build_Management#Local-Build).
* If the build finishes sucessfully, check whether the failure is caused by the
docker container configuration. Therefore, on a linux machine, install the
gitlab-runner and docker packages and build the docker image locally by
executing `docker build -t maven-releng docker/` within your clone of this
repository.
Afterwards, execute the stage from the CI script that failed by executing
`gitlab-runner exec docker <job-name>`. Please not that pipelines are not
not supported if executing the gitlab-runner tool locally. Hence you must
ensure that all required build artifacts are available in the job to test.
For instance, if the test phase fails, the gitlab-ci.yml must be modified to
clone all submodules and use all build flags defined in the build job.
Finally, if the isse is resolved by a change in the Dockerfile, follow the
instructions in the *Structure* section to upload the changes to the gitlab
repository. Otherwise, just push the changes of the gitlab-ci.yml script.
* If this point is reached, the CI build failure may caused by some pipeline
misconfiguration, for instance due to wrong artifact passing. Another likely
reason is an outdated docker image in the repositorie's Container Registry.
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