elastic-recheck/README.rst

elastic-recheck

"Use ElasticSearch to classify OpenStack gate failures"

• Open Source Software: Apache license

Idea

Identifying the specific bug that is causing a transient error in the gate is difficult. Just identifying which tempest test failed is not enough because a single tempest test can fail due to any number of underlying bugs. If we can find a fingerprint for a specific bug using logs, then we can use ElasticSearch to automatically detect any occurrences of the bug.

Using these fingerprints elastic-recheck can:

• Search ElasticSearch for all occurrences of a bug.
• Identify bug trends such as: when it started, is the bug fixed, is it getting worse, etc.
• Classify bug failures in real time and report back to gerrit if we find a match, so a patch author knows why the test failed.

queries/

All queries are stored in separate yaml files in a queries directory at the top of the elastic-recheck code base. The format of these files is ######.yaml (where ###### is the launchpad bug number), the yaml should have a query keyword which is the query text for elastic search.

Guidelines for good queries:

• Queries should get as close as possible to fingerprinting the root cause. A filename query is typically better than a console one, as that's matching a deep failure versus a surface symptom.

• Queries should not return any hits for successful jobs, this is a sign the query isn't specific enough. A rule of thumb is > 10% success hits probably means this isn't good enough.

• If it's impossible to build a query to target a bug, consider patching the upstream program to be explicit when it fails in a particular way.

• Use the 'tags' field rather than the 'filename' field for filtering. This is primarily because of grenade jobs where the same log file shows up in the 'old' and 'new' side of the grenade job. For example, tags:"screen-n-cpu.txt" will query in logs/old/screen-n-cpu.txt and logs/new/screen-n-cpu.txt. The tags:"console" filter is also used to query in console.html as well as tempest and devstack logs.

• Avoid the use of wildcards in queries since they can put an undue burden on the query engine. A common case where wildcards are used and shouldn't be are in querying against a specific set of build_name fields, e.g. gate-nova-python26 and gate-nova-python27. Rather than use build_name:gate-nova-python*, list the jobs with an OR. For example:

  (build_name:"gate-nova-python26" OR build_name:"gate-nova-python27")

In order to support rapidly added queries, it's considered socially acceptable to approve changes that only add 1 new bug query, and to even self approve those changes by core reviewers.

Note that old queries which are no longer hitting in logstash and are associated with fixed or incomplete bugs are routinely deleted. This is to keep the load on the elastic-search engine as low as possible when checking a job failure. If a bug marked as Incomplete does show up again, the bug should be re-opened with a link to the failure and the e-r query should be restored.

Adding Bug Signatures

Most transient bugs seen in gate are not bugs in tempest associated with a specific tempest test failure, but rather some sort of issue further down the stack that can cause many tempest tests to fail.

1. Given a transient bug that is seen during the gate, go through the logs and try to find a log that is associated with the failure. The closer to the root cause the better.

   Note that queries can only be written against INFO level and higher log messages. This is by design to not overwhelm the search cluster.

2. Go to logstash.openstack.org and create an elastic search query to find the log message from step 1. To see the possible fields to search on click on an entry. Lucene query syntax is available at lucene.apache.org.

3. Tag your commit with a Related-Bug tag in the footer, or add a comment to the bug with the query you identified and a link to the logstash URL for that query search.

   Putting the logstash query link in the bug report is also valuable in the case of rare failures that fall outside the window of how far back log results are stored. In such cases the bug might be marked as Incomplete and the e-r query could be removed, only for the failure to re-surface later. If a link to the query is in the bug report someone can easily track when it started showing up again.

4. Add the query to elastic-recheck/queries/BUGNUMBER.yaml (All queries can be found on git.openstack.org) and push the patch up for review.

Future Work

• Move config files into a separate directory
• Make unit tests robust
• Add debug mode flag
• Expand gating testing
• Cleanup and document code better
• Add ability to check if any resolved bugs return
• Move away from polling ElasticSearch to discover if its ready or not
• Add nightly job to propose a patch to remove bug queries that return no hits -- Bug hasn't been seen in 2 weeks and must be closed