- Flaky tests
- Slow tests
Unhealthy tests
Flaky tests
What’s a flaky test?
It’s a test that sometimes fails, but if you retry it enough times, it passes, eventually.
What are the potential cause for a test to be flaky?
State leak
Label: flaky-test::state leak
Description: Data state has leaked from a previous test. The actual cause is probably not the flaky test here.
Difficulty to reproduce: Moderate. Usually, running the same spec files until the one that’s failing reproduces the problem.
Resolution: Fix the previous tests and/or places where the test data or environment is modified, so that it’s reset to a pristine test after each test.
Examples:
-
Example 1: State leakage can result from
data records created with
let_it_be
shared between test examples, while some test modifies the model either deliberately or unwillingly causing out-of-sync data in test examples. This can result inPG::QueryCanceled: ERROR
in the subsequent test examples or retries. For more information about state leakages and resolution options, see GitLab testing best practices. - Example 2: A migration test might roll-back the database, perform its testing, and then roll-up the database in an inconsistent state, so that following tests might not know about certain columns.
- Example 3: A test modifies data that is used by a following test.
- Example 4: A test for a database query passes in a fresh database, but in a CI/CD pipeline where the database is used to process previous test sequences, the test fails. This likely means that the query itself needs to be updated to work in a non-clean database.
- Example 5: Unrelated database connections in asynchronous requests checked back in, causing the tests to accidentally use these unrelated database connections. The failure was resolved in this merge request.
- Example 6: The maximum time to live for a database connection causes these connections to be disconnected, which in turn causes tests that rely on the transactions on these connections to in turn causes tests that rely on the transactions on these connections to fail. The issue was fixed in this merge request.
- Example 7: A TCP socket used in a test was not closed before the next test, which also used the same port with another TCP socket.
Dataset-specific
Label: flaky-test::dataset-specific
Description: The test assumes the dataset is in a particular (usually limited) state or order, which might not be true depending on when the test run during the test suite.
Difficulty to reproduce: Moderate, as the amount of data needed to reproduce the issue might be difficult to achieve locally. Ordering issues are easier to reproduce by repeatedly running the tests several times.
Resolution:
- Fix the test to not assume that the dataset is in a particular state, don’t hardcode IDs.
- Loosen the assertion if the test shouldn’t care about ordering but only on the elements.
- Fix the test by specifying a deterministic ordering.
- Fix the app code by specifying a deterministic ordering.
Examples:
-
Example 1: The database is recreated when
any table has more than 500 columns. It could pass in the merge request, but fail later in
master
if the order of tests changes. -
Example 2: A test asserts
that trying to find a record with an nonexistent ID returns an error message. The test uses an
hardcoded ID that’s supposed to not exist (for example,
42
). If the test is run early in the test suite, it might pass as not enough records were created before it, but as soon as it would run later in the suite, there could be a record that actually has the ID42
, hence the test would start to fail. -
Example 3: Without
specifying
ORDER BY
, database is not given deterministic ordering, or data race can happen in the tests. - Example 4.
Too Many SQL queries
Label: flaky-test::too-many-sql-queries
Description: SQL Query limit has reached triggering Gitlab::QueryLimiting::Transaction::ThresholdExceededError
.
Difficulty to reproduce: Moderate, this failure may depend on the state of query cache which can be impacted by order of specs.
Resolution: See query count limits docs.
Random input
Label: flaky-test::random input
Description: The test use random values, that sometimes match the expectations, and sometimes not.
Difficulty to reproduce: Easy, as the test can be modified locally to use the “random value” used at the time the test failed
Resolution: Once the problem is reproduced, it should be easy to debug and fix either the test or the app.
Examples:
- Example 1: The test isn’t robust enough to handle a specific data, that only appears sporadically since the data input is random.
Unreliable DOM Selector
Label: flaky-test::unreliable dom selector
Description: The DOM selector used in the test is unreliable.
Difficulty to reproduce: Moderate to difficult. Depending on whether the DOM selector is duplicated, or appears after a delay etc. Adding a delay in API or controller could help reproducing the issue.
Resolution: It really depends on the problem here. It could be to wait for requests to finish, to scroll down the page etc.
Examples:
-
Example 1: A non-unique CSS selector
matching more than one element, or a non-waiting selector method that does not allow rendering
time before throwing an
element not found
error. - Example 2: A CSS selector only appears after a GraphQL requests has finished, and the UI has updated.
- Example 3: A false-positive test, Capybara immediately returns true after page visit and page is not fully loaded, or if the element is not detectable by webdriver (such as being rendered outside the viewport or behind other elements).
Datetime-sensitive
Label: flaky-test::datetime-sensitive
Description: The test is assuming a specific date or time.
Difficulty to reproduce: Easy to moderate, depending on whether the test consistently fails after a certain date, or only fails at a given time or date.
Resolution: Freezing the time is usually a good solution.
Examples:
- Example 1: A test that breaks after some time passed.
- Example 2: A test that breaks in the last day of the month.
Unstable infrastructure
Label: flaky-test::unstable infrastructure
Description: The test fails from time to time due to infrastructure issues.
Difficulty to reproduce: Hard. It’s really hard to reproduce CI infrastructure issues. It might be possible by using containers locally.
Resolution: Starting a conversation with the Infrastructure department in a dedicated issue is usually a good idea.
Examples:
- Example 1: The runner is under heavy load at this time.
- Example 2: The runner is having networking issues, making a job failing early
How to reproduce a flaky test locally?
- Reproduce the failure locally
- Find RSpec
seed
from the CI job log - OR Run
while :; do bin/rspec <spec> || break; done
in a loop to find aseed
- Find RSpec
- Reduce the examples by bisecting the spec failure with
bin/rspec --seed <previously found> --require ./config/initializers/macos.rb --bisect <spec>
- Look at the remaining examples and watch for state leakage
- e.g. Updating records created with
let_it_be
is a common source of problems
- e.g. Updating records created with
- Once fixed, rerun the specs with
seed
- Run
scripts/rspec_check_order_dependence
to ensure the spec can be run in random order - Run
while :; do bin/rspec <spec> || break; done
in a loop again (and grab lunch) to verify it’s no longer flaky
Quarantined tests
When we have a flaky test in master
:
- Create a ~"failure::flaky-test" issue with the relevant group label.
- Quarantine the test after the first failure. If the test cannot be fixed in a timely fashion, there is an impact on the productivity of all the developers, so it should be quarantined.
RSpec
Fast quarantine
Unless you really need to have a test disabled very fast (< 10min
), consider using the ~pipeline::expedited
label instead.
To quickly quarantine a test without having to open a merge request and wait for pipelines, you can follow the fast quarantining process.
Please always proceed to open a long-term quarantine merge request after fast-quarantining a test! This is to ensure the fast-quarantined test was correctly fixed by running tests from the CI/CD pipelines (which are not run in the context of the fast-quarantine project).
Long-term quarantine
Once a test is fast-quarantined, you can proceed with the long-term quarantining process. This can be done by opening a merge request.
First, ensure the test file has a feature_category
metadata, to ensure correct attribution of the test file.
Then, you can use the quarantine: '<issue url>'
metadata with the URL of the
~"failure::flaky-test" issue you created previously.
# Quarantine a single spec
it 'succeeds', quarantine: 'https://gitlab.com/gitlab-org/gitlab/-/issues/12345' do
expect(response).to have_gitlab_http_status(:ok)
end
# Quarantine a describe/context block
describe '#flaky-method', quarantine: 'https://gitlab.com/gitlab-org/gitlab/-/issues/12345' do
[...]
end
This means it will be skipped in CI. By default, the quarantined tests will run locally.
We can skip them in local development as well by running with --tag ~quarantine
:
# Bash
bin/rspec --tag ~quarantine
# ZSH
bin/rspec --tag \~quarantine
Also, please ensure that:
- The ~"quarantine" label is present on the merge request.
- The MR description mentions the flaky test issue with the usual terms to link a merge request to an issue.
Note that we should not quarantine a shared example/context, and we cannot quarantine a call to it_behaves_like
or include_examples
:
# Will be flagged by Rubocop
shared_examples 'loads all the users when opened', quarantine: 'https://gitlab.com/gitlab-org/gitlab/-/issues/12345' do
[...]
end
# Does not work
it_behaves_like 'a shared example', quarantine: 'https://gitlab.com/gitlab-org/gitlab/-/issues/12345'
# Does not work
include_examples 'a shared example', quarantine: 'https://gitlab.com/gitlab-org/gitlab/-/issues/12345'
After the long-term quarantining MR has reached production, you should revert the fast-quarantine MR you created earlier.
Find quarantined tests by feature category
To find all quarantined tests for a feature category, use ripgrep
:
rg -l --multiline -w "(?s)feature_category:\s+:global_search.+quarantine:"
Jest
For Jest specs, you can use the .skip
method along with the eslint-disable-next-line
comment to disable the jest/no-disabled-tests
ESLint rule and include the issue URL. Here’s an example:
// quarantine: https://gitlab.com/gitlab-org/gitlab/-/issues/56789
// eslint-disable-next-line jest/no-disabled-tests
it.skip('should throw an error', () => {
expect(response).toThrowError(expected_error)
});
This means it is skipped unless the test suit is run with --runInBand
Jest command line option:
jest --runInBand
A list of files with quarantined specs in them can be found with the command:
yarn jest:quarantine
For both test frameworks, make sure to add the ~"quarantined test"
label to the issue.
Once a test is in quarantine, there are 3 choices:
- Fix the test (that is, get rid of its flakiness).
- Move the test to a lower level of testing.
- Remove the test entirely (for example, because there’s already a lower-level test, or it’s duplicating another same-level test, or it’s testing too much etc.).
Automatic retries and flaky tests detection
On our CI, we use RSpec::Retry
to automatically retry a failing example a few
times (see spec/spec_helper.rb
for the precise retries count).
We also use a custom Gitlab::RspecFlaky::Listener
.
This listener runs in the update-tests-metadata
job in maintenance
scheduled pipelines
on the master
branch, and saves flaky examples to rspec/flaky/report-suite.json
.
The report file is then retrieved by the retrieve-tests-metadata
job in all pipelines.
This was originally implemented in: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/13021.
If you want to enable retries locally, you can use the RETRIES
environment variable.
For instance RETRIES=1 bin/rspec ...
would retry the failing examples once.
To generate the reports locally, use the FLAKY_RSPEC_GENERATE_REPORT
environment variable.
For example, FLAKY_RSPEC_GENERATE_REPORT=1 bin/rspec ...
.
Usage of the rspec/flaky/report-suite.json
report
The rspec/flaky/report-suite.json
report is
imported into Snowflake
once per day, for monitoring with the
internal dashboard.
Problems we had in the past at GitLab
-
rspec-retry
is biting us when some API specs fail: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/9825 -
Sporadic RSpec failures due to
PG::UniqueViolation
: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/9846 - ffaker generates funky data that tests are not ready to handle (and tests should be predictable so that’s bad!):
-
Make
spec/mailers/notify_spec.rb
more robust: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/10015 -
Transient failure in
spec/requests/api/commits_spec.rb
: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/9944 - Replace ffaker factory data with sequences: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/10184
- Transient failure in spec/finders/issues_finder_spec.rb: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/10404
-
Make
Order-dependent flaky tests
To identify ordering issues in a single file read about how to reproduce a flaky test locally.
Some flaky tests can fail depending on the order they run with other tests. For example:
To identify the ordering issues across different files, you can use scripts/rspec_bisect_flaky
,
which would give us the minimal test combination to reproduce the failure:
- First obtain the list of specs that ran before the flaky test. You can search
for the list under
Knapsack node specs:
in the CI job output log. -
Save the list of specs as a file, and run:
cat knapsack_specs.txt | xargs scripts/rspec_bisect_flaky
If there is an order-dependency issue, the script above will print the minimal reproduction.
Time-sensitive flaky tests
- https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/10046
- https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/10306
Array order expectation
Feature tests
- Be sure to create all the data the test need before starting exercise: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/12059
- Bis: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/12604
- Bis: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/12664
- Assert against the underlying database state instead of against a page’s content: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/10934
- In JS tests, shifting elements can cause Capybara to mis-click when the element moves at the exact time Capybara sends the click
- Triggering JS events before the event handlers are set up
-
Wait for the image to be lazy-loaded when asserting on a Markdown image’s
src
attribute - Avoid asserting against flash notice banners
Capybara viewport size related issues
- Transient failure of spec/features/issues/filtered_search/filter_issues_spec.rb: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/10411
Capybara JS driver related issues
- Don’t wait for AJAX when no AJAX request is fired: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/10454
- Bis: https://gitlab.com/gitlab-org/gitlab-foss/-/merge_requests/12626
Capybara expectation times out
Hanging specs
If a spec hangs, or times out in CI, it might be caused by a LoadInterlockAwareMonitor deadlock bug in Rails.
To diagnose, you can use sigdump to print the Ruby thread dump :
- Run the hanging spec locally.
-
Trigger the Ruby thread dump by running this command:
kill -CONT <pid>
- The thread dump will be saved to the
/tmp/sigdump-<pid>.log
file.
If you see lines with load_interlock_aware_monitor.rb
, this is likely related:
/builds/gitlab-org/gitlab/vendor/ruby/3.2.0/gems/activesupport-7.0.8.4/lib/active_support/concurrency/load_interlock_aware_monitor.rb:17:in `mon_enter'
/builds/gitlab-org/gitlab/vendor/ruby/3.2.0/gems/activesupport-7.0.8.4/lib/active_support/concurrency/load_interlock_aware_monitor.rb:22:in `block in synchronize'
/builds/gitlab-org/gitlab/vendor/ruby/3.2.0/gems/activesupport-7.0.8.4/lib/active_support/concurrency/load_interlock_aware_monitor.rb:21:in `handle_interrupt'
/builds/gitlab-org/gitlab/vendor/ruby/3.2.0/gems/activesupport-7.0.8.4/lib/active_support/concurrency/load_interlock_aware_monitor.rb:21:in `synchronize'
See examples where we worked around by creating the factories before making requests:
- https://gitlab.com/gitlab-org/gitlab/-/merge_requests/81112
- https://gitlab.com/gitlab-org/gitlab/-/merge_requests/158890
- https://gitlab.com/gitlab-org/gitlab/-/issues/337039
Suggestions
Split the test file
It could help to split the large RSpec files in multiple files in order to narrow down the context and identify the problematic tests.
Recreate job failure in CI by forcing the job to run the same set of test files
Reproducing a job failure in CI always helps with troubleshooting why and how a test fails. This require us running the same test files with the same spec order. Since we use Knapsack to distribute tests across parallelized jobs, and files can be distributed differently between two pipelines, we can hardcode this job distribution through the following steps:
- Find a job that you want to reproduce, identify the commit that it ran against, set your local
gitlab-org/gitlab
branch to the same commit to ensure we are running with the same copy of the project. - In the job log, locate the list of spec files that were distributed by Knapsack - you can search for
Running command: bundle exec rspec
, the last argument of this command should contain a list of filenames. Copy this list. - Go to
tooling/lib/tooling/parallel_rspec_runner.rb
where the test file distribution happens. Have a look at this merge request as an example, store the file list you copied from step 2 into aTEST_FILES
constant and have RSpec run this list by updating therspec_command
method as done in the example MR. - Skip the tests in
spec/tooling/lib/tooling/parallel_rspec_runner_spec.rb
so it doesn’t cause your pipeline to fail early. - Since we want to force the pipeline to run against a specific version, we do not want to run a merged results pipeline. We can introduce a merge conflict into the MR to achieve this.
- To preserve spec ordering, update the
spec/support/rspec_order.rb
file by hard codingKernel.srand
with the value shown in the originally failing job, as done here. You can fine the srand value in the job log by searchingRandomized with seed
which is followed by this value.
Resources
- Flaky Tests: Are You Sure You Want to Rerun Them?
- How to Deal With and Eliminate Flaky Tests
- Tips on Treating Flakiness in your Rails Test Suite
- ‘Flaky’ tests: a short story
- Test Insights
Slow tests
Top slow tests
We collect information about tests duration in rspec_profiling_stats
project. The data is showed using GitLab Pages in this
UI
In this issue, we defined thresholds for tests duration that can act as a guide.
For tests that are above the thresholds, we automatically report slowness occurrences in Test issues so that groups can improve them.
For tests that are slow for a legitimate reason and to skip issue creation, add allowed_to_be_slow: true
.
Date | Feature tests | Controllers and Requests tests | Unit | Other | Method |
---|---|---|---|---|---|
2023-02-15 | 67.42 seconds | 44.66 seconds | - | 76.86 seconds | Top slow test eliminating the maximum |
2023-06-15 | 50.13 seconds | 19.20 seconds | 27.12 | 45.40 seconds | Avg for top 100 slow tests |