Other labels
failuretest-environment
GitLab.org
Tests that fail because of an issue with an external dependency, e.g., the infrastructure on which the test runs.
feature flag
GitLab.org
New changes that can be disabled using a feature flag, or existing feature flags that are being removed.
feature management
GitLab.org
Issues for Feature Management, part of the Release stage of the DevOps lifecycle
featureaddition
GitLab.org
Issues or MRs related to the first MVC that gives users a foundation of new capabilities that were previously unavailable. Read more at https://about.gitlab.com/handbook/engineering/metrics/#work-type-classification
featureenhancement
GitLab.org
User-facing improvements that refine the initial MVC to make it more useful and usable. Read more at https://about.gitlab.com/handbook/engineering/metrics/#data-classification
feature:suggested reviewer
GitLab.org
Suggested Reviewer functionality for the AI-powered stage within the Data Science section
federal::ALL140-2
GitLab.org
FIPS 140-2, entry level barrier to being eligible for lucrative deals in the pay to play US gov market.
federal::CivCDM
GitLab.org
Continuous Diagnostics and Mitigation (US Civ gov Cybersecurity program) 100 OEMs, $1 Billion/year
federal::CivEINSTEIN
GitLab.org
IPS/IDS program for Internet access run by Verizon, ATT, CenturyLink, 2nd largest Cyber spend by Civ gov
federal::Civ::hacscyber threat
GitLab.org
Civilian, State, and Local gov Highly Adaptive Cybersecurity Services program for Threat Hunting (Pen testing, Risk assessments, high value assessments) services
federal::Civ::high-value-assets
GitLab.org
Civilian gov mandated high value asset governance tied to CDM with Quarterly reports to Congress and Comptroller General
federal::DoDJRSS
GitLab.org
centralized IPS/IDS program for DoD/Allies coordinated by DISA, 37+ OEMs in the Joint Regional Security Stack. So big and awkwardly implemented it's drawn formal Pentagon criticism in 2017 and 2018. Multi-billion dollar IPS/IDS.
flaky-testdataset-specific
GitLab.org
The test assumes the dataset is in a particular (usually limited) state, which might not be true depending on when the test run during the test suite.
Prioritized