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  • 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
  • Merging a feature into an existing feature for simplification.
  • 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
  • Suggested Reviewer functionality for the AI-powered stage within the Data Science section
  • featureflagdisabled
    GitLab.org
    The roll out of this feature does not effect any systems
  • The roll out of this feature only effects all environments
  • featureflagstaging
    GitLab.org
    The roll out of this feature only effects the staging environment
  • 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
  • IPS/IDS program for Internet access run by Verizon, ATT, CenturyLink, 2nd largest Cyber spend by Civ gov
  • Civilian, State, and Local gov Highly Adaptive Cybersecurity Services program for Threat Hunting (Pen testing, Risk assessments, high value assessments) services
  • 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.
  • 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.
  • The test is assuming a specific date or time.
  • The test use random values, that sometimes match the expectations, and sometimes not.