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| Criterion |  DevOps Game Day |  Product Discovery Smoke Test |  Operations Failure Mode and Effects Analysis |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | In preparing for rare incidents, the method tests response capability under controlled conditions. It shows where assumptions about stability, roles, and recovery are too optimistic. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | For a process, product, or service with noticeable failure risks, the method assesses possible failure modes in advance. It directs attention to combinations of occurrence, effect, and detectability. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | High | Low | High | High |
Timedifferent | Halber Tag | 1-5 Tage | 2-6 h | 1-4 Wochen |
Participantsdifferent | 5-20 | Nutzertraffic | 3-10 | 1-6 |
Formatdifferent | Workshop | Async | Workshop | Async |
Outputdifferent | Simulation Notes, Gaps List, Updated Runbooks | Interest Metrics, Conversion Signal, Learning Note | FMEA Table, Risk Priority, Mitigation Actions | Experiment results, Decision log, Learning summary |
Tagsno overlap | ResilienceOperationsIncident | ValidationExperimentsDemandGrowth | RiskQualityOperationsRoot cause | ExperimentsGrowthAnalyticsValidation |