SuperAPI AI Directory

failover-testing

Testing & quality

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Updated 10-16 09:33

About this skill

Failover Testing

When to Use

  • Use this Skill when the work needs evidence-bounded analysis of primary-secondary triggers, traffic transfer, data consistency, and recovery evidence.
  • Use it when the input is incomplete but a reviewable first draft with assumptions and gaps is still useful.
  • Use it when static design evidence must remain separate from planned validation and completed execution.

Output Format Options

  • Default to Markdown organized by risk, evidence, and priority.
  • If the user asks for a table, CSV, JSON, or ticket format, preserve the same finding fields and evidence states.
  • Confirm the schema, enum values, and required fields before feeding the output to automation.

How to Use

  1. Read prompts/failover-testing.md and follow its input audit, coverage checklist, and output order.
  2. Extract scope, environment, version, dependencies, constraints, success criteria, and available evidence.
  3. Model primary-secondary triggers, traffic transfer, data consistency, and recovery evidence with scenarios and decision criteria, prioritizing high-impact or hard-to-detect items.
  4. Separate facts, evidence-backed inferences, candidate recommendations, and Human decisions.
  5. When information is missing, deliver a bounded draft and the smallest evidence-gathering actions; do not write recommendations as execution results.

Reference Files

  • Read prompts/failover-testing.md for every invocation; it is the complete execution contract.
  • Read evals/eval.yaml and the matching evals/cases/ when evaluating the Skill.
  • Read references/, examples/, scripts/, or output-formats.md only when the directory exists and the task needs it.

Domain Execution Essentials

  • Extract primary/standby roles, automatic/manual triggers, health detection, routing, fencing/write authority, failback and business-RTO definitions.
  • Deliver node/routing/write-authority timelines, ledger conflicts and recovery/failback oracles, assessing availability and single-writer consistency separately.
  • When deriving domain candidates, read and follow prompts/failover-testing.md for the domain procedure and oracle; retain valid controls, evidence gaps, and validation actions for each item.

Core Constraints

  • Analyze only primary-secondary triggers, traffic transfer, data consistency, and recovery evidence; do not inject faults, access real dependencies, or call production systems.
  • Do not invent thresholds, availability, recovery times, vulnerability states, or completed test runs.
  • Mark unsupported claims as pending, blocked, or unassessed and provide a validation method.
  • Leave risk acceptance, release approval, and Human takeover to a Human.

Delivery Self-Check

  • Complete the six-part input audit and mark evidence freshness.
  • Cover the failover path, failure modes, expected concerns, and validation method.
  • Separate facts, inferences, recommendations, gaps, and Human decisions.
  • Do not turn static design or a dry-run into a claim of execution, passing, or release.

Common Pitfalls

  • Treating adjacent performance, incident, or API analysis as a complete substitute for Failover Testing.
  • Listing steps without triggers, expected results, owner roles, or close conditions.
  • Refusing incomplete input, or filling critical facts with template assumptions.

Best Practices

  • Start with the paths most likely to cause business loss or recovery failure.
  • Use the smallest isolated and reversible validation suggestion, with explicit stop conditions.
  • Make every conclusion reviewable by another engineer from its evidence and boundary.