qa-resilience

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Design and test distributed-system resilience. Use when adding retries, circuit breakers, chaos experiments, or SLO-based reliability gates.

AI & Automation 87 stars 19 forks Updated 1 weeks ago MIT

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Quality Score: 83/100

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90
Frontmatter 20%
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Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# QA Resilience (Jan 2026) - Failure Mode Testing & Production Hardening This skill provides execution-ready patterns for building resilient, fault-tolerant systems that handle failures gracefully, and for validating those behaviors with tests. Core sources are curated in `data/sources.json`. ## Common Requests Use this skill when a user requests: - Circuit breaker implementation - Retry strategies and exponential backoff - Bulkhead pattern for resource isolation - Backpressure, load shedding, and overload protection - Timeout policies for external dependencies - Graceful degradation and fallback mechanisms - Health check design (liveness vs readiness) - Error handling best practices - Chaos engineering setup - Game days / DR / failover testing (with guardrails) - Production hardening strategies - Fault injection testing **When NOT to use this skill:** - Simple CRUD apps with no external dependencies — use basic error handling - Single database, no network calls — standard connection pooling sufficient - Pure batch jobs with manual retry — scheduled job frameworks handle this - Frontend-only validation — see [software-frontend](../software-frontend/SKILL.md) instead ## Quick Start (Default Workflow) If key context is missing, ask for: critical user journeys, dependency inventory (including third parties), SLO/SLI targets, current timeout/retry/circuit-breaker settings, idempotency/dedup strategy, and where fault injection is allowed (local/staging/prod). 1. Define s...

Details

Author
vasilyu1983
Repository
vasilyu1983/AI-Agents-public
Created
10 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

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