{
  "id": 16243730,
  "title": "Surviving Chaos: how ChaosEngineeringMasterDeck tests microservices resilience",
  "url": "https://urgent.news/2026/10/23/sobrevivendo-ao-caos-como-o-chaosengineeringmasterdeck-testa-a",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-10-23T23:24:32.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/maxwellsilvadev/sobrevivendo-ao-caos-como-o-chaosengineeringmasterdeck-testa-a-resiliencia-de-microsservicos-23ik"
  },
  "original_language": "pt",
  "account": "Chaos Engineering, or the practice of intentionally introducing failures into a system to test its resilience, is being used by teams to identify weaknesses and improve architecture. This approach involves formulating a hypothesis, introducing a limited failure, and observing the system's behavior to gather evidence for improvement. The ChaosEngineeringMasterDeck is a catalog of resilience experiments presented as a deck of cards, each describing a possible failure and a repeatable experiment with objectives, limits, metrics, and recovery procedures. The deck is designed to standardize and govern the practice of chaos engineering, and it contains cards with details such as identification, hypothesis, steady state, chaos variable, blast radius, observability, and criteria for aborting and recovering from the experiment. An example card, CE-004, tests the effect of high latency in a recommendations service, with the hypothesis that the catalog will still respond within 500ms and the error rate will remain below 1%.",
  "summary": "What if one service gets slow now? The important question is not if failures will happen, but if the architecture can absorb them without turning a small problem into a general unavailability. Introduction: why provoke failures on purpose? In distributed systems, an application can work perfectly under normal conditions and still fail when a dependency gets slow, a…",
  "key_points": [
    "ChaosEngineeringMasterDeck is a practical guide for testing microservices resilience",
    "Intentional controlled failures help understand system behavior in adverse situations"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}