{"id":49587,"date":"2022-12-02T00:00:00","date_gmt":"2022-12-02T00:00:00","guid":{"rendered":"urn:uuid:ce68f368-6a53-bddd-8870-dd8521ef250b"},"modified":"2022-12-02T00:00:00","modified_gmt":"2022-12-02T00:00:00","slug":"why-chaos-engineering-is-a-good-stress-test-strategy","status":"publish","type":"post","link":"https:\/\/www.threatshub.org\/blog\/why-chaos-engineering-is-a-good-stress-test-strategy\/","title":{"rendered":"Why Chaos Engineering is a Good Stress Test Strategy"},"content":{"rendered":"

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Expect the unexpected. This adage is perhaps one of the best slogans for testing distributed software. But how exactly do you test for the unexpected? Chaos engineering gets close to the answer.<\/p>\n

Chaos engineering helps you design more resilient systems. This is achieved by forcing you to think about how these systems will respond to unexpected events. It gives you confidence that your system will be able to handle real-world conditions, not just the idealized conditions that are often assumed during development and testing.<\/p>\n

So, what is chaos engineering? It\u2019s a method of resilience testing that intentionally introduces \u201cchaos\u201d into a system to discover vulnerabilities and weaknesses that can be exploited by attackers. Essentially, it\u2019s stress testing through anarchy: randomly terminating processes, injecting faults into networks, or causing other types of failures.<\/p>\n

The origins of chaos engineering can be traced back to Netflix’s “Simian Army” project<\/a>, which was designed to test the streaming service\u2019s ability to withstand outages and failures. Since then, many other companies have adopted similar practices.<\/p>\n

Chaos engineering as a testing strategy<\/span><\/p>\n

Anyone who\u2019s been involved in distributed software development understands that software testing identifies errors, gaps, or missing requirements.<\/p>\n

Software testing can be executed manually (by running through the steps yourself), automatically (with specialized tools), or a combination of both approaches (manual exploratory testing supplemented by automated regression checks). Automation is often leveraged in regression testing since this approach requires retesting software after implementing changes. This guarantees they haven\u2019t inadvertently introduced new bugs or broken existing functionality. It also provides faster feedback and more comprehensive coverage than manual testing alone.<\/p>\n

However, it also requires extra effort upfront to develop reliable test scripts that don’t produce false positives\/negatives. Generally, which approach to take depends on factors that include team size\/skillset, application complexity, and time constraints.<\/p>\n

The types of software tests depend on their purpose; for example:<\/p>\n