Practice the vocabulary of deliberately testing a system's resilience to failure.
0 / 5 completed
1 / 5
At standup, a dev mentions deliberately injecting a failure, like killing a service instance, into a production-like environment to verify the system recovers gracefully. What practice is this?
Chaos engineering deliberately injects a controlled failure, like killing a service instance, into a production-like environment to verify the broader system recovers gracefully rather than cascading into a larger outage. This proactively surfaces a weakness in the system's resilience before it's discovered during an actual unplanned incident. It's a deliberate, planned practice, distinct from an unplanned accidental outage that just happens to occur.
2 / 5
During a design review, the team wants to define upfront what normal, healthy system behavior looks like, so a chaos experiment can clearly detect a deviation from it. Which capability supports this?
Establishing a steady-state hypothesis before running an experiment defines what normal, healthy system behavior looks like, so a deviation caused by the injected failure can be clearly detected and measured. Running an experiment with no defined baseline makes it hard to tell whether an observed effect is actually caused by the injected failure or is just normal variation. This upfront hypothesis is a foundational step in a well-designed chaos experiment.
3 / 5
In a code review, a dev notices the chaos experiment is scoped to a small percentage of traffic in a controlled environment, with an automated mechanism to immediately stop the experiment if impact grows too large. What does this represent?
A blast radius limit scopes an experiment to a small, controlled portion of traffic, paired with an automated mechanism to immediately halt the experiment if its impact grows larger than expected. Running an experiment against all production traffic with no scoping risks turning a controlled learning exercise into an actual widespread outage. This scoping and automated abort capability is what makes chaos engineering safe enough to responsibly run in a real production environment.
4 / 5
An incident report shows a chaos experiment was run without an automated abort mechanism, and an injected failure cascaded into a broader outage that took far longer to recover from than intended. What practice would prevent this?
Including a scoped blast radius and automated abort mechanism before running an experiment against a live system ensures an injected failure that starts cascading unexpectedly gets stopped quickly rather than spiraling into a larger outage. Assuming a failure will always stay naturally contained ignores exactly the kind of cascading behavior chaos engineering exists to uncover. This safeguard is what separates a responsibly run chaos experiment from a reckless one.
5 / 5
During a PR review, a teammate asks why the team deliberately injects failures into a production-like environment instead of relying solely on unit and integration tests to verify system resilience. What is the reasoning?
Unit and integration tests typically run in isolation and can't fully capture how a complete, real system with all its actual dependencies behaves under a genuine failure condition. Deliberately injecting a failure into a production-like environment reveals real cascading effects and recovery behavior those isolated tests can't reach. The tradeoff is the added operational risk and care required to run this kind of experiment safely against a live-like system.
What does the "Chaos Engineering Vocabulary" vocabulary exercise cover?
This exercise tests real IT vocabulary related to chaos engineering vocabulary through 5 multiple-choice questions, each built from realistic workplace sentences rather than abstract definitions.
Is this vocabulary exercise free to use?
Yes. Every exercise on CoderSlingo, including this one, is completely free — no account, sign-up, or payment required.
How many questions does this exercise have?
This exercise has 5 questions. Each one shows a real-world sentence or scenario with multiple-choice options and an explanation once you answer.
What happens after I answer a question?
You'll see immediate feedback showing whether your answer was correct, along with a short explanation of why — then a button to move to the next question, and a full results screen at the end.
Can I retry the exercise if I get questions wrong?
Yes. Once you reach the results screen, click "Try again" to reset your answers and go through the exercise from the start as many times as you like.
Do I need to create an account to take this exercise?
No account is needed. Your answers are scored in your browser during the session — nothing is saved to a server, so you can jump straight in.
Is my progress saved if I leave the page?
No — progress within an exercise resets if you navigate away or reload. Each exercise is short enough to complete in a few minutes in one sitting.
Are these vocabulary exercises connected to other topics?
Yes — this module shares real-world context with 11 other vocabulary modules. See "Related vocabulary" below to keep building a connected skill set.
How is this different from reading a glossary or blog article?
Exercises like this one are active recall drills — you have to choose the correct term or phrasing yourself, which builds retention faster than passively reading a definition.
Where can I find more vocabulary exercises?
Browse the full Vocabulary exercises hub for hundreds of modules covering Agile, DevOps, security, databases, architecture, and more — organised by IT role and skill.