The world of Chaos Engineering is often misunderstood. For many, it’s seen as “breaking things on purpose” or a concept reserved only for tech giants like Netflix and AWS. But these views couldn’t be further from the truth. In fact, these misconceptions can prevent teams from adopting one of the most powerful practices for system resilience.
Today, as part of our 10 Days of Christmas Chaos series, we’re tackling “The Naughty List” — a list of 10 common myths about Chaos Engineering. We’ll debunk each one, explain why it’s incorrect, and share how you can avoid falling for these misconceptions.
By the end of this post, you’ll have a clearer understanding of what Chaos Engineering is (and isn’t) — and hopefully, the courage to run your first chaos experiment. Let’s get started! 🎄
🎅 Myth 1: Chaos Engineering is about breaking production
The Myth
“Chaos Engineering means breaking stuff in production just to see what happens.”
The Reality
Chaos Engineering isn’t about “breaking” production — it’s about controlled, thoughtful experimentation. While it’s true that many teams choose to run experiments in production, it’s done with clear guardrails. The goal is to uncover hidden weaknesses before they cause unplanned outages.
The Truth
- Experiments are designed to be safe, with controlled “blast radius” (so only small parts of the system are affected).
- You can (and should) start chaos experiments in staging or pre-production environments.
- The goal is to build confidence in the system, not cause chaos for the sake of it.
🎅 Myth 2: Chaos Engineering requires a dedicated chaos team
The Myth
“You need a dedicated ‘chaos team’ to do Chaos Engineering.”
The Reality
While large organizations like Netflix may have entire teams dedicated to Chaos Engineering, that’s not a requirement for everyone. Most teams integrate chaos practices into their existing SRE, DevOps, or platform engineering workflows.
The Truth
- Any team responsible for system reliability can practice Chaos Engineering.
- Tools like Gremlin, Azure Chaos Studio, and Litmus Chaos make it easy to run experiments with minimal setup.
- It’s better to run small, regular experiments with existing teams than to rely on a “chaos specialist.”
🎅 Myth 3: Chaos Engineering is only for big tech companies
The Myth
“Only big tech companies like Netflix, AWS, and Google need Chaos Engineering.”
The Reality
While big tech popularized Chaos Engineering, companies of all sizes can benefit from it. The core goal of Chaos Engineering is to ensure that your system can handle failures — something that’s just as important for small startups as it is for tech giants.
The Truth
- Chaos Engineering helps small startups build resilience early and avoid costly outages later.
- Cloud providers (like AWS, Azure, and GCP) offer tools for Chaos Engineering, so small teams don’t need to build everything from scratch.
- Even if you’re running a small Kubernetes cluster, it’s worth running failure simulations to see how your system handles them.
🎅 Myth 4: Chaos Engineering is about causing outages
The Myth
“Chaos Engineering is just about causing outages.”
The Reality
This is one of the most persistent (and dangerous) myths about Chaos Engineering. The goal is to create confidence, not chaos. Outages aren’t the goal — resilience is.
The Truth
- The purpose of Chaos Engineering is to prevent unplanned outages, not cause them.
- Teams use Chaos Engineering to discover failure modes before they happen naturally.
- Every experiment has a hypothesis (e.g., “If we kill this node, will the service failover correctly?”). If the hypothesis is wrong, you learn and improve.
🎅 Myth 5: Chaos Engineering is too risky
The Myth
“If we run chaos experiments, we’ll risk bringing down our entire system.”
The Truth
- Blast radius controls ensure that only small parts of the system are affected during experiments.
- You can (and should) start by running experiments in staging or test environments.
- If you’re using tools like Gremlin or Azure Chaos Studio, you can pause or stop experiments instantly if something goes wrong.
🎅 Myth 6: Chaos Engineering is only about testing hardware failures
The Myth
“Chaos Engineering is only useful for testing hardware or network failures.”
The Truth
- Chaos Engineering can test failures in software logic, databases, third-party APIs, and more.
- Teams use Chaos Engineering to simulate DNS failures, API rate-limiting, CPU spikes, and more.
- People and process failures (like on-call team response times) can also be tested.
🎅 Myth 7: Chaos Engineering is expensive
The Truth
- Many chaos tools are open-source and free (like Litmus Chaos).
- Cloud providers like AWS and Azure offer Chaos Engineering tools with pay-as-you-go models.
- Small experiments cost far less than a large, unplanned outage.
🎅 Myth 8: You have to run chaos experiments in production
The Truth
- Start in staging or test environments.
- Production experiments are useful but not required.
- Production chaos is often the last step in a mature Chaos Engineering program.
🎅 Myth 9: Chaos Engineering is only for Kubernetes environments
The Truth
- Chaos Engineering works on any system — VMs, cloud infrastructure, APIs, databases, and more.
- Kubernetes tools (like Litmus Chaos) get attention, but you can run chaos on legacy systems too.
🎅 Myth 10: Chaos Engineering requires technical experts
The Truth
- Anyone with knowledge of system behavior can design a chaos experiment.
- Chaos platforms offer simple GUIs to create experiments without code.
- No need to be an SRE to run chaos experiments.
What Myths Have You Heard?
These 10 myths are just the beginning. Chaos Engineering is growing, and so are the misconceptions. Have you heard (or believed) any of these myths before? What’s the wildest myth you’ve heard?
Drop your myth in the comments and we might feature it in a future post!
