Quantum computing is entering the same messy adolescence that distributed systems once faced: incredibly powerful in theory, constantly unstable in practice. We build dazzling algorithms, run them on noisy hardware, and then… watch them crumble. So what if we stopped pretending the quantum world is neat and instead did what SREs and DevOps engineers have done for decades—break it on purpose?

Welcome to the Quantum Chaos Monkey—a Python‑based use case that brings the spirit of chaos engineering into the era of qubits and entanglement. Inspired by Netflix’s Chaos Monkey and fault‑injection practices in DevOps, this tool systematically destabilizes quantum circuits to reveal how they fail and how they recover. Using Qiskit and QuTiP, it attacks widely studied algorithms by injecting randomized noise, gate faults, and decoherence spikes. Each run captures metrics such as fidelity loss, success probability, and energy deviation, allowing engineers and researchers to visualize the difference between “robust” and “fragile” quantum solutions.