kube-monkey

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Introduction

kube-monkey is an implementation of Netflix’s Chaos Monkey for Kubernetes clusters. It randomly deletes pods in the cluster, encouraging and validating the development of failure-resilient services.

Apps opt in with labels that set their mean time between failures and kill mode, terminations happen during the hours and days you configure, and a dry-run mode shows what would be killed. It installs via a Helm chart into the cluster.

In the quality loop kube-monkey continuously checks that services survive pod loss.

The source code is at asobti/kube-monkey on GitHub under the Apache-2.0 licence, with about 3,100 stars; the most recent commit was on 20 September 2026.

Features

1. Opt-in labels: Workloads choose to participate.
2. Schedules: Run during configured hours.
3. Kill modes: Single pod, fixed number or percentage.
4. Dry run: Preview terminations.
5. Helm chart: Simple install.
6. Notifications: Optional alerts on kills.

Pros

1. Simple and focused: Easy to understand and run.
2. Free to use: Open source under the Apache-2.0 licence, so the core tool costs nothing to use.
3. Actively maintained: The repository had commits as recent as 20 September 2026.
4. Community: About 3,100 GitHub stars.

Cons

1. Pod deletion only: No network or resource faults.
2. Randomness: Not suited to targeted experiments.
3. Limited reporting: No experiment analysis.

Usage and Links (Example)

helm repo add kubemonkey https://asobti.github.io/kube-monkey/charts/repo
helm install kube-monkey kubemonkey/kube-monkey --namespace kube-system

Resources:

• kube-monkey website

Pricing

kube-monkey is free and open source under the Apache-2.0 licence.

Recommended for?

1. Kubernetes teams starting chaos engineering.

Conclusion

kube-monkey is an easy first step into continuous chaos on Kubernetes.

Move to richer tools for targeted experiments.

On CheckOps, kube-monkey is filed under the Production monitoring & observability stage. Related tools listed here include Chaos Mesh, LitmusChaos, Chaos Toolkit, Gremlin, Steadybit and Toxiproxy. Before standardising on one, compare recent maintenance activity, the pricing model as your usage grows, and the integrations you rely on today. Information on this page was verified against the official website, documentation and repository on 11 November 2026.