ahmetb/kubectl-tree

kubectl plugin to browse Kubernetes object hierarchies as a tree 🎄 (star the repo if you are using)

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Summary Information

Updated 12 minutes ago
Added to GitGenius on September 20th, 2026
Created on December 23rd, 2019
Open Issues & Pull Requests: 16 (+0)
GitHub issues: Enabled
Number of forks: 137
Total Stargazers: 3,436 (+0)
Total Subscribers: 17 (+0)

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Open issues: 2
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,279 days
Stale 30+ days: 2
Stale 90+ days: 2

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Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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  • enhancement (1)

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Detailed Description

kubectl-tree is a kubectl plugin that visualizes Kubernetes object hierarchies as a tree by traversing ownership relationships.

The tool solves the problem of understanding how Kubernetes objects relate to and depend on one another. It works by examining the ownerReferences field on objects to build a tree structure showing parent-child relationships. This approach reveals the complete ownership chain from high-level constructs like Deployments down through ReplicaSets to individual Pods, and works across any Kubernetes API objects that maintain these references.

The plugin suits operators and developers who need to understand object dependencies in their clusters, particularly when debugging or exploring complex workloads. It works well for standard Kubernetes objects and custom resources that properly set ownerReferences. The tool offers filtering capabilities to manage query scope and performance in large clusters: you can filter by namespace, API groups, resource types, and labels. You can also specify which condition types to check and control color output. The README mentions that kubectl lineage is a similar alternative that understands logical relationships between objects without requiring ownerReferences, making it useful when ownership chains are incomplete.

The project shows consistent maintenance with regular updates addressing user-reported issues and feature requests. Development activity includes responsiveness to bug reports and pull requests, with fixes deployed promptly when problems are identified. The maintainer actively incorporates community feedback to improve the tool's filtering capabilities and documentation.