A best practices checker for Kubernetes clusters that analyzes resources and provides actionable feedback.
Clusterlint is a best practices checker for Kubernetes clusters that analyzes live resources to identify configuration issues around resources, security, and reliability. It helps operators avoid common problems during cluster operation or upgrades by providing actionable feedback without altering configurations. The tool supports both common checks and platform-specific checks for environments like DigitalOcean Kubernetes (DOKS).
Kubernetes cluster operators, DevOps engineers, and platform teams responsible for maintaining and scaling production Kubernetes clusters. It's particularly useful for teams managing large or complex deployments across multiple environments.
Developers choose Clusterlint because it provides a non-invasive, external tool that focuses on live cluster analysis rather than static configuration files. Its platform-specific checks and flexible grouping system allow tailored audits, while plugin support enables customization for organization-specific best practices.
A best practices checker for Kubernetes clusters. 🤠
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Queries and analyzes all resources in a running Kubernetes cluster, providing real-time insights unlike static analyzers that only check manifest files, as highlighted in the README's background section.
Includes tailored checks for environments like DigitalOcean Kubernetes (DOKS) and AWS, addressing issues such as hostname changes after upgrades, which helps avoid platform-specific pitfalls.
Allows operators to run or exclude specific check groups (e.g., basic, security) and individual checks via command-line options, enabling focused audits without unnecessary noise.
Runs externally without modifying any cluster resources or configurations, ensuring safety during audits as emphasized in the project description.
Clusterlint only identifies issues and provides feedback; it doesn't fix problems automatically, requiring manual intervention from operators, which can be time-consuming in large clusters.
Building custom checks via Go plugins involves significant overhead, and the README warns about caveats and maintenance challenges, making it less accessible for teams without Go expertise.
Running clusterlint within a cluster requires Docker image building, RBAC configuration, and CronJob setup, as shown in the documentation, adding complexity compared to simpler command-line tools.