K-Atlas (pronounced Cutlass), is a distributed graph based platform to automatically collect, discover, explore and relate multi-cluster Kubernetes resources and metadata. K-Atlas's rich query language allows for simple and efficient exploration and extensibility.

It addresses following problems in a large scale enterprise environment of Kubernetes.

• Discoverability
  • Find K8s objects across multiple distributed K8s clusters
  • Real-time view of discovered objects
  • Streaming APIs and UI for both programmatic and human interactions
• Advanced Exploration
  • Identify similarities and differences between objects from pods to clusters
  • Correlate different objects by performing advanced join operations
• Federated Application View
  • Applications take center stage. K-Atlas provides a unique, application-centric view, with metadata from multiple clusters
  • Single pane of glass view of the entire application - from edge to database, across all clusters, regions etc.
• Reporting
  • Provide advanced reporting on compliance, security and other organizational policies
• Policy Enforcement
  • Allow for organizational policies to be enforced across the fleet in a consistent manner

Check out more details on Motivation and Use Cases that K-Atlas is addressing.

It provides a Web Viewer that can be used to search the Kubernetes cluster data and view graphical results in real time.

Click on the thumbnail below to see a demo video.

The collector is responsible for discovery of Kubernetes assets in Kubernetes Clusters. For details on the Collector design, please refer Design Concepts

The K-Atlas Service exposes APIs that can be used to get details about Kubernetes entities and run queries to help diagnose issues in Kubernetes clusters. For details , please refer K-Atlas APIs

The Web Application exposes UI search capability to search clusters based on several criteria and provide a real time graphical view of entities. For details on usage, please Click here to see a demo

Dgraph is used as the graph database. To know more about our motivation to choose Dgraph, please refer Design Concepts

Make sure you have the following prerequisites:

• A local Go 1.7+ development environment.
• Access to a Kubernetes cluster.

How to Set Up.

• QSL query support
• Dynamic search result layout based on QSL
• Graph view based on QSL query required objects & relationships
• Pagination support for both API and UI
• Custom metadata definition via new API

More details about specific K-Atlas features are at Release Notes.

We encourage you to get involved with K-Atlas, as users or contributors and help with code reviews.

Read the contributing guidelines to learn about building the project, the project structure, and the purpose of each package.