Karmada: Project Lightning Talk

Karmada, a CNCF incubating project, aims to offer a unified control plane for seamless deployment and management across diverse cloud environments. In this lightning talk, the following topics were covered:

• Brief introduction of Karmada
• Core Capabilities
• Key Use Cases
• Community updates

Imagine a scenario where you need to manage multiple Kubernetes clusters…

Problem Statement

Managing multiple Kubernetes clusters can be challenging.
You constantly switch between different kubeconfigs, change contexts with kubectl, and repeatedly apply configurations across clusters. This process is tedious, repetitive, and lacks a centralized management approach.

Moreover, when deploying the same application across multiple clusters, it becomes difficult to ensure everything stays synchronized.

This is where Karmada comes in.
Karmada is an open-source project, currently incubating under CNCF, designed to solve these problems. It enables centralized management of multiple Kubernetes clusters efficiently.

Architecture

Here’s a quick look at Karmada’s architecture:

• Karmada can be installed on top of an existing Kubernetes cluster.
• At the top, we have the Karmada Control Plane, and below it are the Member Clusters that Karmada manages.

This architecture is similar to the Kubernetes model itself — where a control plane manages worker nodes. In Karmada’s case, the control plane manages workloads across member clusters.

The Karmada API Server is built using the Kubernetes native API, so you can interact with it using standard kubectl commands like:

• kubectl apply -f <config>
• kubectl get deployments --cluster <cluster-name>

This makes it very intuitive for Kubernetes users.

Deployment

Deploying applications with Karmada is simple:

1. Apply your standard Kubernetes YAML files — like Deployments, Services, or ConfigMaps.
2. Define a Propagation Policy — a configuration that specifies where the resources should be deployed (i.e., which clusters).
3. Optionally, use an Override Policy to customize deployments per cluster — for example:
   • Using a different container image in certain regions.
   • Applying a different storage class based on cluster needs.

This flexibility ensures your deployments are customized but still centralized.

Scheduling

Karmada offers powerful scheduling capabilities:

• Schedule workloads based on cluster names, labels, taints, and tolerations.
• Make scheduling decisions based on available CPU, memory resources, or custom-defined weights.

This allows you to optimize where and how your applications run across clusters.

Failover

Karmada also supports automatic failover.

If a cluster becomes unavailable, Karmada gracefully migrates your workloads to healthy clusters, ensuring minimal disruption and continuous service availability.

Multicluster Service Discovery

Another standout feature is multicluster service discovery.

Karmada allows applications deployed in one cluster to seamlessly access services running in another cluster — in a Kubernetes-native way.
This means your distributed applications can talk to each other across clusters without needing complex setups.

Community

Speaking of the community — Karmada has a fast-growing, vibrant community with:

• 700+ contributors
• 70+ organizations participating

Learn more about AccuKnox
Website: https://accuknox.com/ 
Help Docs: https://help.accuknox.com/
Blogs: https://accuknox.com/blog
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