How to create a fault-tolerant Kubernetes cluster?

To create a highly available Kubernetes cluster, it is necessary to ensure redundancy of key components and data.

Main steps:

1. Master Nodes:

   • Deploy multiple master nodes (at least three) for the kube-apiserver component, running behind a load balancer. This ensures API server availability even if one master node fails.
   • Each master node should have access to a shared cluster state storage — etcd.

2. etcd:

   • Deploy an etcd cluster of multiple nodes (recommended odd number, at least three), distributed across different availability zones or physical servers. This guarantees data integrity of the cluster state.

3. Load Balancer:

   • Use an L4/L7 load balancer to distribute traffic among master nodes (kube-apiserver).
   • Use another load balancer for incoming traffic to cluster applications (e.g., Ingress Controller with high availability support).

4. Worker Nodes:

   • Deploy enough worker nodes to run Pods.
   • Distribute worker nodes across different availability zones or physical servers to ensure resilience against infrastructure failures.
   • Configure Pod Disruption Budgets (PDBs) to define the minimum number of available Pods during voluntary disruptions (e.g., node updates).

5. Storage:

   • Use distributed or cloud storage with built-in high availability for Persistent Volumes.
   • Examples: Rook (Ceph), GlusterFS, cloud providers (AWS EBS, GCP Persistent Disk, Azure Managed Disks) with replication.

6. Networking:

   • Use a reliable CNI (Container Network Interface) solution supporting high availability (e.g., Calico, Cilium with replicated components).
   • Ensure connectivity between master nodes, etcd nodes, and worker nodes.

7. Backup:

   • Regularly back up etcd data.
   • Use tools like Velero for backup and restore of cluster state and Persistent Volumes.

Example architecture:

graph LR
    subgraph Users
        A[User] --> B(Application Traffic Load Balancer)
    end

    subgraph Kubernetes Cluster
        subgraph Master Nodes
            C1(Master Node 1)
            C2(Master Node 2)
            C3(Master Node 3)
        end

        subgraph etcd Cluster
            D1(etcd 1)
            D2(etcd 2)
            D3(etcd 3)
        end

        subgraph Worker Nodes
            E1(Worker Node 1)
            E2(Worker Node 2)
            E3(Worker Node 3)
        end

        subgraph Storage
            F(Distributed Storage)
        end

        subgraph Network
            G(CNI Network)
        end

        B --> LoadBalancer(API Server)
        LoadBalancer --> C1
        LoadBalancer --> C2
        LoadBalancer --> C3

        C1 <--> D1
        C1 <--> D2
        C1 <--> D3
        C2 <--> D1
        C2 <--> D2
        C2 <--> D3
        C3 <--> D1
        C3 <--> D2
        C3 <--> D3

        C1 --> G
        C2 --> G
        C3 --> G

        E1 <--> G
        E2 <--> G
        E3 <--> G

        E1 <--> F
        E2 <--> F
        E3 <--> F

        G --> E1: Pod Deployment
        G --> E2: Pod Deployment
        G --> E3: Pod Deployment

        E1 --> B: Application Traffic
        E2 --> B: Application Traffic
        E3 --> B: Application Traffic
    end

Automation tools such as kubeadm, Kubespray, or managed Kubernetes services (EKS, GKE, AKS) are used during deployment to simplify the creation of a highly available infrastructure.