Building Large-Scale, Highly Available Kubernetes Clusters

Designing large-scale, highly available Kubernetes clusters demands a strategic approach to ensure scalability, resilience, and operational efficiency.

The architecture should prioritize fault tolerance by deploying the cluster across multiple availability zones or regions, ensuring no single point of failure disrupts operations.

In the feature video ‘No More Disruption: PlayStation Network’s Approaches To Avoid Outages on Kubernetes Platform’, Tomoyuki Ehira & Shuhei Nagata document their Kubernetes platform at PlayStation Network.

With 50+ clusters this handles massive amounts of user traffic every day, and the platform team consists of engineers in several global locations with different technological and cultural backgrounds. Despite such scale and organizational complexity, they achieved remarkable stability in FY2024 so far, maintaining a notable 99.995% uptime.

Architecture Blueprint

The control plane, critical to cluster management, requires at least three nodes to maintain high availability for components like the API server, scheduler, and controller manager.

These nodes should leverage an external load balancer to distribute traffic effectively, while etcd, the cluster’s data store, must be configured in a clustered setup with an odd number of instances for quorum-based consensus. Securing etcd with TLS and regular backups is essential to protect against data loss and ensure recoverability.

Worker nodes form the backbone of workload execution and must be designed for both horizontal and vertical scaling. Using node pools tailored to specific workload types, such as CPU- or memory-intensive tasks, optimizes resource utilization. Auto-scaling mechanisms, like the Kubernetes Cluster Autoscaler, dynamically adjust node counts based on demand, while resource requests and limits prevent contention.

Networking is another critical aspect, requiring a robust Container Network Interface (CNI) plugin, such as Cilium or Calico, to support low-latency, secure communication. For complex microservices environments, a service mesh like Istio can enhance traffic management and observability. Ingress controllers paired with a CDN ensure efficient external traffic routing and protection against threats like DDoS attacks.

Security is non-negotiable in large-scale clusters. Implementing Role-Based Access Control (RBAC), network policies, and secrets management with tools like HashiCorp Vault safeguards the cluster. Pod Security Standards and image scanning further mitigate risks.

Observability is equally vital, with centralized monitoring via Prometheus and Grafana, coupled with logging solutions like Loki or Elasticsearch, enabling proactive issue detection. Distributed tracing with Jaeger can provide insights into microservices performance. For automation, adopting GitOps with tools like ArgoCD ensures declarative, version-controlled deployments, while Infrastructure as Code tools like Terraform streamline cluster provisioning.

High availability extends to disaster recovery, with multi-zone deployments, regular backups using tools like Velero, and chaos engineering to test resilience. Cost optimization, through tools like Kubecost and the use of spot instances, balances performance with budget constraints. Regular upgrades and patch management keep the cluster secure and efficient.

This blueprint, tailored to specific needs and cloud providers, ensures a robust, scalable Kubernetes deployment ready for enterprise demands.