Kubernetes System Design Interview Prep
Master Kubernetes system design interviews with a structured framework, real-world scenarios, and quantitative reasoning. Covers HA, multi-tenancy, networking, security, and cost — everything asked at senior and staff-level interviews.
One-time payment. Lifetime access.
What you'll learn
Curriculum
10 modules · 30 lessonsInterview Framework
How to actually approach a K8s system design interview — the format, the framework, and anti-patterns that cost offers.
Cluster Sizing & Capacity Planning
Quantitative reasoning for cluster design — pod density, node math, etcd limits, and when to split.
High Availability Design
Design multi-AZ HA clusters, multi-region active-active, and reason about availability targets with quantitative rigor.
Stateful Workload Design
Architect stateful workloads on Kubernetes — PostgreSQL, Kafka, and ElasticSearch with proper storage, replication, and failover.
Multi-Tenancy & Isolation
Design multi-tenant Kubernetes platforms with the right isolation boundaries — namespaces, vClusters, and separate clusters.
Networking System Design
Service-to-service communication at scale, global ingress, and zero-trust network policies.
Scalability & Performance
Design autoscaling, massive-scale clusters, and global rate limiting with quantitative reasoning.
Reliability & Disaster Recovery
Design for disaster recovery, safe production deploys, and chaos engineering that actually finds bugs.
Security & Compliance
Design pod security for regulated industries, secrets management at scale, and audit logging for compliance.
Cost & Operations
Design FinOps for massive K8s spend, GitOps for 100+ microservices, and observability that doesn't cost more than the infra.
About the Author
Sharon Sahadevan
AI Infrastructure Engineer
Building production GPU clusters on Kubernetes — H100s, large-scale model serving, and end-to-end ML infrastructure across Azure and AWS.
10+ years designing cloud-native platforms with deep expertise in Kubernetes orchestration, GitOps (Argo CD), Terraform, and MLOps pipelines for LLM deployment.
Author of KubeNatives, a weekly newsletter read by 3,000+ DevOps and ML engineers for production insights on K8s internals, GPU scheduling, and model-serving patterns.