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Kubernetes

The industry-standard container orchestration platform for automating deployment, scaling, and management of containerized workloads across clusters of machines.

Overview

Kubernetes (K8s) is a production-grade container orchestration system originally developed by Google and now maintained by the Cloud Native Computing Foundation (CNCF). It implements a desired-state model where controllers continuously reconcile actual state with declared intent. Kubernetes manages the full lifecycle of containerized applications: scheduling, scaling, networking, storage, and self-healing.

Repository & Community

Attribute Detail
Repository github.com/kubernetes/kubernetes
Stars ~115k+ ⭐
Latest Stable v1.35.3 (April 2026); v1.36 due April 22, 2026
Language Go
License Apache 2.0
Governance CNCF (Linux Foundation)
Contributors 9,000+

Evaluation

  • Why it's better: Cloud-agnostic, massive ecosystem (CNCF landscape), declarative config, self-healing, horizontal pod autoscaling, service discovery, rolling updates, and the dominant industry standard for container orchestration.

  • When it fits (Applicability):

  • Microservices at scale across multiple nodes
  • CI/CD with automated rollouts and rollbacks
  • Multi-cloud / hybrid cloud portability
  • Stateful workloads with persistent volumes
  • AI/ML training and inference pipelines

  • Edge deployments (K3s, MicroK8s)

  • Pros and Cons:

Pros Cons
Cloud-agnostic, runs anywhere Steep learning curve
Self-healing, auto-scaling Complex networking (CNI plugins)
Massive CNCF ecosystem Control plane overhead for small workloads
Declarative desired-state model YAML verbosity
Service mesh, Ingress, Gateway API Security hardening requires expertise
GPU/DRA scheduling for AI/ML etcd operational complexity
Every major cloud offers managed K8s Not ideal for traditional VM workloads

Architecture

flowchart TB
    subgraph ControlPlane["Control Plane"]
        API["kube-apiserver\n(REST + gRPC)"]
        ETCD["etcd\n(distributed KV store)"]
        Sched["kube-scheduler\n(pod placement)"]
        CM["kube-controller-manager\n(reconciliation loops)"]
        CCM["cloud-controller-manager\n(cloud API integration)"]
    end

    subgraph WorkerNode["Worker Node"]
        Kubelet["kubelet\n(pod lifecycle)"]
        KProxy["kube-proxy\n(Service networking)"]
        CRI["Container Runtime\n(containerd / CRI-O)"]
        Pods["Pods\n(application containers)"]
    end

    API <-->|"watch/list"| ETCD
    Sched -->|"bind pod"| API
    CM -->|"reconcile"| API
    CCM -->|"cloud ops"| API
    Kubelet -->|"status"| API
    API -->|"spec"| Kubelet
    Kubelet -->|"CRI"| CRI
    CRI --> Pods
    KProxy -->|"iptables/IPVS"| Pods

    style ControlPlane fill:#326ce5,color:#fff
    style WorkerNode fill:#1565c0,color:#fff

Key Features

Feature Detail
Pod Scheduling Affinity, anti-affinity, taints, tolerations, topology spread
Auto-Scaling HPA (horizontal), VPA (vertical), Cluster Autoscaler
Service Discovery ClusterIP, NodePort, LoadBalancer, ExternalName
Ingress / Gateway API L7 traffic routing, TLS termination
Storage PV, PVC, CSI drivers, StorageClasses
ConfigMaps / Secrets Externalized configuration and credentials
RBAC Fine-grained role-based access control
Namespaces Logical cluster partitioning
DRA (v1.36) Dynamic Resource Allocation for GPUs, FPGAs
Custom Resources Extend API with CRDs + Operators

Key Ecosystem

Category Tools
Managed K8s EKS, GKE, AKS, DOKS, OKE, Linode LKE
Lightweight K3s, MicroK8s, Kind, Minikube
Networking Calico, Cilium, Flannel, Antrea
Service Mesh Istio, Linkerd, Consul Connect
GitOps ArgoCD, Flux
Observability Prometheus, Grafana, OpenTelemetry
Security Falco, OPA/Gatekeeper, Trivy, Kyverno

Pricing

Offering Cost Notes
Self-hosted Free (Apache 2.0) You manage everything
AWS EKS $0.10/hr/cluster + node costs Managed control plane
GKE Autopilot $0.10/hr/cluster + pod costs Fully managed
Azure AKS Free control plane + node costs Managed
Enterprise Various (Rancher, OpenShift, Tanzu) Support + add-ons

Compatibility

Dimension Support
Container runtimes containerd (default), CRI-O
Node OS Linux (primary), Windows (worker nodes)
CPU architecture amd64, arm64, arm/v7, s390x, ppc64le
Storage CSI (Ceph, EBS, GCE PD, Azure Disk, NFS, etc.)
Networking CNI plugins (Calico, Cilium, Flannel, etc.)
Infrastructure Bare metal, VMs, any cloud, edge

Scale Limits (Upstream)

Dimension Limit
Nodes per cluster 5,000
Pods per node 110 (default)
Pods per cluster 150,000
Services per cluster 10,000
Namespaces per cluster 10,000

Sources