Kubernetes

Kubernetes (K8s) has become the de facto standard for running containerized workloads at scale, providing self-healing, automated rollouts, and declarative configuration.

Why it matters

• Abstracts infrastructure differences across cloud providers and on-premises environments.
• Enables portable deployments that run consistently anywhere Kubernetes is available.
• Automates complex operational tasks like load balancing, scaling, and recovery.
• Supports microservices architectures with service discovery and configuration management.

Core concepts

• Pods: The smallest deployable units containing one or more containers.
• Services: Stable network endpoints for accessing pods.
• Deployments: Declarative updates for pods and replica sets.
• Namespaces: Virtual clusters for organizing resources and implementing multi-tenancy.
• Ingress: HTTP/HTTPS routing to services with SSL termination.

When to use Kubernetes

• You run containerized applications requiring high availability and scalability.
• Your team practices DevOps with CI/CD pipelines for frequent deployments.
• You need to avoid vendor lock-in with cloud-portable infrastructure.
• Workloads benefit from automated scaling based on demand.

Common pitfalls

• Running Kubernetes for simple workloads that don't justify the complexity.
• Not implementing RBAC (role-based access control) properly from day one.
• Overlooking resource limits leading to noisy neighbor problems.
• Failing to secure container images and implement admission controllers.
• Not planning for persistent storage and stateful workload requirements.

Managed Kubernetes services

• AWS: Elastic Kubernetes Service (EKS).
• Azure: Azure Kubernetes Service (AKS).
• Google Cloud: Google Kubernetes Engine (GKE).