Kubernetes is an open-source container orchestration platform automating deployment, scaling, and management of containerised applications. Kubernetes automates complex tasks like service discovery, load balancing, rolling updates, and self-healing. Originally developed by Google, Kubernetes has become the industry standard for managing containers at scale.
Kubernetes Fundamentals
Core Kubernetes concepts:
Clusters - Groups of machines running containerised applications.
Nodes - Individual machines in clusters.
Pods - Smallest deployable units containing one or more containers.
Deployments - Managing replicated pods, rolling updates, and rollbacks.
Services - Exposing pods as network services.
Namespaces - Logical isolation within clusters.
Understanding these concepts is essential for Kubernetes usage.
Pod Concepts
Pods are Kubernetes primitive:
Multi-container pods - Pods can contain multiple containers sharing network.
Sidecar containers - Supporting containers (logging, monitoring) alongside main container.
Init containers - Containers running before main containers.
Lifecycle hooks - Running code during pod lifecycle events.
Resource requests and limits - Defining memory and CPU requirements.
Pods abstract container details enabling Kubernetes orchestration.
Deployments
Managing application replicas:
Replicas - Number of pod copies running.
Scaling - Increasing or decreasing replica count.
Rolling updates - Gradually updating pods to new versions.
Rollback - Reverting to previous versions if updates fail.
Health checks - Restarting unhealthy pods.
Update strategies - Controlling how updates proceed (rolling, blue-green).
Deployments ensure applications scale and update reliably.
Services
Exposing pods:
Service types - ClusterIP (internal), NodePort (external), LoadBalancer (cloud).
Service discovery - Pods discovering services by name.
Load balancing - Distributing traffic across pod replicas.
Endpoints - Individual pods serving service.
Session affinity - Routing requests from client to same pod.
Ingress - External access to services.
Services abstract pod locations enabling resilience and scaling.
Configuration Management
Managing configuration:
ConfigMaps - Storing configuration data.
Secrets - Storing sensitive data.
Environment variables - Passing configuration to containers.
Configuration files - Mounting config files in containers.
ConfigMap updates - Updating configuration without redeploying.
Secret rotation - Changing secrets securely.
Effective configuration management enables flexible, secure deployments.
Storage
Managing application data:
Volumes - Persistent storage for pods.
PersistentVolumes (PVs) - Cluster-level storage resources.
PersistentVolumeClaims (PVCs) - Requesting storage.
Storage classes - Dynamic provisioning of storage.
StatefulSets - Managing stateful applications requiring stable storage.
Storage management enables applications with data persistence.
Networking
Kubernetes networking:
Cluster DNS - Service discovery by name.
Network policies - Controlling pod-to-pod communication.
Ingress - External traffic routing.
Network plugins - Enabling various networking models.
Service mesh - Advanced networking for microservices.
Networking enables pod communication and external access.
Resource Management
Managing cluster resources:
Requests - Resources guaranteed for pods.
Limits - Maximum resources pods can use.
QoS classes - Quality of service tiers.
Cluster autoscaling - Automatically adding nodes when needed.
Node affinity - Controlling pod placement on nodes.
Taints and tolerations - Constraining pod placement.
Effective resource management maximises cluster utilisation.
Kubernetes at PixelForce
PixelForce uses Kubernetes (AWS EKS) for orchestrating containerised applications. Kubernetes enables deploying applications reliably, scaling automatically, and managing updates safely. For complex applications requiring sophisticated orchestration, Kubernetes is the standard.
Monitoring and Logging
Understanding cluster and application health:
Prometheus - Collecting metrics from applications and Kubernetes.
Grafana - Visualising metrics.
ELK stack - Aggregating logs.
Jaeger - Distributed tracing.
Custom dashboards - Monitoring application-specific metrics.
Comprehensive monitoring enables understanding and optimising systems.
Security in Kubernetes
Securing clusters:
RBAC - Role-based access control.
Network policies - Controlling pod communication.
Pod security policies - Constraining pod capabilities.
Secrets management - Protecting sensitive data.
Image scanning - Scanning container images for vulnerabilities.
Audit logging - Tracking cluster changes.
Security requires attention across multiple dimensions.
Helm
Package management for Kubernetes:
Helm charts - Templated Kubernetes manifests.
Chart repositories - Sharing charts.
Values - Customising charts.
Releases - Installing chart instances.
Chart versioning - Managing chart versions.
Helm simplifies Kubernetes application management.
StatefulSets
Managing stateful applications:
Stable identity - Pods have predictable names and hostnames.
Persistent storage - Each pod gets persistent storage.
Ordered deployment - Pods deployed in order.
Ordered updates - Updates proceed in order.
Databases and caches - StatefulSets for applications needing state.
StatefulSets enable running stateful applications in Kubernetes.
Jobs and CronJobs
Running batch workloads:
Jobs - One-time batch workloads.
CronJobs - Scheduled batch workloads.
Parallelism - Running multiple job instances.
Backoff policy - Retrying failed jobs.
Cleanup - Removing completed jobs.
Jobs and CronJobs enable Kubernetes for batch processing.
Custom Resources
Extending Kubernetes:
Custom Resource Definitions (CRDs) - Defining custom resource types.
Operators - Applications managing other applications.
Controllers - Automating resource management.
Webhooks - Validating and mutating resources.
Custom resources - Application-specific abstraction.
Custom resources enable extending Kubernetes for specific needs.
Deployment Strategies
Different deployment approaches:
Rolling updates - Gradually replacing pods.
Blue-green deployments - Running old and new versions, switching when validated.
Canary deployments - Deploying to subset of users, expanding if successful.
Feature toggles - Deploying disabled features, enabling gradually.
GitOps - Using Git as source of truth for deployments.
Smart strategies balance speed and risk.
Common Kubernetes Challenges
Kubernetes adoption faces challenges:
Complexity - Kubernetes has steep learning curve.
Skill gaps - Teams may lack Kubernetes expertise.
Operational burden - Managing clusters requires expertise.
Cost - Inefficient configurations waste resources.
Security - Securing clusters is complex.
Addressing challenges requires training and experience.
Conclusion
Kubernetes is the industry-standard container orchestration platform enabling reliable, scalable deployment of containerised applications. By understanding core concepts, designing effective deployments, managing resources properly, and securing thoroughly, organisations leverage Kubernetes for competitive advantage. Kubernetes enables treating infrastructure as easily managed as applications themselves.