How Does Kubernetes Work?
How Does Kubernetes Work?
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. It provides a robust framework for running distributed systems reliably across clusters of machines.
Understanding Kubernetes Architecture
Control Plane Components
The control plane manages the overall cluster state:
kube-apiserver:
- API Server: Central communication hub for all Kubernetes components
- REST API: Exposes Kubernetes API for cluster management
- Authentication: Handles user authentication and authorization
- Validation: Validates and processes API requests
etcd:
- Distributed Database: Stores all cluster data and configuration
- Consistency: Ensures data consistency across the cluster
- Backup: Critical for cluster backup and disaster recovery
- High Availability: Can be deployed in HA mode for production
kube-scheduler:
- Pod Scheduling: Determines where to place new pods
- Resource Allocation: Considers resource requirements and constraints
- Affinity Rules: Applies node affinity and anti-affinity rules
- Load Balancing: Distributes pods across available nodes
kube-controller-manager:
- Controller Loop: Runs various controllers that maintain cluster state
- Node Controller: Monitors node health and handles node failures
- Replication Controller: Maintains desired number of pod replicas
- Service Controller: Manages service endpoints and load balancing
Node Components
Worker nodes run the actual application workloads:
kubelet:
- Node Agent: Primary node agent that runs on each node
- Pod Management: Creates, modifies, and deletes pods
- Health Monitoring: Monitors pod health and reports to API server
- Resource Management: Manages node resources and container runtime
kube-proxy:
- Network Proxy: Maintains network rules and enables communication
- Service Discovery: Implements service abstraction and load balancing
- Network Policies: Enforces network policies and security rules
- IP Tables: Manages IP tables rules for traffic routing
Container Runtime:
- Container Engine: Runs containers (Docker, containerd, CRI-O)
- Image Management: Pulls and manages container images
- Container Lifecycle: Starts, stops, and manages containers
- Resource Isolation: Provides resource isolation and security
How Kubernetes Manages Applications
Pod Lifecycle
Pods are the smallest deployable units in Kubernetes:
Pod Creation:
- API Request: User submits pod creation request to API server
- Scheduling: Scheduler determines optimal node for pod placement
- Node Assignment: Pod is assigned to specific node
- Container Creation: Kubelet creates containers on assigned node
- Health Monitoring: Kubelet monitors pod health and reports status
Pod States:
- Pending: Pod accepted but not yet scheduled or running
- Running: Pod scheduled and all containers running
- Succeeded: All containers completed successfully
- Failed: At least one container failed or terminated
- Unknown: Pod state cannot be determined
Service Discovery and Load Balancing
Services provide stable networking for applications:
Service Types:
- ClusterIP: Internal cluster access (default)
- NodePort: External access via node ports
- LoadBalancer: Cloud provider load balancer integration
- ExternalName: DNS-based service discovery
Load Balancing:
- Round Robin: Distributes requests across available pods
- Session Affinity: Maintains client session consistency
- Health Checks: Removes unhealthy pods from load balancer
- Traffic Splitting: Supports canary deployments and A/B testing
Scaling and Self-Healing
Automatic scaling and recovery capabilities:
Horizontal Pod Autoscaler (HPA):
- Metrics Monitoring: Monitors CPU, memory, and custom metrics
- Automatic Scaling: Scales pods based on resource utilization
- Target Metrics: Maintains target average utilization
- Scale Limits: Configurable minimum and maximum replicas
Self-Healing:
- Health Checks: Regular health checks on pods and containers
- Automatic Restart: Restarts failed containers automatically
- Node Failure Handling: Reschedules pods from failed nodes
- Replica Management: Maintains desired number of replicas
Kubernetes Resource Management
Namespaces
Logical isolation within the cluster:
Default Namespaces:
- default: Default namespace for user resources
- kube-system: System components and add-ons
- kube-public: Publicly accessible resources
- kube-node-lease: Node lease objects
Namespace Benefits:
- Resource Isolation: Separate resources by project or team
- Access Control: Different RBAC policies per namespace
- Resource Quotas: Limit resource consumption per namespace
- Network Policies: Apply network policies at namespace level
Resource Quotas and Limits
Resource management and constraints:
Resource Quotas:
- CPU and Memory: Limit total CPU and memory usage
- Storage: Limit persistent volume claims
- Object Counts: Limit number of pods, services, etc.
- Namespace Scope: Applied at namespace level
Resource Limits:
- Requests: Minimum resources guaranteed to pod
- Limits: Maximum resources pod can consume
- Quality of Service: Determines pod scheduling priority
- OOM Handling: Out-of-memory handling and eviction
Networking in Kubernetes
Pod Networking
Network connectivity between pods:
Pod Network:
- Unique IP: Each pod gets unique cluster IP address
- Flat Network: All pods can communicate directly
- Network Plugins: CNI plugins provide networking implementation
- Cross-Node Communication: Pods can communicate across nodes
Service Networking:
- Virtual IP: Services get virtual IP addresses
- Load Balancing: Distributes traffic across service endpoints
- DNS Resolution: Automatic DNS resolution for services
- Port Mapping: Maps service ports to pod ports
Network Policies
Security and traffic control:
Policy Types:
- Ingress Rules: Control incoming traffic to pods
- Egress Rules: Control outgoing traffic from pods
- Namespace Isolation: Isolate traffic between namespaces
- Pod Selectors: Target specific pods or namespaces
Implementation:
- Network Plugins: Requires network plugin that supports policies
- Policy Enforcement: Applied at network level
- Default Policies: Allow or deny traffic by default
- Policy Chaining: Multiple policies can be applied
Storage in Kubernetes
Persistent Volumes
Persistent storage for applications:
Volume Types:
- Local Storage: Node-local storage
- Network Storage: NFS, iSCSI, cloud storage
- Cloud Volumes: AWS EBS, Azure Disk, GCP PD
- Distributed Storage: Ceph, GlusterFS
Volume Lifecycle:
- Provisioning: Dynamic or static volume provisioning
- Binding: Binding volumes to persistent volume claims
- Mounting: Mounting volumes to pods
- Reclaiming: Volume cleanup after pod deletion
ConfigMaps and Secrets
Configuration and sensitive data management:
ConfigMaps:
- Configuration Data: Non-sensitive configuration data
- Environment Variables: Inject configuration as environment variables
- Files: Mount configuration as files in pods
- Hot Reloading: Update configuration without pod restart
Secrets:
- Sensitive Data: Passwords, tokens, certificates
- Encryption: Encrypted storage in etcd
- Access Control: RBAC-based access to secrets
- External Integration: Integration with external secret managers
Security in Kubernetes
Authentication and Authorization
User and service authentication:
Authentication Methods:
- Client Certificates: X.509 certificates for API access
- Bearer Tokens: JWT tokens for service accounts
- OpenID Connect: Integration with identity providers
- Webhook: Custom authentication webhooks
Authorization:
- RBAC: Role-based access control
- ABAC: Attribute-based access control
- Node Authorization: Node-specific authorization
- Webhook Authorization: Custom authorization webhooks
Pod Security
Security policies for pods:
Pod Security Standards:
- Privileged: Unrestricted access (not recommended)
- Baseline: Minimal security restrictions
- Restricted: Maximum security restrictions
Security Context:
- RunAsUser: User ID for running containers
- RunAsGroup: Group ID for running containers
- ReadOnlyRootFilesystem: Read-only root filesystem
- Capabilities: Linux capabilities for containers
Monitoring and Observability
Metrics and Monitoring
Cluster and application monitoring:
Metrics Sources:
- kubelet: Node and pod metrics
- kube-state-metrics: Kubernetes object metrics
- cAdvisor: Container resource metrics
- Custom Metrics: Application-specific metrics
Monitoring Tools:
- Prometheus: Metrics collection and storage
- Grafana: Metrics visualization and dashboards
- AlertManager: Alerting and notification
- Custom Dashboards: Application-specific monitoring
Logging
Centralized logging for applications:
Log Collection:
- Container Logs: Standard output and error streams
- Node Logs: System and application logs
- Audit Logs: API server audit logs
- Event Logs: Kubernetes events
Logging Solutions:
- Fluentd: Log collection and forwarding
- Elasticsearch: Log storage and indexing
- Kibana: Log visualization and search
- Centralized Logging: Unified logging infrastructure
Best Practices
1. Resource Management
Efficient resource utilization:
- Resource Requests: Always specify resource requests
- Resource Limits: Set appropriate resource limits
- Horizontal Scaling: Use HPA for automatic scaling
- Resource Quotas: Implement namespace resource quotas
2. Security
Security-first approach:
- RBAC: Implement role-based access control
- Network Policies: Use network policies for traffic control
- Pod Security: Apply pod security standards
- Secret Management: Use external secret managers
3. Monitoring
Comprehensive monitoring:
- Health Checks: Implement liveness and readiness probes
- Metrics Collection: Collect application and infrastructure metrics
- Logging: Centralized logging for all applications
- Alerting: Set up alerts for critical issues
4. Backup and Recovery
Disaster recovery planning:
- etcd Backup: Regular backup of etcd data
- Application Backup: Backup application data and configurations
- Recovery Procedures: Document recovery procedures
- Testing: Regular testing of backup and recovery procedures