Kubernetes

Deploy and scale BroxiAI applications on Kubernetes for enterprise-grade container orchestration

Learn how to deploy, scale, and manage BroxiAI applications on Kubernetes for production-ready container orchestration with automatic scaling, self-healing, and service discovery.

Overview

Kubernetes provides:

  • Automatic scaling and load balancing

  • Self-healing and fault tolerance

  • Service discovery and networking

  • Rolling updates and rollbacks

  • Secret and configuration management

  • Multi-cloud and hybrid deployments

Basic Kubernetes Setup

Namespace and Resources

Namespace Configuration

# namespace.yaml
apiVersion: v1
kind: Namespace
metadata:
  name: broxi-ai
  labels:
    name: broxi-ai
    environment: production
---
apiVersion: v1
kind: ResourceQuota
metadata:
  name: broxi-quota
  namespace: broxi-ai
spec:
  hard:
    requests.cpu: "10"
    requests.memory: 20Gi
    limits.cpu: "20"
    limits.memory: 40Gi
    persistentvolumeclaims: "5"
    pods: "50"
---
apiVersion: v1
kind: LimitRange
metadata:
  name: broxi-limits
  namespace: broxi-ai
spec:
  limits:
  - default:
      cpu: "500m"
      memory: "512Mi"
    defaultRequest:
      cpu: "100m"
      memory: "128Mi"
    type: Container

ConfigMaps and Secrets

Configuration Management

Application Deployment

Main Application

Deployment Configuration

Service Configuration

Database Deployment

PostgreSQL StatefulSet

Redis Deployment

Auto-scaling Configuration

Horizontal Pod Autoscaler

HPA Configuration

Vertical Pod Autoscaler

VPA Configuration

Cluster Autoscaler

Node Scaling Configuration

Advanced Kubernetes Features

Jobs and CronJobs

Background Processing Jobs

Network Policies

Security Network Policies

Pod Disruption Budgets

PDB Configuration

Ingress and Load Balancing

Ingress Configuration

NGINX Ingress

Service Mesh (Istio)

Istio Configuration

Monitoring and Observability

Prometheus Monitoring

ServiceMonitor Configuration

Distributed Tracing

Jaeger Configuration

Security and RBAC

Service Accounts and RBAC

RBAC Configuration

Pod Security Standards

Pod Security Policy

GitOps and CI/CD

ArgoCD Application

ArgoCD Configuration

Helm Charts

Helm Chart Structure

Disaster Recovery

Backup and Restore

Velero Backup Configuration

Database Backup CronJob

Best Practices

Resource Management

Resource Optimization

  • Set appropriate resource requests and limits

  • Use horizontal and vertical pod autoscaling

  • Implement cluster autoscaling for node management

  • Monitor resource utilization continuously

  • Use pod disruption budgets for availability

Security

Security Best Practices

  • Run containers as non-root users

  • Use network policies for traffic control

  • Implement RBAC with least privilege

  • Regular security scanning of container images

  • Use pod security standards/policies

  • Encrypt secrets and sensitive data

High Availability

HA Configuration

  • Deploy across multiple availability zones

  • Use pod anti-affinity rules

  • Implement health checks and probes

  • Configure ingress with load balancing

  • Use persistent volumes for stateful data

  • Regular backup and disaster recovery testing

Troubleshooting

Common Issues

Pod Issues

Service Discovery Issues

Networking Issues

Next Steps

After Kubernetes deployment:

  1. Monitoring Enhancement: Implement comprehensive observability

  2. Security Hardening: Regular security assessments and updates

  3. Performance Tuning: Optimize for your specific workload

  4. Disaster Recovery: Test backup and recovery procedures

  5. Cost Optimization: Monitor and optimize resource usage


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