- Overview
- Architecture Components
- Deployment Workflow
- Security Measures
- Scalability and Performance Optimization
- Monitoring and Observability
- Disaster Recovery and Business Continuity
- Cost Management
- Code Quality Assurance
- References and Resources
This document outlines a comprehensive microservices-based AWS architecture for deploying a PHP8 application. The architecture is designed to provide high availability, scalability, security, and performance while meeting the following requirements:
- MySQL for relational data storage
- Redis for session storage and caching
- DynamoDB for key-value storage
- Efficient solution for large file downloads and static content delivery
- Application code hosted on GitHub
- Local development using Docker and docker-compose
Purpose: Provides a logically isolated section of the AWS Cloud for secure deployment of resources.
Configuration:
- Public and private subnets across multiple Availability Zones (AZs) for high availability and fault tolerance.
- NAT Gateways in public subnets for outbound internet access from private subnets.
Rationale: VPC allows for network isolation and segmentation, enhancing security and providing control over network architecture. Multiple AZs ensure high availability and resilience against datacenter failures.
Reference: Terraform AWS: High Availability VPC & EKS kubernetes
Purpose: Orchestrates and manages the deployment of microservices.
Configuration:
- Cluster placed in private subnets for enhanced security.
- Integrated with ECR for secure container image storage.
- Karpenter for efficient auto-scaling of worker nodes.
Rationale: EKS provides a managed Kubernetes platform, reducing the operational overhead of running Kubernetes. It offers seamless integration with other AWS services and provides a scalable, highly available environment for microservices.
Reference: AWS EKS Setup with Terraform: Kubernetes, Ingress, Karpenter & Metrics Server
Purpose: Distributes incoming application traffic across multiple microservices.
Configuration:
- ALB Ingress Controller for dynamic routing based on Kubernetes Ingress resources.
- Configured with HTTPS listeners for secure communication.
Rationale: ALB with Ingress Controller provides intelligent routing capabilities, SSL termination, and seamless integration with EKS. It allows for efficient traffic distribution and enables advanced routing strategies.
Reference: AWS WAF for Kubernetes EKS: ALB Ingress & ASG with ALB
Purpose: Provides a managed relational database for the application's structured data storage needs.
Configuration:
- Multi-AZ deployment for high availability and automatic failover.
- Placed in private subnets for enhanced security.
- Automated backups and maintenance.
Rationale: RDS offers a fully managed MySQL database, reducing administrative tasks while providing high availability, automated backups, and easy scalability. It's ideal for structured data that requires ACID compliance.
Reference: Terraform V-12: AWS RDS MySQL Tutorial for Beginners
Purpose: Offers high availability and monitoring for Redis instances.
Configuration:
- Bitnami Redis Sentinel Helm chart for easy deployment.
- Secure storage of sensitive data like session information and user preferences.
Rationale: Redis Sentinel provides automatic failover, monitoring, and high availability for Redis instances. It ensures that the application can continue to function even in the event of a Redis node failure.
Reference: Kubernetes Redis High-Availability Cluster: Step-by-Step Guide to Setup Redis Sentinel
Purpose: Provides a fully managed NoSQL database for key-value and document storage.
Configuration:
- Global tables for multi-region redundancy.
- Auto-scaling enabled for read and write capacity.
Rationale: DynamoDB offers millisecond response times, infinite scalability, and a serverless model. It's ideal for high-volume data that doesn't require complex relationships, such as user profiles, session data, or real-time analytics.
Purpose: Stores and serves large files and static assets (e.g., images, CSS, JavaScript) with low latency globally.
Configuration:
- S3 buckets with versioning and lifecycle policies.
- CloudFront distribution with S3 as origin.
- HTTPS enforced and geo-restriction as needed.
Rationale: S3 provides durable, scalable object storage, while CloudFront acts as a Content Delivery Network (CDN). This combination ensures fast, secure delivery of static assets and large files to users worldwide, reducing load on application servers and improving user experience.
Reference: Terraform Cloudfront with OAI: Proxy Your S3 Private Bucket Effortlessly!
Purpose: Protects the application from common web exploits and attacks.
Configuration:
- Associated with ALB and CloudFront.
- Rule sets for SQL injection, cross-site scripting (XSS) prevention, and other common attacks.
Rationale: WAF adds an essential layer of security, filtering malicious web traffic before it reaches the application. This helps prevent attacks, reduces the risk of data breaches, and ensures application availability.
Reference: AWS WAF for Kubernetes EKS: ALB Ingress & ASG with ALB
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Set up VPC and Networking
- Use Terraform to create VPC with public and private subnets across multiple AZs.
- Set up Internet Gateway, NAT Gateways, and route tables.
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Deploy EKS Cluster
- Use Terraform to create EKS cluster in private subnets.
- Set up Karpenter for auto-scaling.
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Configure Security Groups, NACLs and Service Accounts
- Setup security groups for RDS MySQL to allow only access from worker nodes.
- Set up NACLs for additional subnet-level security.
- Setup IAM roles and service accounts for EKS pods to access AWS RDS MySQL and DynamoDB (principle of least privilege).
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Set up Database and Caching Layers
- Deploy RDS MySQL instance in private subnets using Terraform.
- Deploy Redis Sentinel cluster in EKS for caching and session management.
- Set up DynamoDB tables with required indexes.
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Configure S3 and CloudFront
- Create S3 buckets for file storage and static assets.
- Set up CloudFront distribution with S3 as origin using Terraform.
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Deploy Application Load Balancer and Ingress Controller
- Set up ALB Ingress Controller in EKS.
- Configure listeners and target groups for microservices.
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Implement CI/CD Pipeline
- Set up GitHub Actions for CI with OIDC integration for AWS ECR.
- Implement ArgoCD for continuous deployment to EKS.
CI with GitHub Actions and OIDC Integration:
- Configure GitHub Actions workflows to build and push Docker images to Amazon ECR.
- Use OpenID Connect (OIDC) for secure, token-based authentication between GitHub Actions and AWS.
- Implement Terragrunt for managing multi-environment infrastructure as code.
Benefits:
- Enhanced security by eliminating the need for long-lived AWS credentials.
- Streamlined CI process with automatic pushing of images to ECR.
- Simplified management of multi-environment deployments with Terragrunt.
Reference: Terragrunt GitHub Actions OIDC Integration with AWS ECR
CD with ArgoCD:
- Set up ArgoCD in the EKS cluster for GitOps-based deployments.
- Configure ApplicationSets for managing multiple similar applications.
Reference: ArgoCD ApplicationSets kubernetes
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Configure Monitoring and Logging
- Set up Prometheus and Grafana for monitoring and alerting.
- Implement ELK stack or Grafana Loki for centralized logging.
- Configure Slack integration for alerts. References:
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Implement Security Measures
- Enable AWS WAF and configure rule sets.
- Implement AWS Shield for DDoS protection.
- Set up HashiCorp Vault for secrets management. Reference: HashiCorp Vault HA TLS Setup on Kubernetes with Secrets Injection in Application Pods
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Set up Code Quality and Static Analysis
- Integrate Sonarqube with GitHub Actions for continuous code quality checks.
- Configure Sonarqube server in the EKS cluster or use SonarCloud for cloud-based analysis.
- Set up quality gates and code coverage thresholds. Reference: Spring Boot SonarQube Integration with GitHub Actions
- Implement IAM roles with least privilege access for all components.
- Use IRSA (IAM Roles for Service Accounts) in EKS for fine-grained permissions.
- Enable encryption at rest for all data stores (RDS, S3, EBS volumes).
- Implement network policies in EKS for inter-service communication control.
- Regularly update and patch all systems, including EKS nodes and containers.
- Implement Istio for enhanced security and traffic management. Reference: EKS Istio Ambient Mesh L4 (Ztunnel) | End-to-End Encryption
- Utilize Karpenter for efficient EKS cluster auto-scaling.
- Implement horizontal pod autoscaling (HPA) for individual microservices.
- Use ElastiCache Redis for caching and session management to reduce database load.
- Implement read replicas for RDS to offload read traffic.
- Use CloudFront for global content delivery and API acceleration.
- Optimize Kubernetes resource requests and limits for efficient resource utilization.
- Set up Prometheus and Grafana for comprehensive Kubernetes monitoring.
- Use CloudWatch Container Insights for EKS monitoring.
- Implement distributed tracing with AWS X-Ray or Jaeger for microservices observability.
- Set up alerts for critical metrics across all components, with Slack integration.
- Use AWS CloudTrail for auditing and compliance.
- Implement Grafana Loki or ELK stack for centralized logging: Reference: Cut Logging Costs with ELK Stack & Fluent-Bit on EKS!
- Use Lens for Kubernetes cluster management and monitoring with Prometheus and Grafana: Reference: Kubernetes Monitoring with Prometheus & Grafana
- Implement multi-region strategy for critical microservices.
- Use RDS Multi-AZ and read replicas for database failover and recovery.
- Set up S3 cross-region replication for important data.
- Implement regular backups for all stateful components.
- Create and regularly test a disaster recovery plan.
- Use Spot Instances with Karpenter for non-critical workloads to reduce compute costs.
- Implement auto-scaling at the pod and node level to match capacity with demand.
- Use S3 Intelligent-Tiering for optimal storage costs based on access patterns.
- Regularly review and optimize resource allocation for all microservices.
- Utilize AWS Cost Explorer and Budgets for ongoing cost management and forecasting.
- Implement FinOps practices for Kubernetes cost management: Reference: FinOps Effortless GKE Kubernetes Logs Costs Reduction
- Integrate Sonarqube with GitHub Actions for automated code quality checks on every pull request and merge to main branch.
- Use Sonarqube to identify code smells, bugs, vulnerabilities, and security hotspots.
- Set up quality gates to prevent merging of code that doesn't meet predefined quality criteria.
- Monitor code coverage and set minimum thresholds to ensure adequate test coverage.
- Regularly review Sonarqube reports and address identified issues to maintain high code quality.
- Consider using SonarCloud for cloud-based analysis if you prefer not to manage a Sonarqube server.
Benefits:
- Early detection of code quality issues and security vulnerabilities.
- Consistent code quality across the entire project.
- Automated enforcement of coding standards and best practices.
- Improved overall maintainability and reliability of the codebase.
Reference: Spring Boot SonarQube Integration with GitHub Actions