LearnHub Architecture Documentation

Modern SaaS Learning Platform on AWS with Kubernetes Multi-Tenancy

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Introduction

LearnHub is a cloud-native Learning Management System (LMS) engineered for scalability, multi-tenancy, and high availability. Built on AWS with Kubernetes orchestration, it delivers isolated tenant environments, robust video processing, and automated failover capabilities.

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Architecture Overview

Note: The above diagram provides a visual representation of the LearnHub architecture for better understanding.

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Core Components

1. Networking & Security

Component	Purpose
VPC	Segregated public/private subnets with security groups
Route 53	DNS management and domain routing
EKS-Managed ALB	Traffic distribution to Kubernetes pods
Nginx Reverse Proxy	Tenant-aware routing to Kubernetes namespaces

2. Kubernetes Cluster (EKS)

Namespace	Microservices	Tenant Isolation
tenant-1	Course, Enrollment, Notification, Transcoding	Dedicated resources via Kubernetes ResourceQuotas
tenant-2	Replica of tenant-1 services	Network Policies for inter-namespace communication

3. Data Layer

Service	Technology	Configuration
Primary Database	PostgreSQL	Active instance with streaming replication
Standby Database	PostgreSQL	Automatic failover via pg_auto_failover
File Storage	S3	uploads-bucket (raw) & transcoded-bucket (processed)
Metadata Store	DynamoDB	Signed URL generation with TTL

4. Video Processing Pipeline

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Key Workflows

1. Multi-Tenant Request Flow

1. User → Route 53 → API Gateway
2. ALB routes to tenant-specific namespace via Nginx ingress
3. Microservices interact with tenant-sharded databases

2. Video Transcoding Workflow

1. Upload API writes to S3 uploads-bucket
2. S3 Event triggers VideoTransformingStateMachine (Step Functions)
3. AWS Batch processes video using FFmpeg containers
4. Output stored in transcoded-bucket with CloudFront CDN
5. DynamoDB stores metadata + signed URLs

3. High Availability Database

• Active-Passive PostgreSQL:
  • Synchronous replication via pglogical
  • Automatic failover using Patroni
  • Read replicas for analytics workloads

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Deployment Guide

Prerequisites

• AWS Account with IAM permissions for EKS, RDS, S3
• eksctl, kubectl, aws-cli installed
• Terraform v1.5+ (for infrastructure provisioning)

Infrastructure Setup

# 1. Provision VPC/EKS Cluster
terraform apply -target=module.vpc -target=module.eks

# 2. Configure database
terraform apply -target=module.rds

# 3. Deploy Kubernetes services
helm install learnhub ./charts -f tenants.yaml

Tenant Configuration

tenants.yaml

tenants:
  - name: tenant-1
    resources:
      requests:
        memory: "4Gi"
        cpu: "1000m"
    database:
      shard: "shard01"
  - name: tenant-2
    replicas: 3
    database:
      shard: "shard02"

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CI/CD Pipeline

LearnHub integrates a GitOps-based Continuous Integration and Continuous Delivery (CI/CD) pipeline to automate code quality checks, infrastructure provisioning, container security, and Kubernetes deployments.

Key Highlights

• Infrastructure as Code: GitHub Actions triggers Terraform to provision cloud resources, securely injecting secrets via HashiCorp Vault.

• Code Quality & Security Checks: Uses SonarQube for static code analysis and Trivy for dependency and image scanning before deployment.

• Container Lifecycle: Docker images are built, scanned, and pushed to AWS ECR private repositories.

• GitOps with ArgoCD: ArgoCD fetches the latest deployment manifests from GitHub and syncs them to the Kubernetes cluster.

This pipeline ensures secure, repeatable, and automated delivery of both infrastructure and application code.

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Operational Excellence

Monitoring

Tool	Use Case
CloudWatch	EKS cluster metrics & S3 bucket analytics
Prometheus	Microservice performance monitoring
AWS X-Ray	Distributed tracing of video pipeline

Disaster Recovery

• Database: Cross-region replication with RDS Snapshots
• S3 Buckets: Versioning + Cross-Region Replication (CRR)
• Kubernetes: Cluster autoscaler with multi-AZ node groups

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Contributing

1. Fork repository & create feature branch (git checkout -b feat/new-service)
2. Submit PR with:
   • Architecture diagrams (using lucidchart and eraser.io)
   • Terraform modules for new components
   • Helm chart updates
3. Adhere to Gitflow workflow

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License

MIT License - See LICENSE.md for full terms.

Note: Production deployments require configuring AWS Backup for RDS/S3 and enabling EKS control plane logging.