Aws Active-Active Architecture: Designing an Active-Active Global Collaboration Platform on AWS with API Gateway, EKS, DynamoDB Global Tables, and EventBridge

Global collaboration platforms are hard because latency, availability, and write conflicts are all first-class requirements. You do not get active-active for free just by replicating a database. A collaboration product such as chat, whiteboarding, or lightweight document workflows needs low-latency access from users worldwide, resilience to regional outages, and near-real-time state propagation for shared entities.

TL;DR: Use CloudFront and Route 53 for entry, API Gateway plus EKS for connection-heavy workloads, DynamoDB global tables for durable shared metadata, Redis for ephemeral presence, and EventBridge plus SQS for async fan-out.

Why Naive Solutions Break — AWS active-active architecture

Centralizing all traffic in one Region causes poor international latency and creates a single outage domain. Using a single-writer database with cross-Region reads also makes collaboration feel sluggish and complicates disaster recovery.

Architecture Overview

Use CloudFront and Route 53 for intelligent entry, API Gateway for public APIs, EKS for collaboration services and connection-heavy components, DynamoDB global tables for active-active metadata, S3 for attachments, EventBridge global endpoints for event continuity, SQS for async fan-out, and ElastiCache for session and presence acceleration.

Architecture Diagram

Service-by-Service Breakdown

• CloudFront: Global edge ingress for APIs, assets, and connection bootstrap endpoints.
• Route 53: Region-aware routing and failover.
• API Gateway: Authenticated API front door per Region.
• Amazon EKS: Runs collaboration services, websocket backends, and stateful coordination components that benefit from container orchestration.
• EKS Auto Mode or Karpenter-backed scaling: Rapid node right-sizing for spiky collaboration traffic.
• DynamoDB global tables: Multi-Region metadata store for rooms, memberships, read markers, and lightweight document state.
• ElastiCache Redis: Presence, ephemeral collaboration hints, and session acceleration.
• S3: Attachment and export storage.
• EventBridge global endpoints: Cross-Region event publisher continuity.
• SQS: Async notification fan-out and heavy secondary processing.
• CloudWatch and X-Ray: Region health, event replication visibility, and trace continuity.

Request Lifecycle and Data Flow

1. A user request lands at the edge and is routed to the nearest healthy Region.
2. API Gateway authenticates the request and forwards it to EKS-hosted collaboration services.
3. Presence and ephemeral session state are served from Redis.
4. Shared metadata is read and written against the local DynamoDB global table replica.
5. Collaboration events are published through EventBridge global endpoints.
6. SQS-backed workers handle notifications, indexing, exports, and secondary projections asynchronously.
7. Attachments and generated artifacts are stored in S3.

Production Code Patterns

IRSA-backed EKS service account for collaboration workers

apiVersion: v1
kind: ServiceAccount
metadata:
 name: room-events
 namespace: collaboration
 annotations:
 eks.amazonaws.com/role-arn: arn:aws:iam::123456789012:role/room-events-role
---
apiVersion: apps/v1
kind: Deployment
metadata:
 name: room-events
spec:
 replicas: 4

DynamoDB write model for read markers

await ddb.send(new PutCommand({
 TableName: process.env.COLLAB_TABLE,
 Item: {
 pk: `ROOM#${roomId}`,
 sk: `READ#${userId}`,
 lastSeenMessageId,
 updatedAt: new Date().toISOString(),
 region: process.env.AWS_REGION,
 },
}));

Scaling Strategy

• Use EKS for workloads that benefit from long-lived connections and fine-grained container control.
• Scale pods horizontally on CPU, memory, request rate, or custom queue metrics.
• Let EKS Auto Mode or Karpenter provision right-sized nodes quickly for traffic spikes.
• Keep ephemeral state in Redis and persistent metadata in DynamoDB global tables.
• Route users to local Regions and avoid cross-Region chatter in the hot path.

Cost Optimization Techniques

• Mix on-demand and spot-friendly node pools for worker workloads.
• Separate websocket or connection-heavy services from stateless APIs for better packing efficiency.
• Cache presence and room summaries with short TTLs.
• Use S3 lifecycle rules for old attachments and exports.

Security Best Practices

• Apply IRSA or equivalent pod-level IAM boundaries for EKS workloads.
• Encrypt DynamoDB, S3, SQS, and Redis in transit and at rest.
• Segment namespaces and network policies by service sensitivity.
• Protect APIs with WAF, strong token validation, and tenant-aware authorization logic.

Failure Handling and Resilience

• Treat collaboration updates as conflict-prone and define merge semantics explicitly.
• Make event consumers idempotent because replicated event flows can duplicate work.
• Use Region failover routing for front-door recovery.
• Degrade gracefully from live collaboration to eventual sync if one Region or subsystem is impaired.
• Rehearse global table conflict and failover scenarios, not just infrastructure outages.

Trade-offs and Alternatives

This architecture supports low-latency global traffic and regional fault isolation, but active-active systems are harder to reason about than primary-secondary designs. If the product does not truly need active-active writes, Aurora Global Database plus regional reads may be simpler.

Real-World Use Case

A Slack-style collaboration product with global teams, real-time room presence, and attachment sharing is a strong fit for this model.

Key Interview Insights

• Clarify which state is ephemeral, durable, and conflict-prone.
• Discuss active-active write conflicts honestly; do not hand-wave them away.
• Explain why EKS is chosen over Lambda for long-lived or connection-heavy services.
• Emphasize Region-local latency, graceful degradation, and disaster recovery testing.

Recommended resources

• AWS Architecture Center
• Amazon API Gateway docs
• Amazon CloudWatch docs

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