AWS Real-Time Voice AI Platform - ap-south-1

aws · network diagram.

About This Architecture

Real-time voice AI platform on AWS ap-south-1 (Mumbai) combining Route 53, CloudFront CDN, AWS WAF, and Shield for global edge delivery and DDoS protection. Traffic flows through dual ALBs and NLBs across two availability zones, routing to ECS microservices (API Gateway, Conversation Manager, LLM Orchestrator, Voice Agent Worker, LiveKit WebRTC server) with CPU/memory auto-scaling. Asynchronous workloads fan out via SQS queues (stt-processing, llm-processing, background-task, retry) with queue-depth scaling, while ElastiCache Redis and RDS PostgreSQL (primary/standby) provide session state and persistent storage across private subnets. CloudWatch, X-Ray, CodePipeline, and IAM complete the observability and CI/CD backbone. Fork this diagram to customize VPC CIDR ranges, add additional regions, or adjust SQS queue configurations for your voice AI workload. This architecture demonstrates multi-AZ resilience, serverless messaging patterns, and managed database failover essential for production voice applications.

People also ask

How do I architect a production real-time voice AI platform on AWS with high availability and auto-scaling?

This diagram shows a multi-AZ AWS voice AI platform in ap-south-1 using ECS microservices (API Gateway, LLM Orchestrator, Voice Agent Worker, LiveKit WebRTC) across two availability zones with ALB/NLB load balancing, SQS queues for async STT/LLM processing with queue-depth auto-scaling, RDS PostgreSQL primary/standby for persistence, and ElastiCache Redis for session state. CloudFront CDN, AWS WAF

AWS Real-Time Voice AI Platform - ap-south-1

AWSadvancedECSReal-time voice AIMulti-AZ architectureSQS async processingRDS failover
Domain: Cloud AwsAudience: AWS solutions architects designing real-time voice AI platforms with high availability and auto-scaling requirements
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Created by

March 8, 2026

Updated

March 8, 2026 at 12:03 PM

Type

network

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