Cloud Infrastructure & Technical Blueprint

AWS Architecture & Scaling Roadmap

A comprehensive breakdown of SriGen Media's production cloud infrastructure, hybrid container topology, and our planned adoption roadmap for Amazon Web Services (AWS) under the AWS Activate program.

AWS Activate Technical Review Brief Document ID: AWS-ACT-SRIGEN-2026

Why SriGen Media is Transitioning to AWS

SriGen Media has proven customer demand with our mathematical ephemeris and autonomous agent products. To handle our next order-of-magnitude scaling (50,000+ daily report compilations and distributed multi-agent DAG sessions), we require the elastic compute, managed Kubernetes runtime, foundation model diversity, and high-concurrency serverless ecosystem provided natively by Amazon Web Services.

1. Agent Scaling (EKS & Bedrock)
Amazon EKS worker nodes executing autonomous DAG tasks orchestrated via Amazon Bedrock models.
2. Serverless PDF Bursting (Lambda)
AWS Lambda workers compiling 90-page printable PDF reports on-demand with parallel SVG rendering.
3. Vector RAG Store (Aurora + pgvector)
Amazon Aurora PostgreSQL Serverless v2 indexing Sanskrit classical shlokas & engineering knowledge bases.

Production Cloud Topology (Hybrid AWS Architecture)

Tier 1: Global Edge & Ingress Layer
Amazon CloudFront & Route 53
Global SSL termination, edge caching, and DNS routing for *.srigenmedia.com.
AWS WAF & Shield Standard
Rate limiting, SQLi/XSS mitigation, and automated bot challenge protection.
Cloudflare Workers Edge Gateway
Sub-50ms routing, asset minification, and zero-trust perimeter token validation.
Tier 2: Elastic Compute & Autonomous Agent Swarm Layer
Amazon EKS (Elastic Kubernetes)
Autoscaling pod clusters hosting Swarm OS worker nodes and DAG compilation containers.
AWS Lambda Serverless Workers
Sub-second burst workers compiling 90-page printable Brihat-Patrika PDF vectors on-demand.
AWS Fargate Stateless Microservices
VSOP87 analytical ephemeris & astronomical calculation microservices with 0 idle cost.
Tier 3: Foundation Model & Multi-Agent Deliberation (AI / ML)
Amazon Bedrock (Claude 3.5 & Titan)
Multi-expert council deliberation, Sanskrit interpretation, and deterministic output verification.
Amazon Bedrock Knowledge Bases
Classical Sanskrit Jyotish treatises & 18-domain occult knowledge graph hybrid vector search.
Amazon SageMaker Fine-Tuning
Continuous evaluation, Sinkhorn calibration, and domain AST fine-tuning for technical code models.
Tier 4: Enterprise Persistence & Storage
Amazon Aurora Serverless v2
PostgreSQL with pgvector handling multi-tenant user records, orders, and transactional state.
Amazon DynamoDB
Single-digit millisecond latency state store for live agent checkpoints and token quotas.
Amazon S3 & S3 Glacier Instant
Encrypted, immutable PDF report storage with signed time-limited pre-signed download URLs.

Detailed AWS Service Utilization Plan

AWS Service Component / Role Technical Implementation Expected Scale
Amazon Bedrock AI Council & Reasoning Claude 3.5 Sonnet / Llama 3 for 10-Rishi consensus and code generation 25M+ tokens / month
Amazon EKS Swarm OS Agent Pods Kubernetes cluster executing isolated, sandboxed multi-agent DAG workers 3-12 m6i.xlarge nodes
AWS Lambda Serverless PDF Compiler High-memory ARM64 Lambda compiling 90-page vector charts in <1.2s 100k invocations / mo
Amazon Aurora PostgreSQL + pgvector Serverless v2 auto-scaling relational store with vector embeddings 0.5 - 16 ACUs
Amazon S3 Document & Chart Vault Encrypted PDF storage with lifecycle policies and CloudFront CDN streaming 5TB+ tiered storage
AWS Secrets & KMS Security & Encryption Automatic key rotation, envelope encryption, and IAM least-privilege roles Enterprise compliance

Target AWS Regions & Multi-Region Strategy

To ensure low-latency access for our primary Indic audience while maintaining sovereign data compliance, our primary cluster is provisioned in AWS Asia Pacific (Mumbai) ap-south-1, with secondary inference endpoints in AWS US East (N. Virginia) us-east-1 for global enterprise client availability.