The AWS Architecture
We’re Building
What each layer does, why we picked it, and the order we plan to deliver it in — from controlled pilots through to production automation.
This page describes a plan, not a running system. Every service named below is our intended direction for production deployment — we will say so plainly when a layer is live.
Architecture Layers
Six-Layer Cloud Foundation
Each layer is designed to scale, be secured, and be monitored on its own. That separation is what will let us change one part without rebuilding the rest.
1. Secure entry layer
A proposed edge and API layer using Amazon CloudFront, AWS WAF, and API Gateway or an Application Load Balancer for controlled public access.
2. Application & workflow compute
Containerized services on Amazon ECS with AWS Fargate, plus AWS Lambda for event-driven tasks where short-lived compute is appropriate.
3. AI orchestration
A model-abstraction layer designed to evaluate Amazon Bedrock models, apply workflow policies, and keep model choice separate from business logic.
4. Data & knowledge
Amazon S3 for approved documents and artifacts, PostgreSQL-compatible storage for application data, and a retrieval layer selected after workload testing.
5. Events & integrations
Amazon EventBridge and Amazon SQS are planned for durable workflow events, retries, back-pressure, and isolation between external systems.
6. Operations & cost controls
Amazon CloudWatch, AWS CloudTrail, tagging, budgets, and usage dashboards are planned to support observability, auditability, and cost ownership.
Security approach
Controls designed with the workflow
Agent security is more than infrastructure. It includes what data an agent can read, which tools it can call, what actions need approval, and how every exception is handled.
Review security principlesSeparate development, staging, and production environments
Use least-privilege IAM roles instead of long-lived shared credentials
Encrypt supported data paths and manage keys through AWS KMS
Store application secrets in AWS Secrets Manager or Parameter Store
Log privileged actions and investigate security-relevant events
Define tenant boundaries, retention rules, and deletion workflows
Require human approval for sensitive or irreversible agent actions
Test backups, recovery procedures, and integration failure modes
Delivery Roadmap
Three-Phase Implementation
From MVP foundation through pilot readiness to production scale
Phase 1
MVP foundation
- Establish AWS accounts, environments, budgets, and infrastructure as code
- Deploy the core application and one controlled agent workflow
- Add centralized logs, secrets management, and baseline monitoring
Phase 2
Pilot readiness
- Add durable queues, retry policies, and integration health checks
- Measure model quality, latency, token usage, and cost per workflow
- Implement approval gates and end-to-end workflow traces
Phase 3
Production scale
- Introduce autoscaling and capacity policies based on measured demand
- Strengthen tenant isolation, recovery objectives, and operational runbooks
- Optimize model routing, storage lifecycle, and infrastructure spend
Infrastructure Investment
AWS Credits Accelerate Scale
Cloud credits enable rapid iteration on infrastructure foundations, comprehensive workload testing, and production-grade security controls—all before revenue scales.
Accelerated Development
Evaluate foundation models and retrieval approaches for real customer workflows
Run development, staging, and limited production environments
Build observability, security, backup, and disaster-recovery foundations
Load-test queues, APIs, databases, and model-serving paths
Measure unit economics before committing to long-term infrastructure
Next Steps
Ready to Build at Scale?
We're actively engaging with early design partners, cloud specialists, and teams ready to pilot focused automation workflows. Let's discuss how Manabgro fits your infrastructure.