This repository contains a reference architecture and tradeoff analysis for secure, scalable mission data platforms in regulated or high-security environments.
The goal of this project is to demonstrate how cloud architecture decisions can be evaluated across security, scalability, cost, operational complexity, and delivery constraints.
This project is especially relevant to:
- Technical Program Management
- Cloud delivery in regulated environments
- Secure data platform design
- Architecture decision support
Design a secure mission data platform that supports:
- Multi-source data ingestion
- Controlled data access
- Scalable analytics workflows
- Secure API access
- Phased delivery in constrained environments
High-level pattern:
- Data ingested into object storage
- Event-driven processing for transformation and validation
- Secure API layer for controlled access
- Identity and access controls enforcing least privilege
- Network segmentation for public/private workload separation
- Monitoring, logging, and audit support
- S3: Best for durable, scalable object storage and data lake patterns
- EBS: Best for block storage attached to a single instance
- EFS: Best for shared file storage across multiple compute resources
- Lambda: Good for event-driven processing with low operational overhead
- EC2: Better when workloads need persistent control, custom runtime tuning, or long-duration processing
- RDS: Better for relational schemas, joins, and structured transactions
- DynamoDB: Better for high-scale key-value access patterns and serverless architectures
- ALB: Better for HTTP/HTTPS routing and application-aware load balancing
- NLB: Better for ultra-high performance and TCP/UDP use cases
- IAM roles and short-lived credentials instead of hardcoded secrets to reduce credential exposure risk
- Least-privilege access patterns aligned to user roles, services, and data sensitivity
- Encryption at rest and in transit for all data flows, particularly for sensitive or mission-critical datasets
- Network segmentation (public vs private subnets) to isolate external access from backend processing and data services
- Centralized logging, monitoring, and audit capabilities to support both operational visibility and compliance requirements
- Access control models aligned to sensitive data environments, including attribute-based access considerations and Zero Trust principles
Architecture decisions directly impact program execution, delivery risk, and stakeholder alignment. Key considerations include:
- Sequencing foundational services (identity, storage, network controls) before introducing advanced analytics or processing capabilities
- Reducing integration risk through modular rollout, enabling incremental validation of components before full system integration
- Aligning architecture choices with delivery timelines, resource constraints, and mission priorities
- Balancing speed, security, and maintainability to ensure sustainable long-term operation
- Enabling clear ownership across teams by defining boundaries between data ingestion, processing, and access layers
- Supporting phased deployment in constrained or classified environments where full cloud capabilities may not be immediately available
This repository is being actively expanded to include:
- Visual architecture diagram illustrating data flow and service interactions
- Example mapping of the reference architecture to mission data platform use cases (e.g., multi-agency analytic systems)
- Additional implementation examples to further explore infrastructure and deployment patterns
These additions reflect ongoing hands-on exploration of cloud architecture and technical program delivery concepts.
This project reflects my interest in cloud architecture, secure delivery, and technical program management for mission-critical systems. This work is informed by hands-on AWS experimentation, including configuring core services such as S3, IAM, and VPC to better understand secure architecture patterns in practice.