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Secure AWS ECS Delivery for a Digital Wellness Platform

Container delivery, content analysis, media conversion, secrets, and monitoring were automated on AWS.

Amazon ECS
DevSecOps Automation
Content and Media Processing
Secure AWS ECS platform with automated CI/CD, WAF-protected application traffic, private services, content analysis, media conversion, managed secrets, and observability

Problem Statement

Centerboard Wellness Center needed a repeatable way to deploy and operate connected frontend and backend services that handle user content and media. Manual infrastructure work, sensitive environment values, content analysis, media conversion, monitoring, backups, and scaling all had to be addressed without expanding the operational burden.

CLIENT

Centerboard Wellness Center

PROJECT SCHEDULE

Oct 2024 to Feb 2025

PROJECT SIZE

$50,000 to $199,999

Proposed Solution

Containerized services on Amazon ECS

Frontend and backend services were packaged as Docker containers and deployed on Amazon ECS with scaling policies for changing demand.

Infrastructure managed with CloudFormation

CloudFormation replaced repeat console changes with reviewable infrastructure definitions for networks, services, and supporting resources.

Protected traffic and secrets

AWS WAF filtered inbound requests, while AWS Secrets Manager kept application credentials out of code and deployment configuration.

Automated content analysis

Amazon Rekognition, Textract, and Comprehend handled image, document, and text analysis as part of the content workflow.

Event-driven media conversion

AWS Lambda coordinated media processing tasks and AWS Elemental MediaConvert produced required media formats without dedicated processing servers.

Automated delivery

AWS CodePipeline and CodeBuild, with GitHub Actions where appropriate, built and deployed changes through a repeatable CI/CD process.

Shared operational visibility

Amazon CloudWatch, Prometheus, and Grafana combined service health, application metrics, and alerting for faster investigation.

The platform separated user traffic, application runtime, asynchronous content processing, and operational controls. This kept the deployment path repeatable and let each processing service scale for its own workload.

Core tech stack we work with

Leveraging the Leading Programming Languages and Frameworks to Deliver Reliable, Scalable Solutions.

Docker
AWS
GitHub
Prometheus

Outcomes & Success Metrics

Measurable improvements in performance, reliability, scalability, and cost.

Manual Deployment

Reduced manual deployment efforts

Security

Improved security with WAF and Secret Manager

Content

Automated content moderation

Scalability

Scalability achieved via ECS auto-scaling

System Health

System health monitored through CloudWatch and Grafana

Lessons Learned
This engagement worked because security, deployment, and media processing were designed as one operating model. Infrastructure definitions reduced configuration drift, managed AWS services reduced server overhead, and content processing stayed outside the synchronous application request path.

Need to secure and automate an ECS workload?

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