Modernizing Monolithic APIs with Amazon ECS: From Single Node to Scalable Microservices

Challenge: Monolithic Single-Node Architecture Causing OOM Failures and Downtime

TargetBay is a marketing automation SaaS provider whose core platform serves thousands of e-commerce merchants via RESTful APIs. The entire application stack — NGINX, PHP-FPM-based APIs, batch processing, and scheduled jobs — was deployed on a single c5.2xlarge EC2 instance.

This monolithic architecture created compounding operational risks:

• Monolithic Single Node: All application components shared a single compute instance, meaning any failure or resource spike affected every workload simultaneously.
• Resource Contention: Traffic spikes triggered out-of-memory (OOM) events, crashing services and causing frontend downtime for merchants relying on real-time API responses.
• Limited Scalability and Fault Tolerance: The only scaling option was vertical (upgrading the instance size), which required downtime and offered no redundancy against instance failure.
• Slow Deployment Cycle: Releasing updates to any component risked disrupting live traffic across the entire platform, forcing cautious, infrequent deployments.

Solution: Decomposing Monolith into Dockerized Microservices on Amazon ECS

FactualMinds decomposed TargetBay’s monolithic application into independently deployable microservices running on Amazon ECS, backed by a cost-optimized compute layer and modern traffic management.

Microservice Decomposition:

• Converted each major component — public-api, jobs-processor, and admin-api — into separate Dockerized microservices with independent lifecycles and resource profiles.

ECS Cluster and Compute Optimization:

• Created an ECS Cluster backed by an Auto Scaling Group of c5.large EC2 instances
• Enabled a Spot and On-Demand instance mix to optimize compute spend without sacrificing availability
• Attached ECS Capacity Providers for dynamic container host scaling based on cluster utilization

Traffic Management:

• Deployed an Application Load Balancer with path-based routing to direct traffic to the appropriate service:
  • /api/v1/* routed to public-api
  • /jobs/* routed to jobs-processor
• Configured health checks for each target group to enable zero-downtime rolling deployments

API Gateway and Security:

• Integrated Amazon API Gateway with throttling at 100 requests per second, IAM-based authentication, and AWS WAF for request filtering

Auto Scaling and Observability:

• Configured ECS Service Auto Scaling with per-service policies that trigger scaling at greater than 60% CPU utilization
• Built CloudWatch Dashboards tracking CPU, memory, request latency, and error rates across all services

AWS Services Used for ECS Microservices Architecture

• Amazon ECS (EC2 Launch Type) — Container orchestration for microservices
• EC2 Auto Scaling Group — Dynamic compute capacity for ECS cluster hosts
• ECS Capacity Providers — Automated container placement and host scaling
• Application Load Balancer — Path-based routing and health-checked traffic distribution
• Amazon API Gateway — Throttling, authentication, and WAF integration
• Amazon CloudWatch — Monitoring dashboards, alarms, and metrics
• AWS IAM — Fine-grained access control across services

Results: Zero-Downtime Deployments and Independent Microservice Scaling on ECS

The migration from a monolithic single-node deployment to a microservices architecture on ECS delivered measurable improvements across reliability, cost, and delivery speed:

• Zero-downtime deployments through rolling updates with health-checked target groups, eliminating the risk of service disruption during releases
• Independent microservice scaling allowing each component to scale based on its own resource demands rather than over-provisioning shared compute
• Reduced compute costs by leveraging Spot instances for fault-tolerant workloads alongside On-Demand instances for critical services
• Faster release cycles as teams could deploy changes to individual services without coordinating full-stack releases
• Improved fault tolerance with no single point of failure — individual service failures are isolated and auto-recovered without impacting the broader platform

For more on DevOps pipeline setup and microservices on Amazon ECS, see our DevOps service page.