01 PROBLEM
Monolithic e-commerce platforms struggle to scale during high-traffic events. The objective was to architect a robust, distributed microservices platform capable of independent scaling.
METRICS
Architecture
Microservices
Database
MongoDB
Queue
Redis Pub/Sub
02 RESEARCH
Investigated event-driven workflows and communication between isolated services. Decided on Redis Pub/Sub for asynchronous message brokering and isolated databases for service data storage.
03 ARCHITECTURE
+------------+ +------------+ +------------+
| Order Svc +----->+ Redis Bus +----->| Inven. Svc |
| (Node.js) | | | | (Node.js) |
+-----+------+ +------------+ +-----+------+
| |
v v
+-----+------+ +-----+------+
| MongoDB A | | MongoDB B |
+------------+ +------------+
04 CHALLENGES
Monitoring performance across distributed boundaries can be a black box. Debugging requests that traverse multiple independent services was initially complex.
05 SOLUTION
Implemented distributed tracing and system metrics using OpenTelemetry, which provided deep visibility. Containerized each service with Docker and custom API routing.
06 LEARNINGS
- >Microservices add operational complexity but solve horizontal scaling.
- >Distributed tracing is fundamentally required from day one in a microservices ecosystem.