UpchaarNepal Logger System
Problem it solves
Internal logging and observability system supporting UpchaarNepal’s distributed healthcare microservices.
Overview
The Logger System supports reliability across UpchaarNepal’s microservice architecture. It centralizes operational logs from gateway traffic, event consumers, cache behavior, and payment retries so engineering can diagnose issues across patient, doctor, clinic, pharmacy, diagnostic, and admin services.
I built this as a Full Stack Software Developer at Upachaar Nepal (Jun 2024 - Dec 2025).
Architecture and technical approach
Event-driven services using Apache Kafka and Redis benefit from correlated logs when requests cross multiple healthcare domains.
Implementation used Node.js, Express.js, NestJS, Apache Kafka, Redis, and Docker. The same names appear on the skills page.
Key features
- Centralized logging across healthcare microservices
- Visibility into gateway, consumer, cache, and payment flows
- Support for diagnosing distributed failures
- Operational backbone for production reliability
Technologies used
- •Node.js
- •Express.js
- •NestJS
- •Apache Kafka
- •Redis
- •Docker
Challenges and solutions
Distributed healthcare traffic produces noisy, cross-service logs. The challenge was structuring observability so failures in booking, payments, or messaging could be traced without slowing the services themselves.
Screenshots
Logger System cover representing observability across UpchaarNepal microservices.
Contribution and what I learned
The Logger System underpins UpchaarNepal’s production healthcare stack by making multi-service failures diagnosable.
More product work is on all software projects and the Upachaar Nepal role. Featured work is also previewed on Diwash Bhattarai's homepage.