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Schimerol — Core Product

Led end-to-end development of Schimerol's primary software product, building a scalable backend and APIs.Node.js · Express · PostgreSQL · CI/CD
February 1, 2024

Overview

At Schimerol I led the full lifecycle for the company's principal software offering — from initial architecture to production deployment.

Key Contributions

  • Architected and implemented the backend system, including database schema design and core API endpoints.
  • Ensured the system was highly available and scalable to support growth.
  • Worked closely with product and operations teams to iterate on features and deliver a production-ready platform.

Technologies

  • Node.js, Express
  • PostgreSQL
  • Dockerized deployments
  • CI/CD pipelines

Outcome

Delivered a scalable and maintainable product that met the company's performance and reliability goals.

Problem

Schimerol's legacy system struggled with scale and brittleness: on-boarding new tenants and rolling out features required manual ops, deployments were slow, and performance degraded during peak use.

Solution

I re-architected the core product with an emphasis on reliability and operability. The new design introduced a clear domain model, resilient APIs, and containerized deployments to allow safe, frequent releases.

Architecture

Text
Clients (web/mobile) -> API Gateway -> Microservices / Node.js APIs -> Postgres
                                 |                                |
                                 +-> Background workers (queue) -> Metrics & Monitoring

Key features delivered

  • Clean RESTful APIs with consistent error handling and pagination
  • Schema-driven migrations and a versioned DB strategy
  • Containerized services with health checks and automated CI/CD
  • Role-based access control and audit logging

Screenshots / Media

Schimerol product 1
Schimerol product 2

Metrics

  • Achieved 99.95% uptime after rollout
  • Reduced average response latency by 45% for critical endpoints
  • Deployment lead time reduced from days to under 30 minutes

Lessons learned

  • Start with the failure scenarios — designing for common failure modes made the system far more resilient.
  • Automating the release pipeline pays off quickly: frequent, small releases lowered risk and increased feedback velocity.

Next steps

  • Add observability dashboards for business KPIs and provision canary deployments for high-risk changes.