HAWK.
A central view of retail point-of-sale systems, helping teams catch issues before customers do.
- Role & Responsibilities
- Software Engineer & Team Lead at OLR
- Timeline
- 2021 — 2022
- Core Tech Stack
- React, Next.js, Node.js, InfluxDB, AWS, Terraform
Store POS Terminals
Thousands of point-of-sale registers across multi-store retail chains sending diagnostic telemetry.
Lightweight daemon polls system metrics without taking CPU away from cashier transaction processing.
Context & Domain
At OLR, I built HAWK from the ground up: a monitoring platform that gives retailers a central view of their point-of-sale systems. I worked directly with senior leadership and clients to take the product from an initial idea into production.
Problem & Constraints
Support teams needed to see the health of distributed retail systems and catch issues before they affected store operations and customers. The product had to turn incoming telemetry into a useful operational view.
Engineering Approach
I worked with enterprise clients and product managers to define requirements, scope deliverables, and set milestones. Alongside hands-on development, I led and mentored four engineers, ran planning and code reviews, and managed staging and production deployments.
Architecture & Systems Design
React and Next.js provide operational dashboards, with Node.js REST APIs and InfluxDB for telemetry. The API layer includes session-token authentication, OpenAPI documentation, and queries tuned for InfluxDB and SQL. Kapacitor and PowerShell support distributed alerts. Cloud deployment uses AWS, Terraform, Jenkins, and Nginx.
Outcomes & Measured Impact
HAWK reached production and gave retail support teams a shared view of point-of-sale systems, with automated alerts to detect failures before client outages. I owned delivery across the frontend, backend services, and deployment while supporting a team of four engineers.