Case study
FleetAnalytix 2.0
Platform rebuild, cloud operations and engineering management for FleetLogix
Mission
Move FleetLogix's day-to-day operations system onto a modern stack without stopping the business, then keep it fast, observable and economical to run as the volume of work and years of history keep growing.
Problem
The first FleetAnalytix platform had served FleetLogix for a decade and was rebuilt on a new stack through 2023 and 2024. Production scale then brought the next set of challenges: a database that struggled under peak load, dashboards that lagged when the scan queue backed up, releases that interrupted service, and little visibility into where time was going when a request was slow.
Solution
arroWebs took the platform in hand end to end: we own the architecture, review every change and run the cloud estate. Over 2025 and 2026 we re-architected the database tier, archived years of history, introduced a zero-downtime release pipeline and wired monitoring and tracing through every service. Feature work never stopped.
What the platform does
FleetLogix crews service rental-car fleets on site, and every piece of work starts as a scan on the FleetAnalytix mobile app: a badge, a vehicle, an activity. Scans flow through message queues into the platform, where duplicates and exceptions are reconciled before they count. The web portal turns that stream into dashboards at company, brand and site level, management screens for sites, employees and vehicles, scheduled reports, and a per-vehicle history that shows what happened to any car, scan by scan.
- A set of Node.js microservices behind a gateway, an Angular front end and a companion mobile app
- A large API surface over a shared multi-tenant data model, documented per service
- Scheduled jobs that build the summary data the dashboards read from
Built to run at scale
The platform runs on a clustered database with separate writer and reader nodes, so read traffic goes to replicas while the few read-after-write paths stay on the writer. A caching layer sits in front of the hottest lookups and the heaviest dashboard queries, with a fallback to the database, and older records move into yearly archives and object storage so the live tables stay lean. Releases go through a pipeline that builds a tested artifact, pushes static assets to a CDN and rolls the services over gracefully, with configuration and secrets held in a managed store so one build serves every environment. Distributed tracing, structured logs, alarms and runbooks give a view inside production when something needs attention.
- Clustered database with read replicas, sized from live metrics
- Caching on the hot paths, with fallback to the database
- Yearly archives and rolling retention on high-volume tables
- Artifact-based deployments with a validation gate and zero-downtime rollovers
- Centralised configuration and secrets
- End-to-end tracing, structured logging, alarms and runbooks
- Reviewed pull requests, staging promotion and automated data imports
- Cloud cost and capacity planning, ongoing feature work and production support
Sound familiar?
Transitioning a legacy system to a modern stack, without stopping the business that runs on it? That is what we did for FleetAnalytix. Get in touch and we'll talk through how we would approach yours.