Telecom EU Industry Leader

Qualysoft transformed a monolithic, error-prone GPS fleet platform into a streamlined, test-hardened architecture; unlocking scale, slashing latency, and restoring reliable device ingestion.

Telecom EU Industry Leader

Key Results

70× performance improvement with optimized data flow and caching.
40% reduction in cyclomatic complexity by consolidating microservices and simplifying code paths.
8,000 devices per service instance today, with an architecture targeting 50,000.
2,400+ unit & integration tests via TDD for high confidence releases.
2,400+ unit & integration tests via TDD for high confidence releases.

Summary

Re-architect a GPS-based fleet tracking system to resolve scale, reliability, and security issues introduced during a prior microservices migration

Client

An european recognized leader in telecommunications

Industry

Telecommunications / Telematics / IoT

Location

Europe

Size

Enterprise (national footprint; high device counts)

Services

Solution architecture, backend engineering, platform hardening, QA automation (TDD), DevOps enablement, performance engineering

Technologies

.NET, SQL Server, RabbitMQ, Redis, Elasticsearch, Azure DevOps, Docker

Allocated Team

Solution architect, .NET engineers, QA automation engineer(s), DevOps/SRE, performance engineer

Cooperation period / Project duration

Multi-phase engagement with staged cutovers

Client Challenge

The existing platform struggled to onboard new clients and devices. A prior shift to microservices introduced scalability and security gaps, excessive inter-service chatter, and brittle cache updates; consuming ~50% of processing time. The system had high error rates, complex code, and no robust failover, risking GPS data loss during incidents.

Qualysoft Solution
  • Domain-Driven Design (DDD) – Clarified bounded contexts (ingestion, tracking, alerts, reporting), aligned services to domain models, and eliminated accidental complexity.
  • Service Consolidation – Reduced the number of microservices to cut network hops and failure modes; simplified contracts and message schemas.
  • Test-Driven Development (TDD) – Built 2,400+ unit & integration tests; enforced coverage thresholds and contract tests to prevent regressions.
  • High-Throughput Pipeline – Tuned RabbitMQ for bursty telemetry, Redis for write-optimized caching, and Elasticsearch for fast queries and analytics.
  • Reliability & Failover – Added multi-server failover and idempotent processing to prevent GPS data loss; health checks and back-pressure controls.
  • DevOps & CI/CD – Azure DevOps pipelines with gated releases to staging and production, blue/green strategies, observability (logs/metrics/traces), and automated rollbacks.
  • Data & Storage – Optimized SQL Server with partitioning/indexing for time-series writes and read replicas for reporting. 
Results
  • Performance – End-to-end throughput improved by 70×; latency and queue backlogs dramatically reduced.
  • Simplicity – 40% average reduction in cyclomatic complexity; fewer services, clearer ownership, faster change cycles.
  • Scalability – Stable support for 8,000 devices per instance with headroom and design path toward 50,000.
  • Quality & Safety – TDD + CI/CD cut regressions and enabled frequent, safe releases.
  • Resilience – Failover and idempotent processing eliminated telemetry loss during incidents, improving SLA adherence and customer trust.