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Modernizing Fleet Management: Monolith to Microservices Migration

Case Study

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The Client

The client was a telematics fleet management company with over 1000 employees, with their products including everything from on-board diagnostics to CO2 emissions reporting.  They’re also a pioneering force in fleet management and EV adoption, and support industries as diverse as logistics, government, pharmaceutical, and everything in between.

The Project

We were tasked with decomposing, evaluating, and recombining two monolithic applications into a collection of wholly independent, fully scalable, and effortlessly maintainable microservices.

The client was looking for overall improvements to system agility, reducing time-to-market for new features, and enhancing fault isolation.

This bevy of hardware technologies, software features, and marketing and business goals posed a uniquely complex set of interrelated challenges, and at first glance might’ve seemed as functionally infinite.

Key Challenges

Key Challenge 1

Streamlining Development Cycles

Тackling the existing large-scale architecture, which presented significant challenges – including slow development cycles due to tight component coupling.

Key Challenge 1

Lack of Documentation

Multiple potential risks, including Integration issues, data loss, performance degradation, and other unexpected side effects.

Key Challenge 1

Scaling and Cascading Failures

Difficulty in scaling individual components independently. Increased risk of cascading failures.

Our Solution

Legacy Platform

Established auto-scaling capabilities

Chose a cloud-native environment to handle fluctuating workloads

Legacy Platform

Improved Microservices Architecture

Established and fostered clear service boundaries and independent deployments

Legacy Platform

Monolith to Distributed Migration

Safely and efficiently migrated data from monolithic databases to a distributed architecture

Legacy Platform

Rigorous Testing

Unit integration and end-to-end tests for each microservice

Legacy Platform

API-first

Utilized API gateways to manage traffic and ensured smooth integration with other systems, tested API compatibility between services

Legacy Platform

Debugging and Troubleshooting

Utilized distributed tracing tools to identify and resolve microservice issues

Legacy Platform

Scalability, security and performance

Improved performance and optimized processes through thorough monitoring

Legacy Platform

Advanced understanding of dependencies

Identified and isolated dependencies between components within and across monoliths

Legacy Platform

Bridging skill gaps

Eliminated skill gaps within the client’s team in different areas, including containerization, distributed systems, and others

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Implementation

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Phase 1

Entirely focused on working out and analyzing the existing monoliths, getting to grips with their individual and collective quirks, and outlining next steps.

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Phase 2

Our engineers designed and developed the initial set of microservices and improved their architecture going forward.

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Phase 3

Gradual migration of functionality from the two monoliths to the microservices produced in Phase 2.

Technology Stack

Docker
Google Cloud
Kafka
Kong
Kubernete
Linkered
Mongo DB

Results

Reduction in development time for new features, improved scalability and performance and faster time-to-market for the client’s new products and services.

Enhanced customer satisfaction due to improved system reliability and performance. Increased agility and ability to respond quickly to market changes.

Expanded agility and ability to respond and adapt to market changes quickly, and a decrease in operational costs due to improved efficiency and reduced maintenance overhead.

For our engineers, this opportunity meant that we significantly reinforced, refined, and improved development and deployment processes. These are aspects of our work that extend far beyond this project, as lessons learned will be leveraged for future microservices challenges. 

A project this large also means that our teams are now equipped with the knowledge and experience to research, tackle, orchestrate, and communicate large-scale, complex undertakings across multiple teams and positions.

The success of this partnership has since expanded to include more Software Engineering Teams and BI Developers, ensuring the client’s continued ability to stay ahead in a competitive market. 

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