Case Study
Accelerate the transition to microservices with Domain Driven Design
We have revamped the software design process for a client in the energy & utilities sector, transitioning from a traditional multi-tier architecture to a complex, large-scale microservices architecture.
Where: Italy
Where: Italy
Challenge
The transition to microservices helps reduce management costs, but it requires standardizing application development, defining clear patterns, and implementing an infrastructure capable of dynamically supporting diverse business needs and workloads.
Approach
The adoption of Agile methodology has allowed us to develop the infrastructure iteratively, progressively refining the system to make it increasingly resilient and versatile. To manage the project's complexity, we implemented methodologies such as Domain Driven Design, Test Driven Design, and Event Driven Design, integrated with other best practices developed through our decade-long experience in application modernization.
Digital Ecosystem
Solution
Digital Ecosystem
First, we defined the shared services across all microservices, including logging, auditing, event management, component communication, authentication, authorization, and API gateway. We then introduced streaming services and large batch management. The use of the Confluent platform has improved event isolation, optimized performance, and reduced management costs.
The solution hosts tens of thousands of microservices and enforces development standards; it enables a complete overhaul of applications and more uniform management of IT resources. The roadmap is continuously evolving with the integration of new technologies (IoT, digital twins, artificial intelligence, edge computing).
We also support the client in the creation, configuration, and management of DevOps pipeline components, as well as the development of new internal products.
Results
Standardization of application development processes
Removal of vendor lock-in
Improvement of code quality
Elimination of large synchronization batches between applications
Impacts
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