Increasing financial services flexibility with a comprehensive cloud migration
Overview
Industry
Location
Financial services
Finland
Technology Used
Azure Machine Learning
Kubernetes
Microsoft Azure
Project overview
Our client’s long-term strategy involved migrating all existing financial services development, staging and production infrastructure from legacy data centers to Microsoft Azure. Working together with the client’s cloud transformation team, Software Mind supported the design and implementation of a phased cloud migration that included building a cloud-native machine learning (ML) framework, establishing a new CI/CD pipeline and consolidating operations in Azure.
Client background
A leading Finnish software provider with over 20 years of experience driving growth for Nordic companies. They develop one of Finland's top cloud-based financial management software suites and are a key component of an international group that specializes in financial and HR services.
Goals
The goal of this project was to modernize operations and increase platform stability and scalability, while reducing infrastructure maintenance and operational costs. This cloud migration also aimed to enable cloud-native application development, improve platform development flexibility and accelerate release and innovation cycles. The team working on this project had to ensure business continuity during staged migrations and re-architect services to align them with cloud-native principles.
Results
One of the client’s largest infrastructure transformation projects
Migrating a few hundred staging, production and development virtual machines as well as development, staging, quality assurance and production environments
40% faster deployment time
Establishing quicker and more stable build and deployment processes and creating CI/CD pipelines that improved release cycles
Reduced operational costs by nearly 30%
Significantly decreasing infrastructure maintenance effort and costs, while cutting operational costs by retiring legacy data center infrastructure and optimizing workloads in Azure
Increased service scalability
Improving the scalability and flexibility of the client's financial services and reducing reliance on on-premises infrastructure
New ML-driven functionalities
Rolling out ML-driven predictive insights to production within the first year of the cloud migration and creating new business opportunities
Enhanced software development
Adopting cloud-native development practices across teams
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