case study / fintech / Pay Advance Application

Pay Advance Application

Lohika shared the best practices of migration from a monolith to microservices and built cloud-based scalable infrastructure for microservices architecture from scratch.

Challenge

Due to the rapid growth of the number of users the existing vertical scaling capabilities were almost exhausted. The company decided to start the migration from the monolith to microservices architecture. Our client had no practical experience in implementing a microservices architecture and underlying infrastructure and decided to involve 3rd-party experts. Lohika was ready to share its expertise in building cloud-based scalable solutions leveraging microservices architecture.

Overview

Our client provides a unique financial mobile application, which has become incredibly popular due to the uniqueness of the service and ease of use.

Solution

Our collaboration started with an analysis of the requirements and an assessment of the existing architecture. The objective of this step was to understand the big picture and consider a potential scale and load. Based on the information collected, Lohika team has offered several possible solutions for building a microservices architecture based on various cloud services, infrastructure, and orchestration tools. Also, Lohika team has provided a comparative analysis of the possible solutions and our recommendations, that allowed the client to consider all the pros and cons and make an educated decision about the best fitting solution.
Our team was involved in splitting of the existing .NET monolith application and building a microservices architecture based on .NET Core, AWS, and Kubernetes. As part of the delivery, Lohika introduced DB migration approach that allowed ensuring database schema changes are controlled and schemas are the same across all environments are up-to-date with no manual alternation.
Cloud native solutions are all about observability, so Lohika team has created a framework for logging and monitoring using FluentBit, Kibana, ElasticSearch, Prometheus, and Grafana.
Our engineers built designed and implemented CI/CD infrastructure and pipelines using Jenkins, Nexus, Terraform, Docker, and Kubernetes that allowed our client to significantly reduce the time of deployment of changes to production.

Results

The new microservices architecture implies the system elasticity and horizontal scalability in the conditions of an ever-increasing number of users, load and volume of data.
The cloud infrastructure allows the client to rapidly deploy changes to production Kubernetes cluster ensuring all the necessary automated tests pass. Robust logging and monitoring system makes it possible to respond to and troubleshoot emerging issues in real-time mode.

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