Monolithic to Microservices for faster time to Market

Develop, Test, Deploy, Operate, and Scale individual components independently, and provide significant uplift for the business


  • Over 7 years of constant development and multiple MVP (minimum viable product) releases, the code base has become highly monolithic and was hard to perform 2-week release cycles. There was a need to break down the monolithic application into multiple microservices and have its own service lifecycle.
  • Take advantage of team’s diverse skillsets and build services that are polyglot in nature both at programming language and persistence storage.
  • Quickly develop and deploy services for roadshows and demos and retire them as needed.


  • Identify proper boundary context to split the services that can be loosely coupled and highly cohesive.
  • Analyze the traffic for different API methods to understand the scalability aspect.
  • Follow Microservices principles to make sure no service accesses another service data store, provide different service templates to quickly spin up new services, build services in a consistent way, and define proper API contracts between services.


  • Identified around 80 services from the monolithic application and converted them into microservices.
  • Applied necessary data model changes, split the data across multiple physical databases and logical schemas that are needed for individual services and adhere to boundary context principles.
  • Followed read-only microservice pattern where 95% of the services are read-only. This helped to quickly convert the monolithic into microservices. All write intensive responsibilities are moved into data processing layer.
  • The following technologies were chosen to implement the microservice architecture:
    • Docker was chosen for containerization and built multiple base images for quick deployment.
    • Registrator, Consul, Consul template, and Consul servers was chosen for service registry, discovery, and to apply Nginx templates dynamically.
    • Filebeat, CollectD, Logstash, Kibana, and ElasticSearch was used for logging of all services.
    • Jenkins was used for Continuous Integration and Deployment with blue-green deployment of crucial services.
    • AWS API Gateway was used as routing and mediation purpose and also to take care of caching of services using Elasticache.