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IBM Mono2Micro


IBM Mono2Micro, offered by WebSphere Hybrid Edition, uses the power of AI to refactor Java monoliths into microservices. The added power of machine learning and AI makes the refactoring process a semi-automated one, so that you don't have to rewrite your entire application code in order to create a microservice architecture.


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Key features
Analyze source code
Group your application code into two different partition recommendations that you can explore in the graph view.
Refactor partitions
Explore the two partition recommendations, business logic and natural seams, based on their different class relationships. You can also create your own customized partitions in the graph view.
Generate code
After exploring and customizing the partitions, you can generate the code for your partitions whenever you're ready.
Introducing Mono2Micro
IBM Mono2Micro gives users with both novice and expert skill sets and technical knowledge access to creating their own microservice architecture. The typical approach for refactoring monolithic applications into microservices is costly, time consuming, and disruptive to the development lifecycle. Refactoring and migrating applications requires an extensive knowledge of the application code, and it's easy to make errors while manually rewriting the code. IBM Mono2Micro addresses these issues and makes creating a microservice architecture more accessible for your team.
Do you already have access to WebSphere Hybrid Edition? Get started with Mono2Micro.
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Our users experience
After spending over a year on manual refactoring effort of a large monolith consisting of more than a million lines of code, Mono2Micro was able to complete analysis of the monolith and recommend about two dozen partitions, which were verified by SMEs. Mono2Micro also revealed the existence of a significant amount of potential dead code in the application that can be removed to reduce the size and the static complexity of the application.
Lead enterprise architect
Fortune 20 company
We were looking to migrate 50-70 Java based applications, some of which needed refactoring. Mono2Micro was able to drastically reduce development time, and validate what the refactoring teams were doing. We could see code clusters and how the code is used in real time, as well as dead code.
Lead architect
Financial institution
Mono2Micro was able to create partitioning that is very close to what is produced manually by domain experts. Mono2Micro outperforms most state-of-the-art academic microservice extraction techniques, especially for the class-level application decomposition.
Lead researcher
University of British Columbia