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What's New in IBM Mono2Micro 22.0.03
By
Len Theivendra
posted
Wed April 06, 2022 09:26 AM
0
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The March release of IBM
®
Mono2Micro
™
introduces some exciting new features that help you work faster and better when refactoring Java monolith applications to microservices for WebSphere Liberty. Firstly, it provides a much simpler way to collect data on your monolith in preparation for running its AI engine to get partitioning recommendations. Secondly, this release introduces a brand new UI to view and refine microservice recommendations in both graphical and tabular forms, making it easier to gain insights on and refactor large applications.
As part of collecting data on your Java monolith application for Mono2Micro to analyze and provide partitioning recommendations, previously you were required to both analyze and instrument the source code with Mono2Micro, and then rebuild and run the application through various use cases to collect trace data on execution of code. With this release, the instrument->rebuild->rerun steps are no longer needed. Now, after analyzing the application source code with Mono2Micro you can run your monolith app as-is on the application server along with Mono2Micro's Java agent which will instrument dynamically as use cases are executed. More details here:
https://www.ibm.com/docs/mono2micro?topic=collecting-application-data
This release introduces a new workbench UI that has been redesigned from the ground up to make it easier for you to view and customize the partitioning recommendations from Mono2Micro's AI, and also gain more insights into the monolith application. The two different partitioning schemes recommended by Mono2Micro can be viewed in separate tabs, along with any custom view you create. On the side, a context sensitive details panel gives you useful information and stats based on what is currently selected (partitioning view, a partition itself, class, etc). Read all about it here:
https://www.ibm.com/docs/mono2micro?topic=viewing-microservice-recommendations
.
The UI is now better able to handle analysis data on large applications by providing a whole new way to view the data in addition to the graph, in a tabular form. Now you can switch between the graph and table representations of the partitions and other data, viewing or customizing them in either modes. For large partitions with lots of classes, the table view comes in handy where you can customize columns and what data to see, and sort columns (i.e. sort by class name, package, partition name, etc). And you can also select multiple classes to do group actions like moving them to another partition. The table view also allows you create and manage labels, which you can then assign to classes. For example, Mono2Micro already assigns the reserved label 'unobserved' to all classes that are in the monolith application but were not observed in any use case executions. You can create and add your own labels on classes to track actions and other information that helps you manage the refactoring process. Using the filtering panel you can choose to filter classes by these labels in addition to other filters. Filtering in general is a very useful way to dissect and manage large amounts of data in the workbench, be sure to check out more details at
https://www.ibm.com/docs/mono2micro?topic=recommendations-applying-filters
To take advantage of all these new capabilities and more head over to
https://ibm.biz/Mono2Micro
to download and check out Mono2Micro yourself, and also try a live interactive demo of the workbench.
#ApplicationModernization
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#ML
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