![](https://www.ensono.com/wp-content/uploads/2022/09/Verisk-Website-Image.jpg)
Global data & risk analytics provider migrates 2/3 of mainframe application workload to AWS
The Client
The client is a global data and risk analytics provider to the insurance, energy, specialized markets, and financial services industries.
The Challenge
The client used a mainframe platform to manage its critical, revenue-generating and back-office applications. The company wanted to migrate these workloads off the mainframe to address the business risk of reduced skills to support legacy technologies; reduce costs; and convert code to modern languages that could be maintained and evolved into the future.
The Solution
The client chose Ensono to migrate its legacy applications off the mainframe following a rapid proof of concept that delivered high quality code to its Java and C# developers and enabled application maintainability on AWS.
Ensono used its ExperThinkTM AI toolchain to automate the migration of COBOL, Db2 and Model 204 to Java, C# and Postgres, producing a high-quality, maintainable application solution. Working closely with the client, Ensono moved business critical applications to the public cloud (AWS), including the client’s largest mainframe CPU consuming application.
![](https://www.ensono.com/wp-content/uploads/2022/09/Verisk-Website-Image-768x432.jpg)
The outcomes
- Applications converted to maintainable Java and C# running in AWS cloud
- Eliminated risk of retiring legacy skills
- Reduced mainframe cost and capacity needs
- 2/3 of workload MIPS successfully migrated off the mainframe. Remaining mainframe now managed by Ensono
- Ensono’s automation toolset and methodology accelerated the client project start-up and execution
- Client now well positioned to continue to develop these key business applications into the future
Technical Specifications
- More than 3,000 COBOL programs with Db2 and MQ converted
- 700 Model 204 artifacts converted
- Migrated to C#, Java, Spring, Angular and Postgres and Aurora on AWS, to suit different development teams’ skills and preferences
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