Cloud Data Migration

Step 1: Discovery

We begin every modernisation initiative with a discovery, free of charge. Our modernisation experts work with you to understand and document your business and technical goals and objectives. Together, we gather information about your mainframe estate. Everything from infrastructure to language and database types and quantities are accounted for. The discovery concludes with a workshop where we recommend optimal modernisation approaches based on information gathered, as well as rough order of magnitude (ROM) pricing, and estimated project durations and resource requirements.

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Step 2: Assess and design

The assess and design phase is performed using our automated tools to fully catalogue and develop a complete understanding of the data, application, infrastructure, and operational components of a mainframe environment. It exposes mainframe artifacts that organisations did not know they had, relationships they did not realise existed, and assets that are no longer in use. Assess and design activities provide stakeholders with valuable insight to inform data migration decisions such as ancillary application disposition strategies and target environment architectures. It also mitigates cost and risk by highlighting potential challenges and how to overcome them. At the conclusion of the assess and design phase, all in-scope artifacts are accounted for, a detailed project plan is established, and the transformation process begins.

Step 3: Transform

The transform phase includes the bulk of the Automated Refactoring activities associated with ancillary applications, the database and data conversion, and build-out of the target operating environment. Our tools generate the new target DDL, a set of custom extract programs, and the related JCL that extracts the data to a set of sequential delimited files, and generates the load syntax required to populate the new relational databases using the target database's load utility. These relational databases are delivered ready for creation and population, including the target DDL for the database definition, appropriate extract programs, JCL for extract execution, and load syntax for populating the relational tables. During transform, we also refactor applications in pre-defined work packets, perform functional tests, and deliver them into the DevOps pipeline. While customer teams build, test, and deploy these work packets in the target environment, we refactor the next work packet, iterating until the entire mainframe estate has been transformed.

Step 4: Test and deploy

The test and deploy phase begins with the receipt of work packets through the DevOps toolchain as they are delivered from iterative refactoring activities in the transform phase. If issues arise, the work packet is passed back to us where we review the code, adjust our tooling, reprocess the work packet, and send it back into the DevOps pipeline to resume testing and deployment. This process repeats until the entire refactored estate has been deployed.

Prior to go-live, we refresh the target environment by transforming a final snapshot of the mainframe environment to account for changes that have taken place throughout the modernisation project as part of normal business operations. Fortunately, since all adjustments and optimisations have been made to the automated refactoring and data migration tools and not the refactored code or converted databases, this final refresh can be delivered into production over a weekend, eliminating code freezes.

Step 5: Support

We work closely with you and your team to ensure a smooth transition into production. Part of this transition includes the cooperative construction and testing of a go-live production cutover plan to reduce the potential risks associated with application deployments. We also provide on-demand assistance during the warranty period following production deployment, as well as post-transformation support of the modernised application.