Our Automated IMS Migration solution delivers modern Cloud-enabled databases and supporting applications that are functionally equivalent to their legacy counterparts. Our software converts the IMS database into a relational database, providing instant access to vendor and third party tools for reporting, monitoring, maintaining, and documenting. In addition, it allows the data to be accessed and analysed by a vast talent pool of DBAs with modern skillsets.
IMS Migration
Why modernise?
CHALLENGES
Scarcity of domain expertise
Developers and database administrators who understand mainframe technology are reaching retirement age and no one is trained to replace them, resulting in a steadily diminishing talent pool. As this shortage grows, the costs and risk of relying on legacy systems will continue to rise.
Limited flexibility
Successful digital transformation and business agility hinges on good data. Non-relational databases and the underlying assets that support them were not designed for today’s business demands or modern IT, resulting in difficult integrations, inaccessible data, and limited flexibility.
Exorbitant costs
Mainframes cost as much as 4,500 per cent more to operate than equivalent Cloud counterparts. This figure is compounded by rising licensing and maintenance fees for ancillary mainframe applications and databases.
Automated Data Migration
OUR SOLUTION
Our Automated IMS Migration solution includes the generation of a new relational database to replace the functionality, parent-child relationships, and other data structures that are part of your IMS hierarchical database. The new target database can reside on or off-mainframe, and can use any of the standard relational database management systems (SQL Server, Oracle, Db2, PostgreSQL).
Replacement of database functionality through Automated IMS Migration provides a complete replacement for all IMS database functionality including multi-view records, parent-child relationships, indexes, and more. Primary keys and index definitions are automatically created, and all constraints are generated into the resulting DDL. Table spaces, indexes, table names, and column names are all generated according to your naming standards.
The IMS data extract and relational load process is simple, straightforward, and fast. We can provide a number of extract variations for customers that have special requirements for a short IMS data migration window. Our data migration software gives us numerous capabilities for tailoring your data migration so that the new database meets your requirements.
The IMS database definition can be re-collected and processed through our Automated Data Migration software anytime throughout the project lifecycle. This prevents the need to put a freeze on changes to the IMS database structure, a huge win for critical business systems that change often.
Refactoring ancillary applications
Our Automated IMS Migration solution also includes Automated Refactoring of applications and languages that use the IMS database including COBOL, Assembler, Easytrieve, JCL and Procs for IMS applications.
This solution preserves the benefits of legacy systems while empowering organizations to leverage the advantages of newer platforms, especially the Cloud. This unlocks a whole new world of automation and scalability from automated testing to quality assurance, and the ability to leverage containerized deployments and orchestration with Docker and Kubernetes.
Over 35 years of mainframe modernisation experience
More than 500 successful modernisation projects completed
Over 2.5 billion lines of code refactored through automation
Intelligent modernisation, unparalleled experience
OUR PROCESS
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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.
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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.
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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.
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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.
“The re-platformed system provides the DWP and its citizens with a faster and more responsive service with improved resilience and scalability.”
Mark Bell, VME-R Deputy Director,
UK Department for Work and Pensions
Additional resources to help you modernise
GUIDE
Modernisation secrets of the Fortune 1000
This paper highlights the drivers to modernise, and profiles three global businesses who leveraged Advanced solutions for success.
WHITEPAPER
Data Migration: Liberate legacy data
This whitepaper outlines the challenge of data locked in legacy systems, the options for solving them, and a breakdown of our solutions.
REPORT
2022 Mainframe Modernisation Report
Exploring the impact of the new era of digitalisation and change on the current state of legacy systems and organisations' modernisation plans.
ON-DEMAND WEBINAR
Live discussion: 2022 Mainframe Modernisation Report
ON-DEMAND WEBINAR
How to begin your mainframe modernisation journey
WHITEPAPER
Know the details, reduce the risk
ON-DEMAND WEBINAR
Inside the largest modernisation in UK Government history
How security is driving mainframe modernisation
Although the mainframe’s stellar reputation for security remains untarnished, there are some growing ancillary risks that are influencing platform decision-making.
02 Dec 2022 by Tim Jones, Managing Director of Application Modernisation, Advanced
IMS Conversion: A technical snapshot
This blog explores our IMS Data Migration solution, and the process we take towards moving legacy data on or off the mainframe.
07 Sep 2021 by Rob Anderson, Vice President of Marketing and Product, Advanced
IMS to Db2 Conversion: How it works
IMS is still popular amongst Fortune 1000 companies, but this old favourite is now squarely in the crosshairs of a big data rivalry.
09 Feb 2022 by Rob Anderson, Vice President of Marketing and Product, Advanced
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