AWS Partner Network (APN) Blog

Modernize Natural and Adabas Workloads on AWS with Advanced’s Application Transparency Platform

By Cindy Howard, VP of Technology and Solutions – Advanced
By Robert Young, Head of Pre-Sales – Advanced
By Brenesh Stanslas, Sr. Partner Solutions Architect, Migrations and Modernizations – AWS
By Bruno Sahinoglu, Principal Partner Solutions Architect – AWS

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Mainframes continue to support critical workloads and core transactional applications for many enterprises with Adabas database and Natural programming language.

Companies who continue to rely on Natural and Adabas face two growing difficulties: product license cost and a shrinking pool of resources capable of maintaining and extending the 4GL (Fourth Generation Languages) and its inverted list database. As a result, many are considering modernization to reduce their reliance on these technologies.

These same businesses are looking to enable agile evolution of the customer experience through digital transformation. This effort requires a scalable, low-cost environment that integrates with modern cloud-based technologies and development practices.

In addition, customers are looking to improve time-to-market with agile development while adopting cloud capabilities, better reporting, and easier integration with mobile, social, and analytics applications.

This combination of factors often drives Natural and Adabas modernization to Amazon Web Services (AWS). This post highlights the modernization paths available for Natural and Adabas with Advanced and AWS. Advanced offer refactor and replatform functionality, as well as self-service migration options.

Advanced is an AWS Specialization Partner with the Mainframe Modernization Competency. A leading international provider of mainframe migration and modernization services, Advanced has over 35 years of experience across more than 500 successful projects.

Solution Overview

Key to minimizing risk while modernizing Natural and Adabas is the maturity of the options offered by Advanced’s unique software and services.

The Advanced Application Transparency Platform (ATP) software acts as the cornerstone of these solutions. Each provides an end-to-end strategic pathway to lower costs by eliminating the supplier license costs for Natural and Adabas, while preserving legacy assets and business rules.

The illustration below depicts the source to target mapping with Advanced ATP.

Natural Adabas workload modernization - Source to Target mapping

Figure 1 – Natural Adabas modernization overview.

Automated Refactoring of Natural to Java or C#

Advanced’s ATP solution can refactor Natural source code into a functionally equivalent modern application either in Java or C#. Refactored code can be maintained or extended with any modern integrated development environment (IDE). ATP also provides options for embedding the Natural language in the comments to help former Natural developers find business logic within the structure of the new application.

Technical capabilities of Natural/Adabas refactoring are:

  • Automatically refactor all Natural objects including programs, subprograms, data definition modules (DDMs), maps, and data area types.
  • Maintain and execute refactored code as native Java or C# .NET on AWS.
  • Auto-refactor Natural Report Mode code to Structure Mode.
  • JCL conversion to PowerShell or Spring Batch XML (Java JSR352 standard).
  • Support customers who opt to retain their JCL and PROCS as-is in the target environment and execute them using Advanced’s eavJES solution.
  • Assure the refactored code meets the quality standards set by SonarQube.
  • Maintain and enhance the refactored applications as web applications (Angular for user interfaces).

Natural Adabas workload Modernization: Refactor Landing Zone in AWS

Figure 2 – Natural Adabas workload modernization – Refactor landing zone on AWS.

Once the legacy applications and databases are refactored and deployed into AWS, developers can extend the application functionality using standard DevOps tools and CI/CD using services like AWS Code Pipeline and AWS Code Build. Business logic from the legacy Natural code is preserved as-is.

An additional level of optimization can be applied in ATP for efficient delivery and to take advantage of AWS services.

Replatforming Natural

Enterprises that wish to retain their legacy codebase can execute Natural syntax on Windows using ATP. The resulting applications are identical to those on the mainframe, minimizing the amount of change that occurs when migrating from the mainframe to AWS.

Replatforming provides a relatively low-cost and low-risk way to reduce mainframe operating expenses and maintain the business value that the original applications provide.

  • Since the Natural syntax remains as-is, organizations can continue to leverage their existing Natural development talent while providing them with new features within ATP.
  • ATP includes a fully-featured UX development workbench for Natural developers, which includes Natural code analysis, flow diagramming, impact analysis, pattern matching, version comparison, and interactive debugging capabilities. In other words, Natural development teams can continue to develop and maintain applications with the support of modern, efficient development tools.
  • For the execution of the Natural Online programs, ATP interprets and executes each Natural command at a byte level, allowing existing Natural applications to execute as-is against the new relational database without any changes to the original code.
  • ATP processing engine interprets the Natural READ, WRITE, and other I/O commands. ATP creates equivalent SQL syntax to perform the data access/updates against the new database.
  • ATP enables modern business intelligence (BI) tools to integrate with the relational database in ways the legacy system would never have allowed.

In the replatformed environment in AWS, JCL runs in Advanced’s eavJES batch execution environment, an add-on to the ATP suite with a fully featured set of tools. Developers can maintain the JCL and PROCS, resulting in flawless execution with very little change.

Execution results in the same actions, cataloguing, restart, and recovery as in the mainframe environment. The catalog is constantly monitored and maintained during job execution and can even allow command line manipulation of datasets.

Path to Extended Modernization After Replatforming

The Replatforming Natural path aids customers who choose to undertake a phased approach for moving into a modern language. ATP provides the ability to automatically refactor the codebase to Java or C# through a simple transformation in ATP using the “Save As” function.

The newly-refactored Java/C# code is functionally equivalent to the legacy Natural application. The new code operates using a web UI and Angular. This feature enables extended modernization to support the re-use of developers’ existing skillsets in Natural and their extensive knowledge of the applications, while deploying as Java or C#.

Natural Adabas workload modernization: replatform Landing Zone in AWS

Figure 3 – Natural Adabas workload modernization – Replatform landing zone on AWS.

Automated Adabas Migration

In conjunction with either Automated Refactoring or Replatforming Natural, all Adabas databases will be migrated to relational equivalents (Amazon RDS for SQL Server, Oracle, Db2, Amazon Aurora).

Each resulting relational database will have the same functionality and traversal capabilities as the original Adabas. Natural unload programs are auto-generated to allow the client to extract the data from Adabas into a format that is ready-to-load to the new relational database.

The new relational database is generated with base tables, child tables, and grandchild tables as needed to replace the Adabas Multiple Occurring Field (MU) and Periodic Group (PE) instances. This allows the new databases to include table-to-table relationships expected in a relational data model.

Access to the MU and PE data is handled by the ATP engine when running with ATP. The Natural program code receives the data in the expected view format.

  • New relational database includes the field types that are definable in the new database (small integer, integer, decimal, binary).
  • All packed and zoned decimal data is transitioned to the relational data type when it’s extracted from Adabas.
  • Binary data is preserved during the file transfer protocol (FTP) from the mainframe using scripts, which prevent the conversion of the selected fields.
  • All existing mainframe Adabas data is transitioned to a valid data type in the target database.
  • Each data field is written to the extract file in a display format, so that even packed fields are written as display fields.
  • The EBCDIC extracted data files are converted to ASCII as the data is transmitted from the mainframe to AWS. As a result of the transition from EBCDIC to ASCII, there may be differences in some sort sequences when numeric and alphanumeric data is represented in the same data field.
  • Internal sequence numbers (ISN) are preserved during the extract process. New row occurrences will receive the next available ISN number using the optimum mechanism provided by the new relational database management system.
  • Includes the generation of Natural programs and related JCL to migrate the Adabas data to sequential files for loading to the new relational database.

Be aware that Adabas replacement often requires materialized views to replace super-descriptor and sub-descriptor functionality, and that stored procedures ensure accuracy and high performance in the new solutions. The target database should support the features needed to replace this functionality.

Benefits of Natural Modernization with Advanced ATP

With Advanced ATP, modernizing your Natural and Adabas environment to AWS will provide the following benefits:

  • Options for both replatforming and refactoring with ATP, along with automated Adabas migration.
  • Cost reduction by eliminating mainframe MIPS (millions of instructions per processor second) and Natural Adabas license costs.
  • Modern relational database unleashes the data for distributed applications on AWS.
  • Report generation capability improvements.
  • Better developer experience with a modern IDE, ATP environment, and DevOps enablement.
  • Ease of user community adoption through identical functional experience.

Conclusion

With Advanced’s Application Transparency Platform (ATP) Platform, customers can migrate from procedural Natural code and pre-relational Adabas databases into AWS either by refactoring or replatforming.

Advanced ATP is designed to support customers regardless of where they are in their modernization journey. As an AWS Mainframe Modernization Competency Partner, Advanced has the technology and the expertise to successfully move away from Natural Adabas and unleash the power of AWS.

Learn more about Natural and Adabas workload modernization with ATP from Advanced, and check out the AWS Marketplace listing:

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Advanced – AWS Partner Spotlight

Advanced is an AWS Specialization Partner and leading international provider of mainframe migration and modernization services. Advanced has over 35 years of experience across more than 500 successful projects.

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