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Unleash the Power of Mainframe using API Economy

The trend across today's industries is to move toward open web APIs. Enterprises are transforming their business models to embrace API Economy in a connected digital world with a large community of developers.

What has mainframe got to do with the API Economy?

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Existing mainframe systems have been built up over the years and encapsulated enormous valuable business logics and data. These rich and mission-critical sources of business services and information are critical for digital transformation. As enterprises address business transformation, they will have to make their mainframe data and applications available as APIs in the total digital solutions. 

In my recent engagements with enterprise clients, clearly, both the healthcare and financial services sectors are becoming major drivers of digital innovation.  I have been frequently asked to advise how to revitalize, and incorporate enterprises' mainframe assets in digital environments. Here are some enterprise clients' business cases related to digital transformation:

financial services company, which handles majority of credit and debit processing, including prepaid cards, is looking to re-engineer their mainframe based complex and high speed transaction and data processing. Currently, I am leading an architectural proposal to modularize the mainframe portfolio and expose core capabilities as micro services and REST APIs to expedite future development efforts in meeting business demands on a timely basis.  Our proposal also addresses their skill issues with emerging technologies for decades to come. The proposal lends itself for a commercial project with defined outcomes.

This year, Infosys was chosen as the preferred partner for an American health insurance company's digital transformation initiatives. While our engagement teams were working diligently to deliver the transformation, this client also actively approached Infosys for mainframe integration. Their digital initiatives will not work without incorporating their family of systems, which are mainframe based mission critical business capabilities. The primary challenge they are facing is to expose their mainframe assets as REST services, with transactional tracking and problem determination capabilities across multi-components and platforms.

The other case is a Brazilian large banking and financial services company. This bank's core banking system resides on mainframe, and processes more than 2.5 billion transactions every day. With increased transaction volumes for digital banking, including a recent merger, and upcoming public/hybrid clouds, the bank is facing challenges for continuing integration with mainframe systems with same QoS and reduced MIPS. The mainframe revitalization proposals have been well accepted by the Bank's technical community for execution.

How to expose mainframe assets as micro services, and nature APIs?

Creating a successful API, however, is not easy. Creating APIs for mainframe data and applications is even more difficult, because it requires deep integration capabilities, especially in exchanging data between legacy and newly-written applications in the API digital world.

Solving such difficult and challenging problems of data exchange require certain technology like CAM (Common Application Metamodel). CAM is a standards based technology which facilitates data transformation from one language and platform domain to another, and also simplifies new applications creation. CAM is highly reusable and independent of any particular tool or middleware, and has been adopted and implemented as the underpinning in heterogeneous systems for enterprise application integration. Language based importers, which parse programming language source files and import relevant language metamodels,  have already been implemented in a variety of AD tools, and can also be re-used in any new tools to be created.

A comprehensive development tooling can therefore readily be developed by leveraging CAM and associated language importers to expose mainframe applications, e.g. CICS and IMS transactional applications, as micro services. Such tooling will read and parse legacy applications' interface declarations, e.g. COBOL copybooks, PL/I include files, and other source files, to generate REST / JSON services.

Further considerations also need to be evaluated regarding data transformation techniques. A development tooling can be designed for interpretive marshalling by generating metadata to be used during execution time. The very same tooling can also be designated to generate stub routines for compiled marshalling instead. In general speaking, compiled marshalling is faster than interpretive marshalling, though there are trade-offs between these two marshalling techniques. However, a hybrid approach between these two techniques should be considered to resolve the trade-offs.

Once REST / JSON services are created from legacy applications, these services can then be easily mapped as standard, language-agnostic interfaces to REST APIs, according to the OpenAPI Specification. These generated invocable APIs allow both human and computer to discover and understand the capabilities of the mainframe services. New apps can also be easily developed with these APIs to interact with mainframe assets with minimal implementation logics. 

With mainframe APIs, enterprises can now readily extend their digital reach for consumption in mobile applications, cloud applications and Internet of Things (IoT).


It's Good.. Now legacy applications moving to Manhattan API..Which we are implementing right now.

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