Global Consulting Practice White Paper Mainframes: Bridging Legacy Systems. Building Digital Futures.
About the Author K Vaidyanathan K Vaidyanathan is a senior consultant with the Global Consulting Practice IT Performance Group at Tata Consultancy Services (TCS). He has more than 17 years of experience in IT services and has delivered successful consulting engagements to global customers in banking, insurance, telecom, life sciences, and retail. He has architected solutions for a wide range of areas such as mainframe optimization, consolidation, legacy application exit, and capacity upgrade, as well as IT disaster recovery strategy and database technology migration planning. He has a Master's degree in Computer Applications from Bangalore University.
Abstract In this digital age of global connectivity, the pioneer of massive computing, the mainframe ecosystem, is unfairly tagged as 'legacy.' This paper attempts to dispel the unjust profiling and demonstrate the ongoing relevance of mainframes. Mainframe hardware platforms and software ecosystems have evolved continuously. Advanced mainframes are 'digital ready' for the next generation. They can host and integrate contemporary IT systems in multiple ways. Legacy systems on mainframes serve as the backbone of business operations. They present optimization and integration opportunities to third-party service providers and newly developed distributed service-oriented architecture (SOA) systems. They ensure robustness, performance, scalability, availability, security, and business continuity, and are cost-effective.
Contents Mainframes Are Still Relevant 5 Technology Evolution Enables Cost Benefits 5 Mainframe Utility Service Models Trigger Cost Optimization Demands 5 The Role of Specialized Mainframe Processors 6 Re-hosting Solutions 6 Repurposing and Bridging Legacy with Distributed Systems 7 Repurposing of Legacy Workloads 7 Transformation Drivers for Migrating Legacy Workloads 7 Bridging Legacy with Distributed Systems 8 Mainframes in the Digital Paradigm 8 Mainframe on the Cloud 8 Systems of Engagement 10 Big Data Systems on Mainframes 10 Enterprise Mobility on Mainframes 10 Conclusion 11
Mainframes Are Still Relevant Legacy mainframes are trusted backbone platforms for executing critical business transactions. They are robust, reliable, scalable, and most importantly, resilient. Mainframe ecosystems have evolved to stay relevant, and despite their bad press, they have contributed to major technology milestones in the last decade. Mainframes are now digitally compatible and can be integrated with distributed Service Oriented Architecture (SOA) based systems. The total cost of ownership of mainframes is significant. Enterprises can turn this into an opportunity and optimize core business legacy transaction systems in the short and medium terms. Bridging legacy with contemporary and next-generation systems prior to transformation is inherently beneficial to enterprises and cost-effective in the long term. Retaining and investing in mainframe upgrades is a compelling option since mainframes are adaptive, possess superior attributes, and ensure business continuity, all of which is required for hosting next-gen digital systems. Facts about Mainframes 96 of the world's top 100 banks, 23 of the top 25 US retailers, and 9 out of 10 of the world's largest insurance companies still use mainframes Mainframes process roughly 30 billion business transactions per day, including most major credit card transactions and stock trades, money transfers, manufacturing processes, and ERP systems. ¹ Technology Evolution Enables Cost Benefits Third- party utility and offshoring service models relieve the enterprise of managing complex mainframe hardware, infrastructure system software and legacy application systems in-house. Utilizing such models entails optimization initiatives, including offloading and re-hosting solutions. Mainframe Utility Service Models Trigger Cost Optimization Demands Historically, few enterprises outsourced their mainframe data centers to infrastructure service providers. Most had in-house mainframe platforms. But now enterprises typically outsource and maintain charge-back business models with service providers and pay by usage. Like paying electricity bills, an enterprise pays by the monthly use of CPU and storage. In addition, charges for annual software license renewal and for native technology stack products are also levied. Sometimes, this utility service model entails significant operational expenses for IT organizations due to high usage of mainframe CPU and storage caused by both undetected performance inefficiencies in legacy systems and unsupported versions of system software infrastructure portfolio. Because of shrinking IT budgets, CXOs drive optimization efforts across the mainframe environment to free up millions of instructions per second (MIPS) capacity of CPU resources and reduce expenses of legacy IT systems supporting "run the business" operations. This [1] SHARE, Don't Believe the Myth-Information About the Mainframe, accessed on May 14, 2015 http://www.share.org/d/do/9005 5
situation provides ample opportunities for IT service providers to develop and offer infrastructure software license portfolio and application performance optimization solutions. With these services, an enterprise can achieve operational efficiency and reduce costs. Tactical techniques include offloading workloads into modernized mainframe special processors and mid-range platforms to reduce consumption. The Role of Specialized Mainframe Processors To keep up with rising customer demands and emerging trends, mainframe vendors offer specialized CPU engines. These CPU engines are tuned to run Linux and Java applications, and database housekeeping utility workloads, in an optimized manner. Such specialized CPU engines help enterprises to offload the eligible workloads from the native mainframe processors and contribute to a reduced mainframe total cost of ownership (TCO). Re-hosting Solutions Mainframe workloads based on native technology stacks can be re-hosted on low-cost Linux or UNIX mid-range platforms using re-hosting solutions. Such migration and re-hosting is executed by system integrators and migration service vendors, with minimum effort and code changes. As a pilot, an enterprise usually selects a simple application workload, built on a basic technology stack. Re-hosting involves: n Migrating full or partial legacy application components, or dependent services, from the mainframe to the target mid-range hardware platform n Sustaining the run of migrated application components Over time, re-hosting software vendors have made advances that address technical gaps in system integration and workload migration. Now target hardware and operating system servers, in combination with re-hosting solutions, can easily re-host transferred workloads. Such advanced re-hosting software benefits enterprises through mainframe MIPS savings. Scenario: A fund management company can offload report generation workloads from a mainframe to a mid-range environment and reduce the TCO A large fund management company generates heavy calculation based reports for arriving at the daily Net Asset Value (NAV) for all fund holdings of retail and corporate customers. The workloads for generating such reports can be offloaded from the mainframe environment to the mid-range Unix environment using re-hosting solution software and associated technology stack products. The investment cost for such a rehosting initiative can be recovered through savings in annual MIPS consumption and operating expenses. 6
Repurposing and Bridging Legacy with Distributed Systems Repurposing of Legacy Workloads Repurposing existing mainframe transaction systems as web applications allows business users easy access to remote data. Legacy transactions are web-enabled in multiple ways. Transaction gateway software, web services, wrappers, enterprise service bus (ESB) middleware, adapters, plug-ins, and messaging middleware are used. These establish constant communication between the web application and mainframe. Some challenges exist: The use of web-enabling transaction services consumes significant mainframe CPU capacity, which can affect performance, scalability, and continuity. This has prompted service providers to get equipped with solutions to improve the scalability, availability, and performance of both back-end and web services. Scenario Health insurance companies can increase productivity by web-enabling mainframe-based legacy transactions A health insurance company can repurpose its mainframe-based legacy transactions and expand its user base. If the back-end mainframe based insurance claims maintenance system is web-enabled, business users such as agents and call-center staff can access the claims data quickly to validate the eligibility of cashless claims. There will be no need for users to log on to the mainframes since the information can be accessed through the web-enabled front-end application. Transformation Drivers for Migrating Legacy Workloads Most legacy systems hosted on mainframes are custom-built. A couple of decades ago, they were developed using third-generation programming languages, and monolithic architecture and procedural styles. Business logic and data access components were bundled together and rolled out in functional release cycles. This approach created significant redundancy in technical and functional services including data and security access checks. Inflexibility was a problem. Point-to-point communication applications had to adapt to fixed data exchange interfaces. The technical skills required to transform legacy systems were not commonly available. Enterprises of all sizes are adapting by: 1. Re-engineering all, or portions, of their home-grown mainframe legacy systems into open source or other available distributed technology stacks and mid-range platforms 2. Migrating and absorbing business processes into packaged solutions available in the market These transformations are not done at one go: phased approaches are used to reduce business risk. 7
Bridging Legacy with Distributed Systems Integration adapters are used to meet business-to-business and business-to-customer needs. These adapters enable packaged solutions to access data hosted on the mainframe database. They enable SOA distributed applications to assimilate mainframe processing logic and databases in a seamless manner. Plug-ins and adapters enable the exchange of transaction messages between distributed systems and the mainframes. Custom adapters enable cross-communication and create compatibility, interoperability, and portability between systems. Integration solutions offer ways to trigger mainframe-based legacy services when required using messaging and ESB middleware. Service providers and system integrators often collaborate with software vendors to optimize new system design in enterprises' IT transformation initiatives. Integrated system design can help enterprises exploit the full potential of legacy systems during transformation. Enterprises can protect existing investments made on mainframes while reengineering legacy systems to adapt to distributed platforms. Scenario: Stock brokerages can use mainframe integration solutions to reduce processing time from hours to minutes and deliver better customer experience In a stock brokerage, brokers take orders on the phone and enter data directly into the back-end mainframe system using legacy transactions. The back-end system is updated hourly with order details, but the turnaround time of order confirmation to customers may be as long as one hour. The firm can build a new order management system, a customer self-service portal in the distributed SOA platform using messaging middleware that integrates with the back-end mainframe. Through this new system, direct stock order requests by customers will be transformed into instant messages. The middleware will appropriately route messages to the mainframe back-end services, update order entries immediately, and notify customers through email and SMS. This kind of self-service portal can reduce the turnaround time for customer orders from hours to minutes and help the brokerage deliver excellent customer experience. Mainframes in the Digital Paradigm Advanced mainframe technology ecosystems provide 'digital ready' platforms that can host mobile, Big Data, and cloud solutions. Mainframe on the Cloud The evolved mainframe is ready to host business on the cloud. The advent of mainframe specialty CPU engines means enterprises can deploy, host, and run multi-tier applications on the same mainframe box. This will have a detrimental effect on the systems' speed. Private mainframe cloud computing services allow enterprises to host large-scale multi-tier workloads. This deployment model reduces network latency among web, application, and database tiers since all of them get co-located in the same mainframe box. Workloads can be hosted in the mainframe platform on private clouds, as illustrated in Figure 2. 8
Digital Ready Mainframes (Cloud, Mobility, Analytics) Legacy Applications Transaction Processor Database Native Operating System Radio Frequency Network Mainframe Hardware Mainframe on Cloud Application Programming Interfaces Enterprise Service Bus Database Gateway Services Web Services Connectors Presentation Application Data Access Layer Layer Layer Social Media Network (LAN, WAN) Mobile App Server Big Data File System Linux Linux Application Database Messaging Linux Linux Linux Virtualization Layer Mainframe Hardware Figure 2: Integration and hosting of mobile and analytics applications in mainframes on a private cloud Private mainframe cloud service packages include mainframe hardware capacity, storage, virtual server hypervisors, cloud integration APIs, and a management administration suite to orchestrate provisioning and monitor system performance. Pricing is based on utility models such as 'pay as you use.' Private cloud service providers with mainframe computing platforms offer the capacity to meet the dynamic horizontal scalability demands of diverse customers. They build Linux servers, application servers, and database servers on mainframes when required. Enterprises can reduce operating costs by moving distributed Linux-based application workloads from their inhouse data center to Linux partitions of mainframes on a private cloud. 9
Systems of Engagement The Internet of Things, mobile, and social media applications directly engage various entities within business networks and generate huge volumes of data. This data is transmitted to Big Data systems on a continuous basis in near real time. Systems of engagement are next-gen digital technology solutions that enable businesses to improve performance. They prompt new business strategies and facilitate the introduction of products and services that can fuel growth. Mainframe technology has evolved to host digital platforms such as Big Data systems and mobile applications. Big Data Systems on Mainframes Big Data systems contain structured, semi-structured, and unstructured data. There is a tremendous volume and variety of data that arrives at high-speed velocity in these systems. Evolved mainframes can host Big Data systems on Linux partitions. 'Extract, Transform, Load' (ETL) products and processes move structured transactional data from legacy databases and file systems in the native environment to the Linux-based environment in mainframes. Real-time analytical workloads can also be hosted on the Linux partition of mainframes. Technology stack elements like Hive (SQL), Pig (a programming language), and Map Reduce can be used to develop analytical processing components that deal with Big Data. Consider telemetry-messaging protocols that transmit field data in real time (Data in Motion) on a continuous basis. Here, sensor devices transfer data through radio frequency networks. Field data is continuously transmitted and transformed by messaging middleware. Transformed messages are stored in Big Data file systems and these messages are further processed by analytical components to derive meaningful business insights and decisions. There is significant potential for providers to optimize both ETL and Big Data analytical processes. Scenario: Retailers can plan campaigns based on customer preference insights from Big Data within mainframe Linux platforms Multi-channel retailers can analyze both structured and unstructured data to understand customer preferences. The point-of-sale distributed system transmits structured data, such as purchase information, to the legacy mainframe database. At the same time, the ecommerce channel transmits unstructured data about customers, such as reviews and comments, catalog browsing history, and queries, to the Big Data system in near real-time using middleware infrastructure. Analysis of such structured and unstructured Big Data, through analytics applications in the mainframe Linux environment, will help the retailer get a 360- degree view of customer preferences and behavior for planning focused promotional campaigns. Enterprise Mobility on Mainframes Presently, Linux and associated technology products can be hosted on top of a special processor of mainframes for implementing enterprise mobility services. Enterprise mobile application services can be developed, deployed, and maintained using products such as mobile application development centers, mobile application servers, application programming interfaces (APIs), and continuous integration deployment tools. 10
Mobile applications are predominantly developed and deployed in mid-range based Linux and Windows platforms. Front-end mobile applications can be integrated with existing legacy databases hosted on mainframes using specialized connectors such as adapters, compatible data transport protocols, ESB, and messaging middleware. This integration allows secure access to key business and customer data on the go for mobile users. Customers, suppliers, partners, and field staff use mobile devices such as tablets and smartphones on a daily basis. There is potential for an immense increase in the user base if access to mainframe data is guaranteed for the growing number of mobile users through integration layers. Service providers can gain here by improving scalability and performance of integration solutions and back-end database systems hosted on mainframes. Scenario: Banking customers can access account details through mobile applications integrated with the mainframe legacy system Customers access bank account information on their mobile devices through a mobile app integrated with the back-end mainframe system. In this model, the mobile application accesses mainframe databases. A fund transfer operation triggers debit and credit functional modules of the legacy system, and is reflected in the deposit database maintained in the legacy environment. Through the messaging middleware infrastructure, customers will receive transaction notifications on the mobile app. Conclusion Mainframe hardware platforms and software ecosystems have evolved continuously. The backbone of business operations, they present optimization and integration opportunities with distributed IT systems. Legacy systems hosted on mainframes are tremendously valuable; they ensure sustainability of business operations and are also cost effective. SOA-based distributed systems can be cost-effectively integrated with existing legacy systems on a mainframe platform. The introduction of next-gen CPU processor technology in mainframes helps enterprises improve the overall operational efficiency. Mainframes offer a digital platform to host Big Data analytics and mobile applications, and allow workload hosting on the cloud. Mainframes can continue to support operations effectively even in the digital future. 11
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