An Innovative Digital Solution

The answer lies in mainframe digital DevOps. This helps enterprises remain competitive in an app-centric economy. Through a unified cross platform, DevOps is integrating mainframe tools with open source DevOps tools.

This approach allows organizations to retain their legacy code and does not require legacy code migration—especially when the back-end core applications are on mainframe. As veteran COBOL programmers retire out of the skill orbit, this becomes even more important. There is an imperative and an expectation for agility and higher productivity from IT—without jeopardizing performance, customer experience, security and other compliance factors.

Transforming the Developer Environment

Most mainframe development, test and ops work is executed in antique “green screen” SPF environments, which calls for specialist knowledge that limit productivity among programmers of Agile and DevOps transformation. Turnaround times of monolithic mainframe applications are painfully slow compared with the new-age agile technology of mobile and web applications. This can be frustrating for developers who wish to make frequent changes to mainframe code to fulfill the urgent needs of business.

Therefore, it’s important to make the shift to modern tools and integrate mainframe with non-mainframe DevOps processes to deliver cross-platform services. This will improve staff productivity across development, testing and production operations and enable inexperienced mainframe professionals to perform application development and enhancements with ease and efficiency.

Large mainframe clients embark on transformation by modernizing the workspace to work on both mainframe and non-mainframe applications. Open system developers are familiar with new-age IDEs such as Eclipse, which have user-friendly interfaces. Similarly, other mainframe tools are available that provide source code editing, debugging, fault diagnosis and browse data to enable developers to write, compile and run code from a modern Eclipse-based IDE. Developers can drag and drop files between LPARs and perform other tasks to improve productivity metrics. Collaboration between the two teams will motivate mainframe developers to use DevOps principles to integrate mainframe with distributed and cloud applications.

Once quick wins are established, adoption levels of Agile and DevOps will improve among mainframe developers and business.

Eliminating Barriers to Unit Testing

Historically, mainframe developers have not been accustomed to unit testing. Automated unit testing is common in Java but not in the mainframe environment. Agile coaches, familiar with mainframe tools, will need to enable collaboration in interactively testing smaller pieces of code.

Unit testing can improve throughput by increasing the frequent code drops in production environment and help to accomplish DevOps key performance indicators (KPIs) with fewer errors in the later stages of the software development lifecycle process. Some tools can facilitate this process by automatically breaking the mainframe code into discrete logical units, and creating tests for such logical units.

Tracking and Monitoring Progress for High Quality

Visualization is an important element of DevOps for improved visibility to track and monitor progress across the enterprise. As most mainframe applications and data structures are large, complex and not well-documented, enterprise IT is highly dependent on the personal and institutional knowledge of senior mainframe staff. Graphical visualization can help quickly “read” existing application logic, program interdependencies, data structures and data relationships. Business rule extraction tools are available in the market to reveal logic and data relationships through graphically intuitive diagrams. This helps developers work independently on unfamiliar programs to better estimate project work, meet delivery deadlines and commit timelines to business.

Most mainframe applications are often associated with core business processes with zero tolerance for error. Any attempt with inadequate mainframe experience can lead to catastrophic non-recoverable error. Continuous integration (CI) is critical in determining application quality issues early and establishing KPIs to deliver continuous quality code in production. Enterprises have started embracing modern tools and techniques to transform from the Waterfall delivery model to Agile. Modern DevOps tools embrace CI, and certain tools can quickly detect application quality issues (such as unbalanced or unmatched working storage and data items, and out-of-range nested conditions and branches).

Training for Effective Enablement

Successful implementation of cross-platform DevOps calls for the right training on Agile tools, processes and methodologies. A single Scrum team can be formed to collaborate with developers across mobile, web and mainframe. The Agile mainframe team will need to focus on stories and epics that capture specific units of business value instead of technical tasks in a project plan. Open system tools such as JIRA and Confluence that can support Scrum and Kanban can be used to manage tasks and improve collaboration through centralized and well-organized web tools. This will incorporate Agile values such as transparency, knowledge-sharing and ideation to improve the developer’s performance.

The move to Agile scrumming represents a transformative shift of mainframe work culture, and herein lies the importance of the right coaching in Agile processes. A “2- n a box” partnering model of mainframe developers and experienced Agile developers from other platforms can create the required collaboration.

Operational Data Analysis to Close the ‘Last Mile’ Loop

Good quality code alone is not enough. Operational data analysis is required to reduce costs by discovering and mitigating avoidable CPU consumption caused by code inefficiency.

Mere monitoring and reporting by triage teams is not enough to support and maintain applications in the world of DevOps. Production data analyses by enabling an auto-feedback loop is imperative to improve productivity of the dev, test and production teams. Tools are available that can quickly pinpoint bad statements and pinpoint application inefficiencies such as bad SQL statements. Tools also help identify the causes of excessive CPU consumption and slow data retrieval.

Automation for Speedy Efficiency

Agile-enabled core source code management (SCM) is a fundamental requirement of DevOps. Traditional SCM cannot support parallel development work on different user stories. SCM migration is therefore essential to increase the speed and frequency of mainframe code drops. Automating the change management process and defining the proper workflows can eliminate manual steps and reduce code approval delays.

Again, tools are available that can fulfill business expectations by seamless SCM migration without disrupting the current work in progress.

Automated release and deployment is pivotal to keeping pace with today’s fast-moving markets. Business needs to quickly see reliable new code in production.

Toward a Unified IT Service Management

Cross-platform continuous delivery is vital for efficient use of mainframe applications and their data for multiplatform customer-facing applications, including mobile, web and cloud components. Mainframe DevOps process should fully synchronize the code delivery process across all platforms. This will establish a centralized deployment control center to provide a unified cross-platform and accurately report progress. Tools can be the single point of control for all changes across z/OS, Windows, Unix and other platforms. REST APIs are flexible to mix and match best-in-class tools and avoid vendor lock-in.

The ultimate destination is to create a de-siloed environment where mainframe is just another platform with high scalability, reliability, performance, security and cost-efficiency. A unified mainframe digital DevOps platform may be the answer to modifying traditional process that fulfills this business demand.