IBM’s Application Discovery and Delivery Intelligence (ADDI) is an analytical platform for application modernization. It uses cognitive technologies to analyze mainframe applications so you can quickly discover and understand interdependencies and impacts of change. You can use this intelligence to transform and renew these applications faster than ever. Capitalize on time-tested mainframe code to engage the API economy. Accelerate application transformation of your IBM Z hybrid cloud environment and more.
Formerly, ADDI was known as EZSource. Back then EZSource was designed to expedite digital transformations by unlocking core business logic and apps. Specifically it enabled the IT team to pinpoint specific mainframe code in preparation for leveraging IT through a hybrid cloud strategy. In effect it enabled the understanding business-critical assets in preparation of deployment of a z-centered hybrid cloud. This also enabled enterprise DevOps, which was necessary to keep up with the pace of changes overtaking existing business processes.
This wasn’t easy when EZSource initially arrived and it still isn’t although the intelligence built into ADDI makes it easier now. Originally it was intended to help the mainframe data center team to:
- Identify API candidates to play in the API economy
- Embrace micro services to deliver versatile apps fast
- Identify code quality concerns, including dead code, to improve reliability and maintainability
- Mitigate risk of change through understanding code, data, and schedule interdependencies
- Aid in sizing the change effort
- Automate documentation to improve understanding
- Reduce learning curve as new people came onboarded
- Add application understanding to DevOps lifecycle information to identify opportunities for work optimization
Today, IBM describes Application Discovery and Delivery Intelligence (ADDI), its follow-up to EZSource, as an analytical platform for application modernization. It uses cognitive technologies to analyze mainframe applications so your team can quickly discover and understand interdependencies and impacts of any change. In theory you should be able to use this intelligence to transform and renew these applications more efficiently and productively. In short, it should allow you to leverage time-tested mainframe code to engage with the API economy and accelerate the application transformation on your IBM Z and hybrid cloud environment.
More specifically, it promises to enable your team to analyze a broad range of IBM and non-IBM programing languages, databases, workload schedulers, and environments. Enterprise application portfolios were built over decades using an ever-evolving set of technologies, so you need a tool with broad support, such as ADDI, to truly understand the relationships between application components and accurately determine the impacts of potential changes.
In practice, it integrates with mainframe environments and tools via a z/OS agent to automatically synchronize application changes. Without keeping your application analysis synchronized with the latest changes that your developers made, according to IBM, your analysis can get out of date and you risk missing critical changes.
In addition, it provides visual analysis integrated with leading IDEs. Data center managers are petrified of changing applications that still work, fearing they will inadvertently break it or slow performance. When modifying complex applications, you need to be able to quickly navigate the dependencies between application components and drill down to see relevant details. After you understand the code, you can then effectively modify it at much lower risk. The integration between ADDI and IBM Developer for z (IDz) combines the leading mainframe IDE with the application understanding and analytics capabilities you need to safely and efficiently modify the code.
It also, IBM continues, cognitively optimizes your test suites. When you have a large code base to maintain and manyf tests to run, you must run the tests most optimally. ADDI correlates code coverage data and code changes with test execution records to enable you to identify which regression tests are the most critical, allowing you to optimize time and resources while reducing risk. It exposes poorly tested or complex code and empowers the test teams with cognitive insights that turns awareness of trends into mitigation of future risks.
Finally, ADDI intelligently identifies performance degradations before they hit production. It correlates runtime performance data with application discovery data and test data to quickly pinpoint performance degradation and narrow down the code artifacts to those that are relevant to the cause of bad performance. This enables early detection of performance issues and speeds resolution.
What’s the biggest benefit of ADDI on the Z? It enables your data center to play a central role in digital transformation, a phrase spoken by every c-level executive today as a holy mantra. But more importantly, it will keep your mainframe relevant.
DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.
Tags: ADDI, analytics, API economy, Application Delivery and Discovery Intelligence, Big Data, Cloud, code interdependencies, DevOps, EZSource, hybrid EZSource, IBM, IBM Application Discovery and Delivery Intelligence (ADDI), IBM Developer for Z (IDz), IDE, Java, Linux, mainframe, micro services, mobile, risk mitigation, technology, z-centered hybrid cloud, z/OS agent
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