May 5, 2020 By Ruchir Puri
Shawn DSouza
3 min read

CIOs and other technology innovators are boldly leading their companies through change during this unprecedented time. As IT leaders make their journey to the cloud and prepare their business for the future, greater application modernization and agility is needed to meet these new marketplace realities – now more than ever. 

With deep roots in AI and hybrid multicoud technologies, IBM is completely reimagining how clients can approach application modernization with the roll out of new AI capabilities such as the Accelerator for Application Modernization with AI. This accelerator is designed to help clients reduce modernization efforts and costs dramatically by using advanced AI capabilities developed by IBM Research. It includes a series of tools for optimization, including analysis and containerization, microservices recommendations and continuous, guided feedback and AI learning. 

The power of AI for application modernization

As IT leaders embark on their journey to hybrid multicloud, they realize that advanced technologies like automation and AI are key to help reduce IT costs and shore up business continuity. Thus far, most businesses have moved only their simpler workloads with lower complexity to cloud – and are struggling with the daunting task of modernizing most of their mission-critical applications because of incompatibility with cloud-native architectural principles. These applications span generations of software technologies, even decades — and contain millions of lines of code with their intellectual property (IP) and expertise locked in them.

That’s where the new accelerator comes in; it automates resource-intensive modernization tasks and provides explainable AI capability with reasoning to guide decisions and assist enterprises with speeding modernization. Teams can unlock core applications and fuel cloud-native development. Let’s take a closer look at the accelerator tools with advising and building capabilities:

Advise

Modernization Workflow Orchestrator (MWO): Helps determine the best transformation paths for an application in an automated manner, and recommends and orchestrates the tool-assisted journeys required for migration or modernization. MWO continuously learns from engagement feedback and the evolving technology landscape, and reacts to changing priorities in application modernization programs. It’s like GPS for app modernization. It plots the best path for optimization based on the technology with AI-planning technology.

Application Containerization Advisor: Simplifies the analysis portion of modernization and assists enterprises with making stronger containerization recommendations; think of this as the evaluation phase that recommends if an application is, or can transform into a cloud-ready application. At the core, it’s about taking incompatible apps and transforming them into something that’s cloud-ready.

This is a machine-learning, model-based research asset, powered by IBM Watson to determine feasibility of containerization for the application portfolio being analyzed. The tool helps reduce time required to conduct advisory stages by up to 50 percent.

Build

Candidate Microservices Advisor: Rapidly identifies potential microservices from legacy applications that run on traditional distributed systems or mainframes. The tool uses continuous learning and feedback to provide increasingly precise recommendations for application candidates.

Essentially, it greatly simplifies and reduces end-to-end microservices development effort by optimizing and automating the labor-intensive and time-consuming process of understanding and interpreting legacy code – especially important as many of the developers who wrote the code initially are no longer available. This tool is powered by breakthrough AI technology that understands the code, its context of business rules and data dependencies, and recommends the optimal set of microservices to modernize legacy applications.

Take a recent use case with an auto manufacturer. Using the microservices advisor technology, we analyzed over a million lines of code built with several generations of Java technology; the tool automatically recommended a set of 26 microservices, shortening the execution time of the project from more than a year to less than a month—an order of magnitude improvement.

Flexible app modernization

Red Hat OpenShift provides IT leaders the flexibility to modernize applications and help enable their workloads to run flexibly in any open hybrid multicloud environment.

Lastly, in addition to helping IT leaders compress efforts and costs, application modernization is ultimately about getting the journey to cloud right the first time, and in the most de-risked and optimized manner, while ensuring that the target state is scalable and flexible enough to support evolving business needs.

Learn how your business can tackle challenges with deploy-anywhere application modernization.

 

Was this article helpful?
YesNo

More from Cloud

Bigger isn’t always better: How hybrid AI pattern enables smaller language models

5 min read - As large language models (LLMs) have entered the common vernacular, people have discovered how to use apps that access them. Modern AI tools can generate, create, summarize, translate, classify and even converse. Tools in the generative AI domain allow us to generate responses to prompts after learning from existing artifacts. One area that has not seen much innovation is at the far edge and on constrained devices. We see some versions of AI apps running locally on mobile devices with…

IBM Tech Now: April 8, 2024

< 1 min read - ​Welcome IBM Tech Now, our video web series featuring the latest and greatest news and announcements in the world of technology. Make sure you subscribe to our YouTube channel to be notified every time a new IBM Tech Now video is published. IBM Tech Now: Episode 96 On this episode, we're covering the following topics: IBM Cloud Logs A collaboration with IBM watsonx.ai and Anaconda IBM offerings in the G2 Spring Reports Stay plugged in You can check out the…

The advantages and disadvantages of private cloud 

6 min read - The popularity of private cloud is growing, primarily driven by the need for greater data security. Across industries like education, retail and government, organizations are choosing private cloud settings to conduct business use cases involving workloads with sensitive information and to comply with data privacy and compliance needs. In a report from Technavio (link resides outside ibm.com), the private cloud services market size is estimated to grow at a CAGR of 26.71% between 2023 and 2028, and it is forecast to increase by…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters