Smoothing the Never-Ending Road to Modernization

In the realm of Information Technology, the finish line seems to continually recede, regardless of the speed at which organizations strive to reach it. Cloud migration has revolutionized how businesses think about infrastructure, providing enhanced scalability and agility, but it has also introduced years of extensive migration work that persists today.

Subsequently, application modernization has shifted the discourse from where workloads operate to how efficiently applications can harness modern architectures and services, leaving IT teams to modernize both their applications and environments concurrently. The emergence of Artificial Intelligence has introduced yet another wave of modernization, with organizations seeking methods to link agents to existing applications and data.

The perception that there's always another modernization initiative just around the corner is, in fact, a common reality. IT, however, lacks a definitive end point. The future never waits for organizations to conclude their past modernization endeavors. With evolving technologies and shifting business needs, it is incumbent upon IT departments to ensure their environments and applications remain up-to-date.

While the concept of continuous modernization may conjure images of numerous large-scale projects such as extensive cloud migrations or enterprise-wide application refreshes, the truth is that modernization predominantly comprises smaller, recurring tasks like updating libraries, addressing vulnerabilities, and aligning applications with internal development standards.

Treating these tasks as individual, manual projects can consume considerable engineering time and leave IT teams feeling perpetually unable to make progress. However, by automating many of these tasks, organizations can release capacity for genuine innovation and, more importantly, make legacy applications and data ready for agents without the need for a complete rewrite, without waiting for every workload to migrate.

This is the essence of AWS Transform – continuous modernization, a novel feature of AWS Transform designed for continuous, autonomous technical debt analysis and remediation. While AWS Transform already assists enterprises in migrating to the cloud, modernizing applications, and streamlining software maintenance, this new agentic feature provides broad visibility into the state of a codebase across thousands of repositories.

It offers detailed dependency mapping to aid in prioritizing findings, with code changes delivered as pull requests for developer review. Out of the box, the service includes policies for identifying outdated dependencies, deprecated frameworks, and other prevalent sources of technical debt. IT teams can further enhance these functionalities with remediation patterns tailored to their organization, encompassing approved libraries, internal coding standards, or tech debt policies that their platform teams already uphold.

The objective is to enable organizations to continuously diminish technical debt and render their frameworks and codebases AI-ready, without requiring developers to dedicate their time to managing legacy code in the pursuit of modernization. In the immediate aftermath of this new offering's announcement, organizations have already begun to experience the effects of continuous modernization.

Tasks that once consumed substantial manual effort now occur more swiftly at a scale that would have been unattainable previously. Quantiphi, an AI-focused digital engineering and services firm based in Massachusetts, implemented continuous modernization across a substantial portfolio, compressing a multi-week assessment into just days.

The company evaluated over 500 repositories, uncovering more than 3,000 technical debt findings in under a week. By automating technical debt discovery and uncovering actionable remediation insights, the company reported that they could reduce assessment efforts by over 60%. Tech Mahindra, a multinational consulting and engineering company based in India, witnessed even more substantial time savings, cutting assessment time across 25 enterprise repositories by 80%, from 40 hours down to just eight hours.

Sanjeev Agarwal, the company's global head of AWS business, remarked that company leaders consider this the "beginning of a transformative shift" in how organizations approach IT modernization. "AWS Transform's scanning and analysis engine is robust, and the structured output empowers our teams to rapidly validate findings and develop prioritized remediation plans with confidence," he stated.

Additionally, U.S. healthtech company Netsmart utilized AWS Transform – continuous modernization to accelerate projects estimated to take between three months and a year, with some even being completed within two weeks. "Dependency mapping has traditionally been a laborious, complex, and ongoing endeavor," said Pepper Pancoast, Senior Director of Engineering at Netsmart.

"This new capability automates dependency mapping on a regular basis, providing us with enhanced visibility into the health of our codebase at scale."