AWS DevOps & Developer Productivity Blog

Accelerate large-scale modernization of .NET, mainframe, and VMware workloads using HAQM Q Developer

Software runs the world – not just the new software applications built in modern languages and deployed on the most optimized cloud infrastructure, but also legacy software built over years and barely understood by the teams that inherit them. These legacy applications may have snowballed into monolithic blocks or may be fragmented across siloed on-premises infrastructure. The significant maintenance, security, and compliance challenges caused can create lasting implications for business performance and competitiveness. Therefore, transformation of legacy applications using modern languages, new frameworks, and cloud services has become an organizational imperative.

Application modernization challenges

Modernization of software applications is a long and painful journey – requiring large teams of developers, domain experts, and consultants who first need to understand the application landscape, devise strategic modernization plans, and then tactically implement the plans in phases, typically over a span of many years. This process is linear, slow, and complex. Traditional labor-intensive modernization approaches incur significant costs and take years to leverage new cloud technologies and innovations for business-critical applications.

Generative AI can help with intelligent automation, domain expertise, and scalability to transform modernization journeys.

Introducing HAQM Q Developer transformation capabilities

Q Developer transformation capabilities powered by LLMs and domain-expert agents support human-agent interaction via an IDE experience for individual developers and a web experience for multifunctional teams.

HAQM Q Developer transformation capabilities

HAQM Q Developer, the most capable generative AI–powered assistant for software development, is now the first generative AI-powered assistant for large-scale modernization and migration of .NET, mainframe, and VMware workloads. This extends Q Developer’s transformation capabilities for Java upgrades launched in April 2024 to new types of workloads. Q Developer combines both foundational models and specialized tools based on AI and automated reasoning via autonomous agents that tackle workload-specific modernization steps spanning analysis, planning, and implementation.

Multifunctional teams, including consultants, IT experts, workload domain experts, and developers, can use a unified web experience to offload transformation tasks to HAQM Q Developer agents and transform hundreds of workloads at a time. The agents can port .NET Framework to cross-platform Linux-ready .NET, modernize COBOL applications on mainframes to Java applications on AWS, or virtualized workloads on VMware to scalable workloads on EC2. The modernization teams engage with Q Developer using natural language and share transformation objectives, code repositories, and context. Q Developer agents analyze artifacts like code segments, dependencies, and integrations, applying expertise from prior modernizations. They propose customized plans tailored to codebases, resource utilization, and objectives. The teams can then review, adjust, and approve the plans with iterative engagement with the agents. After the plans are approved, the agents implement the transformation keeping the modernization teams updated on milestones completed and blockers needing human guidance. The transformation journey is an interactive process between the modernization team and Q Developer, with modernization team maintaining control and visibility over the transformation.

Human team members interact with Q Developer generative AI agents using natural language chat.

Natural language chat with Q Developer AI agents

Faster, scalable, and better modernization

HAQM Q Developer enhances transformation in three primary ways – acceleration, scalability, and quality.

HAQM Q Developer automates and accelerates complex, multi-step processes. Agents conduct assessment and discovery of legacy artifacts to build documentation and dependency maps that improve the understanding of source assets. Most large-scale modernization projects are done in waves that need to be carefully planned. The agents develop modernization wave plans based on source dependencies, stated project goals, and teams can review and approve the plans. Thereafter, the goal-seeking autonomous agents handle implementation complexities to execute the plans. Customers using HAQM Q Developer can modernize Windows .NET applications to Linux up to four times faster than traditional methods and help customers realize up to 40% savings in licensing costs. Migration Planning for the sequence to transform monolith z/OS COBOL application code that takes months to accomplish with human subject matter experts, HAQM Q Developer generates in minutes. Q Developer agents convert on-premises VMware network configurations into modern AWS equivalents in hours vs. the weeks required with traditional manual approaches. The shorter time spent on manual modernization means more freedom for your team to focus on innovation.

Modernization has traditionally been a linear journey with multiple steps and dependencies on cross-functional teams with limited mechanisms for collaboration. This limits teams’ ability to tackle large-scale projects. HAQM Q Developer addresses the challenges by task parallelization and web-based collaboration. Multiple generative AI agents work simultaneously on tasks. Large monolithic applications can be decomposed along business functions like engineering, marketing, sales applications, and transformed in parallel. A unified web-based experience for large-scale transformation means multi-functional team members can collaborate with the autonomous agents, and review and approve key decisions in one place, enabling teams to execute larger and more complex projects in a given time.

Finally, the quality of transformation manifested in functional equivalence, security, and resilience of modernized applications determines the business outcomes like project ROI and operational performance. To ensure transformation quality, you need expertise in languages and frameworks like COBOL, Java, .NET; specialized steps like code base analysis, monolith decomposition, code refactoring, network translation; and domains like mainframe, virtualization, and cloud. You may not have the requisite expertise in your team. That is where HAQM Q Developer can help. Q Developer agents are trained with specific domain expertise to identify code dependencies and frameworks, replace deprecated code, upgrade to new language frameworks, incorporate security best practices, and validate upgraded workloads using workload-tailored plans. Your team can examine the agents’ recommendations, make informed decisions, and guide the modernization journey towards better outcomes like enhanced security, compliance, and performance.

Q Developer supports modernization of .NET Framework applications to cross-platform .NET applications, mainframe-based COBOL applications to Java applications on AWS, on-premises VMware workloads to workloads on EC2, and Java v8/11/17 to Java17/21.

Workloads supported by HAQM Q Developer transformation capabilities

Next steps

HAQM Q Developer transformation capabilities are now available in preview. To learn more, please visit Q Developer web page featuring short demo videos and documentation that can get you started. Read the AWS News blogs that walk you through the unified web experience and IDE experience. Dive deeper into the transformation of specific workloads by reading the workload-specific blogs related to transformation of .NET, mainframe, and VMware workloads.

About the author:

Elio Damaggio

Krishna Parab

Krishna B. Parab leads product marketing for HAQM Q Developer transformation capabilities. He has over 13 years of experience in product marketing and prior experience in engineering and product management. He has led marketing for Cisco Cloud, ServiceNow service management SaaS, Arm Pelion IoT platform, Automation Anywhere RPA platform, and AWS Mainframe Modernization service. Krishna’s educational background includes BTech, MS, and MBA degrees from IIT Bombay, UT Austin, and University of Michigan, respectively.

Elio Damaggio

Elio Damaggio

Elio Damaggio is the product lead for the transformation capabilities of HAQM Q Developer. With more than 15 years in tech, 11 patents, and a PhD in Computer Science, he is now looking for exciting ways to empower developers through AI.