re:Invent 2024

Amazon Q Developer: Transform Use Cases

Generative AI & LLMOps

See all the ways that Amazon Q’s Developer: Transform can help you migrate and modernize your data system.

Amazon's Q Developer toolkit includes an AI-powered transformation tool that helps organizations migrate and modernize their systems. This technology reduces the technical barriers to updating application & data infrastructure, making it practical for companies to build scalable, stable, and secure systems. When planning your modernization and migration initiatives, understanding what Q Developer: Transform can accomplish will help you make informed decisions about your technology roadmap.

In this comprehensive guide, we'll explore Amazon Q Developer's capabilities, examine specific use cases for Developer: Transform, and show how Caylent Applied Intelligence can enhance your migration and modernization work.

What is Amazon Q Developer: Transform?

Amazon Q Developer: Transform marks a significant advance in code modernization and system migration. This AI-powered tool analyzes your codebase systematically, identifying opportunities for adaptation and upgrading while following current developer standards established by language engineers.

The tool's approach to transformation centers on developer control: rather than implementing changes automatically, it presents update recommendations for your approval or rejection. This combination of AI analysis with developer oversight creates an efficient and reliable modernization process.

Q developer transform

Q Developer: Transform helps organizations modernize systems quickly and migrate between different infrastructures - whether you're moving to the cloud, switching operating systems, or updating legacy codebases. By simplifying cloud adoption and preparing systems for AI enablement, the tool helps organizations extract more value through targeted system upgrades.

Use Cases for Amazon Q Developer: Transform

Amazon Q Developer: Transform currently supports four primary transformation scenarios, with the potential for expanded capabilities as the tool evolves. Let's examine each use case in detail to understand how this powerful tool can address specific modernization challenges.

Key Transformation Capabilities:

  1. Migration from Windows-exclusive .NET frameworks to cross-platform environments
  2. Modernization of legacy mainframe applications to cloud architectures
  3. VMware workload transition to AWS infrastructure
  4. Java application version upgrades and optimization

Porting .NET from Windows to Linux

The process of modernizing .NET frameworks is necessary because traditional .NET Framework applications were designed exclusively for Windows environments, using Windows-specific libraries and APIs. These applications often rely on Windows-only features like the Registry, Windows Services, or COM interop, making direct migration to Linux impossible. A move to Linux requires upgrading to .NET Core or .NET 5+ (which unified .NET Core and .NET Framework), as these versions were rebuilt to be cross-platform compatible.

The modernization begins with using Q Dev tools' "transform" function on the target code files. The AI system analyzes the code and suggests specific areas that require modernization, identifying Windows-dependent code patterns and suggesting cross-platform alternatives. This includes replacing Windows-specific file path handling, updating authentication mechanisms to work with Linux security models, and modifying system service integrations to use platform-agnostic approaches.

Moving to an open-source operating system significantly reduces licensing costs while enhancing security through modernization of the underlying .NET framework. Organizations gain access to current development practices by moving away from outdated .NET architectures, positioning them for future growth and innovation.

Modernizing Mainframe Applications

The challenge of moving applications from mainframe data center architectures to modern cloud-based infrastructures has long been a significant obstacle for organizations seeking to leverage the benefits of AWS. Organizations typically struggle with complex batch processing dependencies, COBOL to Java conversions, and the risk of data loss during migration. Many also face the challenge of preserving decades of business logic embedded in legacy code while dealing with incomplete or outdated system documentation.

Amazon Q Developer: Transform addresses these challenges through comprehensive code analysis and systematic decomposition of large applications. Using advanced AI analysis, Q Developer: Transform examines mainframe code and breaks down large applications while generating detailed documentation for the transition process. This enables organizations to migrate mainframe data systems to scalable cloud environments while transforming monolithic programs into modern, efficient architectures that maintain system functionality while improving overall performance.

Migrating VMware Workloads

For virtual machine architecture transitions to AWS cloud, Q Developer: Transform employs generative AI to analyze existing workload architecture, track dependencies, and create transition plans that minimize system downtime. This systematic approach accelerates the migration process while ensuring the stability of virtual environments in their new cloud infrastructure.

Technical Benefits:

  • Reduced discovery and planning time through automated analysis
  • Seamless workload transition with minimal operational disruption
  • Enhanced scalability and security in the cloud environment

Upgrading Java Applications

Keeping Java applications current with the latest language versions is crucial for maintaining optimal performance and security. Q Developer: Transform automates code updates, unit testing, and deployment readiness verification while maintaining human oversight for final approval. This automation reduces time spent on repetitive tasks, allowing developers to focus on strategic projects while ensuring applications remain current and secure.

Amazon Q Developer and Caylent Applied Intelligence

Caylent's Applied Intelligence platform works alongside Amazon Q Developer's capabilities to provide comprehensive modernization tools. As an Amazon partner, Caylent harnesses Q Developer's functions with our Applied Intelligence Methodology. The Applied Intelligence Framework also includes proprietary systems built on Amazon Bedrock and Amazon SageMaker. These include:

  • SQL Polyglot: A revolutionary solution for modernizing SQL architectures, enabling rapid and reliable database migrations while preserving complex functionality
  • IaC Polyglot: An advanced automation tool for Infrastructure as Code implementations, streamlining the process of infrastructure modernization and deployment

Using Amazon Q Developer: Transform and Caylent Applied Intelligence together allows organizations to create detailed modernization plans in days instead of months. Recent implementations show how these tools work together to reduce migration timeframes and improve success rates for complex transformations. As cloud technologies evolve, this integrated approach to modernization helps organizations keep their technical systems current and competitive.

Ready to speed up your modernization work? Contact us today to learn how Caylent AI can help you achieve your transformation goals more quickly.

Generative AI & LLMOps
Ryan Gross

Ryan Gross

Ryan Gross leads Cloud Data/AI/ML delivery at Caylent. Through his 15+ years of experience, Ryan has guided over 50 clients in building tech-driven data and AI cultures across various industries. By identifying technology trends, and leading the development of asset backed consulting offerings to realize value, he builds a growth culture within his team. Ryan is also a frequent conference speaker on emerging data and AI trends.

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