As enterprises embrace AI to modernize applications, GitHub Copilot and other AI-powered tools are transforming how developers write, refactor, and migrate code. AI is playing a crucial role in application modernization by automating code generation, optimizing cloud migrations, and improving developer productivity.
However, one of the biggest challenges in modernization remains data access, especially for organizations with mission-critical workloads on IBM Z mainframes. While AI-powered tools streamline code transformation, they still struggle to access and integrate real-time mainframe data, which is essential for a smooth transition.
This is where VirtualZ Computing helps. VirtualZ does not develop AI solutions or modernize applications directly, but our software removes the data access roadblock, enabling seamless integration between modern applications and mainframe data without replication, ETL, or change data capture (CDC).
The Role of AI in Application Modernization
AI is transforming modernization efforts in several ways:
- AI-driven code refactoring converts COBOL, PL/I, and RPG into modern languages like Java, Python, and C#.
- Automated testing and validation use AI to generate test cases and identify dependencies.
- AI-powered migration tools analyze workloads to optimize cloud deployment strategies.
- Code documentation tools scan and generate readable documentation for legacy applications.
- Developer productivity tools suggest optimized code structures in real time.
Despite these advancements, AI-powered tools still require seamless access to the underlying data to be effective. Without real-time mainframe data access, modernization efforts stall due to slow, manual, and costly data extraction methods.
The Data Challenge: AI Alone Isn’t Enough
While AI can rewrite and migrate applications, it does not address the core challenge of accessing mainframe data. Most modernization projects fail or experience major delays due to reliance on outdated data integration methods:
- Change Data Capture (CDC) requires constant maintenance and is expensive.
- Extract, Transform, Load (ETL) processes are slow, batch-based, and resource-intensive.
- Manual data conversion is error-prone and difficult to scale.
These traditional methods slow down modernization by consuming mainframe resources, increasing costs, and requiring specialized skills that are increasingly scarce.
How VirtualZ Removes the Data Access Bottleneck
VirtualZ enables AI-driven modernization by providing real-time mainframe data access without replication, ETL, or CDC. With Lozen™, PropelZ™, and Zaac™, enterprises can seamlessly integrate mainframe data into AI-powered modernization projects.
Lozen: Real-Time, Read/Write Data Access
- Allows modern applications to access live mainframe data as if they were still on the mainframe.
- Eliminates the need for ETL, CDC, or data replication.
- Supports cloud-native AI applications with direct read/write access from the cloud to the mainframe.
PropelZ: No-Code Mainframe Data Integration
- Pushes mainframe data to cloud platforms like Azure, AWS, and Google Cloud for AI-powered analytics.
- Eliminates the need for custom scripts or complex ETL jobs.
- Provides flat-rate pricing with unlimited data movement, reducing costs and complexity.
Zaac: Cost-Effective Cloud Storage for Mainframe Data
- Enables organizations to store and access historical mainframe data in cloud storage solutions like Amazon S3 and Azure Blob Storage.
- Reduces costs by eliminating expensive DASD or tape storage.
- Provides secure, encrypted access to meet compliance and regulatory requirements.
The Power of VirtualZ + GitHub Copilot: AI-Powered Modernization Without Data Bottlenecks
By leveraging VirtualZ Computing’s real-time data access solutions, enterprises can unlock the full potential of AI-driven application modernization. When paired with GitHub Copilot, organizations can:
- Migrate applications without disrupting business operations: AI refactors applications while Lozen provides continuous data access.
- Accelerate cloud adoption: PropelZ moves data to Azure, AWS, and Google Cloud seamlessly.
- Eliminate costly ETL and CDC processes: No need for expensive infrastructure or maintenance-heavy integration tools.
- Ensure security and compliance: Data remains on IBM Z while being accessible for AI and analytics.
- Increase developer productivity: GitHub Copilot assists in modernization while VirtualZ ensures applications have instant access to mainframe data.
Conclusion: AI-Driven Modernization Needs Real-Time Data Access
AI and GitHub Copilot are transforming how enterprises modernize applications, but without seamless data integration, AI alone cannot solve the challenges of mainframe transformation. VirtualZ removes the data access barrier by providing real-time mainframe data access, eliminating the need for slow, expensive, and complex data extraction methods. For IT leaders seeking to accelerate application modernization while reducing costs and complexity, the solution is clear: combine GitHub Copilot’s AI-driven code modernization with VirtualZ Computing’s real-time mainframe data access for a seamless digital transformation.