What Is Mainframe Modernization?
Mainframe modernization refers to updating and transforming traditional mainframe systems to modern IT environments. These legacy systems, while reliable, often come with limitations in scalability, flexibility, and high operational costs. Modernization enables organizations to move away from rigid, monolithic structures to more agile, scalable, and cost-effective architectures.
Organizations can modernize mainframes through various methods such as rehosting (lift-and-shift), refactoring, or rebuilding applications entirely to align with new business objectives. By modernizing, organizations can integrate mainframe workloads with cloud services, improve operational efficiency, and improve data utilization for emerging technologies like AI and machine learning.
Why Modernize Mainframe Workloads with Azure?
Azure provides a scalable, secure, and enterprise-ready platform for mainframe modernization. Organizations that transition their legacy systems to Azure can reduce operating costs, eliminate infrastructure overhead, and improve performance by leveraging cloud-native capabilities. Azure’s pay-as-you-go pricing model replaces the high fixed costs associated with maintaining on-premises mainframes, offering a more predictable and flexible cost structure.
Azure supports multiple modernization strategies—from rehosting and replatforming to full refactoring—allowing organizations to choose the path that aligns with their goals, risk tolerance, and technical complexity. Its global footprint ensures low-latency access and compliance with regional data residency requirements, making it suitable for industries with strict regulatory demands.
Another advantage is Azure’s integration with hybrid cloud and DevOps tools, enabling coexistence between modernized and legacy workloads. Services like Azure Arc and Azure DevOps allow teams to manage, monitor, and deploy applications across environments, supporting incremental modernization and reducing migration risks.
Azure Services and Tools for Mainframe Modernization
Microsoft Azure offers a set of tools to simplify the transition from mainframe environments to modern cloud-native architectures. These services support everything from application migration to data protection and operational optimization.
- Azure Kubernetes Service (AKS) enables the deployment of mainframe applications within containerized environments. This orchestration platform helps reduce infrastructure costs and supports scalability and resilience for complex workloads.
- Azure SQL provides cloud-based database services that replicate mainframe and midrange capabilities. These services are optimized for high availability, performance, and integration with other Azure tools, enabling migration of critical data systems.
- Azure DevOps enables rapid development, testing, and deployment of applications. It brings modern software engineering practices to legacy workloads, allowing teams to adopt agile methodologies and CI/CD pipelines.
- Azure Site Recovery supports business continuity by replicating systems for disaster recovery. This minimizes downtime during transitions and ensures application availability.
- Azure Confidential Computing secures data while in use, not just at rest or in transit. This is critical for maintaining privacy and compliance when modernizing sensitive mainframe workloads.
- Azure Service Fabric allows organizations to re-platform legacy applications into scalable microservices. It supports the evolution of existing software into cloud-native solutions without needing a full rebuild.
Learn more in our detailed guide to mainframe modernization tools
Mainframe Workloads Supported on Azure
Azure supports a range of mainframe workloads through specialized tools, emulators, and modernization frameworks designed to handle legacy languages and transaction environments. These solutions accommodate both batch and online processing systems, enabling enterprises to run traditional workloads on a modern, cloud-native platform.
Development tools and compilers
Azure integrates with several third-party tools to support mainframe languages like COBOL, PL/I, and Assembler. This includes development environments such as Asysco AMT COBOL, Micro Focus Visual COBOL, and Fujitsu NetCOBOL, which allow COBOL applications to be maintained and extended within Azure. Tools like Raincode and NTT Data provide PL/I and Assembler support on the .NET platform, making it easier to move codebases without a complete rewrite.
Emulation environments
To replicate mainframe execution contexts, Azure supports deployment of emulated transaction processing and batch environments. Asysco AMT GO, Micro Focus Enterprise Server, and NTT DATA’s native transaction systems can emulate CICS, IMS, JCL, and other proprietary mainframe components. These environments allow legacy applications to operate within Azure while maintaining performance and functionality.
Code conversion and migration services
Azure enables automated code transformation through technologies like Asysco AMT Transform and Heirloom Computing. These tools help convert COBOL and PL/I code into modern languages such as Java while preserving the business logic. Additional services from Asysco and Microsoft partners offer full migration lifecycle support, including system inventory, training, and post-migration assistance.
Enterprise-grade modernization
For large-scale projects, Azure collaborates with global system integrators (GSIs) that specialize in designing and executing modernization strategies. These services provide architectural guidance, tooling integration, and operational support to ensure that mainframe workloads transition smoothly to cloud environments.
Best Practices for Azure Mainframe Migrations
Organizations can ensure smooth migration of mainframe workloads in Azure by implementing the following practices.
1. Assessment and Planning
Effective modernization requires a complete understanding of the current mainframe estate. Begin by cataloging all applications, data repositories, job schedules, interfaces, and dependencies. Evaluate which workloads are best suited for rehosting (lift-and-shift), replatforming (minor code or platform changes), or full refactoring (redesigning for cloud-native deployment).
Tools like Azure Migrate and Microsoft’s Mainframe Transformation Assessment provide insights into resource consumption, batch schedules, transaction profiles, and code dependencies. They help organizations determine workload complexity, business criticality, and cost implications of different modernization paths.
Involve enterprise architects, operations teams, security leads, and business stakeholders early. This ensures alignment on migration goals, timelines, and priorities. Develop a phased migration plan with milestones, fallback strategies, and post-migration validation steps.
2. Standardize on Modern Toolchains
Migrating to Azure involves adopting modern engineering practices as well as moving workloads. Standardizing on cloud-native toolchains ensures consistent, scalable, and secure deployment processes. Use infrastructure-as-code (IaC) tools like Terraform, Bicep, or ARM templates to define and automate environment provisioning.
For development and testing, adopt modern IDEs like Visual Studio or VS Code integrated with legacy language extensions such as Micro Focus Visual COBOL or Raincode tools. These environments allow developers to maintain legacy logic while integrating it into a CI/CD pipeline.
Adopt a version control system like GitHub or Azure Repos for all source code, scripts, and configurations. Use Azure DevOps or GitHub Actions to automate build, test, and deployment workflows.
3. Ensure Thorough Testing Cycles
Legacy workloads often carry decades of business rules, making rigorous testing critical. Establish automated testing pipelines early in the migration process. Include unit, integration, functional, and regression tests. Use Azure Test Plans for test case management and integration with CI/CD workflows.
Recreate realistic production scenarios by simulating transaction volumes and data flows using Azure Load Testing. Include parallel run phases where old and new systems operate simultaneously, and compare outputs to verify correctness.
Incorporate service virtualization tools when dependent systems are not yet available or are too costly to replicate. Validate data integrity through automated checks during each migration phase.
4. Monitor Performance Continuously
After deployment, monitoring becomes essential to maintain performance and detect issues before they escalate. Azure Monitor collects metrics and logs from all components, while Application Insights offers visibility into application behavior, response times, and user interactions.
Set performance baselines based on pre-migration metrics. Configure alerts for deviations in CPU usage, I/O latency, memory consumption, and transaction throughput. Use Azure Log Analytics to aggregate and correlate logs from different systems, including hybrid components that remain on-premises.
Implement dashboards to visualize key performance indicators (KPIs) and operational trends. Monitoring is not a one-time activity—it must evolve as workloads grow, application features change, or usage patterns shift.
5. Prioritize Security From the Start
Legacy systems often have limited built-in security controls, making proactive security planning essential when migrating to Azure. Start with a comprehensive risk assessment. Classify data based on sensitivity and regulatory requirements. Apply data protection policies accordingly.
Use Azure Security Center to identify misconfigurations, apply compliance benchmarks (e.g., ISO 27001, NIST, PCI DSS), and monitor for threats. Implement encryption for data at rest (via Azure Storage Service Encryption or SQL TDE) and in transit (using HTTPS, TLS 1.2+). Use Azure Key Vault for managing secrets, certificates, and keys securely.
Apply the principle of least privilege using Azure RBAC to restrict access based on roles and responsibilities. Enable conditional access and multi-factor authentication (MFA) for administrative access. Regularly review access logs, audit trails, and threat alerts.
