What Is Mainframe to Cloud Migration?
Mainframe to cloud migration involves transitioning applications, data, and workloads from mainframe systems to cloud platforms. This process modernizes IT environments by leveraging the flexibility, scalability, and innovation available in cloud infrastructure.
The migration can vary from rehosting to complete refactoring, depending on business needs. Key motivations behind such migrations include reducing operational costs and overcoming the limitations of aging mainframe systems.
Financial institutions and large enterprises with significant mainframe investments often undertake this migration process. The challenge lies in ensuring uninterrupted service and maintaining data integrity during the migration. Careful planning and execution are crucial to the success of a mainframe cloud migration strategy.
This is part of a series of articles about mainframe modernization
Key Benefits of Migrating from Mainframe to Cloud
Here are some of the reasons to move a mainframe system to the cloud.
Modernize Outdated Technology and Attract New Talent
Mainframe systems are often built on outdated technology that can be cumbersome to maintain and improve. Migrating to the cloud enables organizations to update their tech stack, leveraging modern programming languages and tools that are more relevant and efficient. This shift improves system performance and reliability and lays the foundation for future innovation.
Modern architectures and technologies are more attractive to new talent entering the workforce. Young professionals typically prefer working with the latest tools and platforms. By transitioning to the cloud, organizations can attract skilled individuals eager to work in a contemporary technological environment.
Improve Scalability and Agility
Cloud platforms offer unmatched scalability compared to mainframe systems. Organizations can scale their IT resources up or down depending on demand, eliminating the need for overprovisioning hardware. This on-demand scalability results in improved resource efficiency and cost management, particularly for applications with variable workloads.
Agility is another critical benefit of migrating to the cloud. Enterprises can quickly deploy new applications and services without the lengthy procurement and provisioning processes associated with mainframes. This increased agility allows companies to respond to market opportunities and challenges more effectively.
Reduce Costs and Complexity
Moving from mainframes to the cloud significantly reduces operational costs by eliminating the need for expensive hardware maintenance and upgrades. Cloud services often follow a pay-as-you-go model, meaning organizations only pay for the resources they consume. This flexibility leads to better financial predictability and aligns expenses with actual usage.
Complexity is also reduced since cloud providers manage much of the underlying infrastructure. This simplifies IT operations as organizations no longer need extensive in-house expertise to maintain and troubleshoot legacy systems. IT teams can focus on strategic initiatives rather than day-to-day maintenance, resulting in higher operational efficiency.
Learn more in our detailed guide to mainframe migration (coming soon)
5 Core Approaches for Mainframe Migration to the Cloud
There are several ways to implement a mainframe to cloud migration. Here are some of the main approaches.
1. Rehosting (Lift-and-Shift)
Rehosting in mainframe migration means moving legacy applications directly from a mainframe to a cloud environment with minimal changes to the code or architecture. Mainframe emulation technologies, virtual machines, or replatforming tools are typically used to replicate the original computing environment in the cloud.
This method allows organizations to quickly retire costly mainframe hardware while preserving existing business logic and minimizing disruption. It is especially effective for stable, well-understood applications. However, because applications are not redesigned for cloud, organizations may miss out on cloud-native benefits like dynamic scaling, managed services, and resiliency enhancements
2. Refactoring
Refactoring in the context of mainframe migration involves restructuring or optimizing the original application code to better suit cloud environments without changing the application’s core functionality. For example, monolithic COBOL programs might be modularized or modernized to run more efficiently on cloud infrastructure.
This strategy can strike a balance between speed and modernization. Refactoring improves maintainability, performance, and scalability while avoiding the risks of a complete rebuild. However, it requires careful code analysis and skilled teams familiar with both legacy mainframe programming and modern cloud development practices.
3. Rebuilding
Rebuilding in a mainframe migration context means completely rewriting legacy applications to run natively on cloud platforms. Instead of trying to replicate mainframe behavior, organizations design modern applications from the ground up, using contemporary programming languages, development frameworks, and cloud-native architectures like containers, microservices, and serverless functions.
This approach enables maximum optimization for cloud environments, unlocking capabilities like auto-scaling, real-time data integration, and rapid deployment pipelines. However, it is resource-intensive and requires deep expertise in both the original business logic and modern application development.
4. Replacement or Retirement
In mainframe migration, replacement refers to substituting legacy systems with modern cloud-based commercial off-the-shelf (COTS) solutions that replicate essential business functions. Retirement involves decommissioning applications that are obsolete, redundant, or whose functionality can be consolidated into newer platforms.
This method is often driven by a desire to cut maintenance costs and eliminate technical debt. However, replacement or retirement requires a detailed assessment of application dependencies, business processes, and compliance needs to avoid gaps in service or data loss. It may also require substantial retraining of users and revision of internal workflows.
5. Partial Modernization
Partial modernization for mainframe migration involves selectively moving specific workloads, applications, or services to the cloud while keeping mission-critical or highly integrated components on the mainframe. This is common when full migration is too risky, costly, or impractical due to regulatory, performance, or technical constraints.
Typical candidates for partial migration include data analytics, customer portals, or batch processing systems. Over time, this incremental approach can evolve into a full migration as dependencies are decoupled and cloud maturity grows. It provides a lower-risk, phased path to modernization while still delivering early wins and cost savings.
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Common Technical and Organizational Challenges
Organizations often face the following challenges when migrating mainframe systems to the cloud.
Complex Legacy Architectures
Mainframe applications often contain decades-old custom code, tightly coupled components, and proprietary interfaces. These systems were not designed with modern interoperability or modularity in mind, making them hard to analyze, understand, and decouple. Even basic documentation may be outdated or missing, adding to the challenge of reverse engineering functionality.
Dependencies across modules, legacy programming languages like COBOL or PL/I, and custom integration points complicate the mapping of current workflows to cloud-native architectures. Migrating such systems requires careful planning, tool-assisted code analysis, and phased refactoring to avoid business disruption.
Data Security Risks and Regulatory Compliance
Mainframes typically operate in highly secure, controlled environments, especially in sectors like banking and healthcare. Migrating to the cloud introduces new vectors for data exposure, including internet-based access, shared infrastructure, and increased reliance on third-party vendors.
Ensuring compliance with regulations like HIPAA, GDPR, or PCI-DSS requires strong encryption, detailed audit trails, and rigorous access controls in the cloud environment. Organizations must also align their cloud security posture with internal policies and external mandates, often requiring a redesign of identity management, data residency strategies, and monitoring systems.
Knowledge Gaps and Skill Shortages
Many mainframe systems are maintained by specialists nearing retirement, while fewer professionals are trained in legacy technologies. At the same time, cloud environments demand new skill sets in areas such as containerization, DevOps, and cloud-native development.
Bridging this gap requires investment in upskilling, cross-training, and sometimes hiring new talent with cloud experience. Without this, organizations risk project delays, misconfigurations, or reliance on expensive external consultants.
Insufficient Migration Strategies
A successful mainframe-to-cloud migration requires a clear roadmap, but many organizations start without a detailed plan or underestimate the complexity involved. Lack of upfront assessment, unclear prioritization of applications, or misalignment with business goals often leads to stalled or failed migrations.
Effective strategies require rigorous application inventory, risk assessments, and phased rollouts with built-in testing and rollback mechanisms. Organizations should also define success metrics, involve stakeholders early, and allocate sufficient resources for both technical execution and organizational change management.
5 Strategies for a Successful Mainframe to Cloud Migration
Organizations can improve the effectiveness of their migration of mainframe applications to a cloud environment by implementing these practices.
1. Evaluate Code Quality and Complexity
Before migration begins, perform an assessment of all mainframe applications. This includes code quality checks, complexity analysis, dependency mapping, and documentation reviews. Legacy systems often include thousands of lines of code written in COBOL, PL/I, or assembler, much of which may be poorly documented or tightly coupled.
Use static analysis tools to detect technical debt, redundant code, and modules that can be modularized or retired. Understanding these factors helps determine the appropriate migration approach—rehosting, refactoring, or rebuilding—and guides planning efforts. Early evaluation also reveals integration points with external systems, which must be addressed to avoid migration surprises.
2. Implement a Phased, Staged Approach
Migrating all systems at once is risky and rarely feasible. A phased strategy reduces this risk by segmenting the migration into manageable stages based on business impact, application complexity, and interdependencies. Begin with low-risk, standalone applications to build confidence and refine tools and processes.
Each phase should include testing, monitoring, and feedback loops. Establish clear success criteria and rollback plans for every stage. This approach enables continuous learning and process improvement while minimizing operational disruption. Additionally, it helps train teams and prepare users for larger shifts later in the migration.
3. Adopt Automated Testing and CI/CD
Automated testing is essential to validate functionality and performance before and after migration. Legacy applications should be surrounded with unit, regression, integration, and performance tests to detect issues introduced during rehosting or refactoring. Building a strong test suite ensures migrated code behaves as expected in the cloud.
Integrate testing with CI/CD pipelines to support faster, more reliable deployments. This includes automated build processes, environment provisioning, and post-deployment validation. CI/CD enables continuous delivery of features and fixes, shortens feedback cycles, and reduces human error.
4. Select the Right Cloud Platform
Choosing a cloud platform goes beyond infrastructure. Evaluate platform features such as support for mainframe-like capabilities (e.g., batch processing, high I/O workloads), managed services, regional availability, and compliance certifications. Ensure the platform can handle the scale, latency, and throughput requirements of workloads.
Consider hybrid cloud and multi-cloud options if full migration isn’t feasible initially. Assess pricing models, tool compatibility, and partner ecosystems to ensure long-term flexibility. Selecting a platform that aligns with the target architecture—whether containers, serverless, or microservices—simplifies the migration path and reduces future rework.
5. Plan for Gradual Legacy Decommissioning
Mainframe systems are often deeply embedded in enterprise workflows, so full shutdowns must be planned carefully. Begin by identifying which components can be safely retired, such as rarely used modules or reporting tools now replaced in the cloud. Build coexistence models where both cloud and mainframe systems run in parallel during the transition.
Create a roadmap for decommissioning that includes data migration, dependency resolution, and system integration updates. Monitor usage to ensure legacy systems are no longer needed before turning them off. Gradual decommissioning lowers operational risk and enables better resource allocation as the organization fully transitions to cloud-native operations.
Supporting Mainframe Migrations with Swimm
When planning your mainframe migration, understanding the existing codebase is essential for success. Swimm helps technical teams address this challenge by automatically mapping and documenting legacy systems, significantly reducing the time traditionally spent on manual code analysis.
Swimm’s technology extracts business rules from COBOL applications, identifies dependencies between programs, and creates clear visualizations of application architecture. This comprehensive understanding helps preservation of critical business logic during cloud transition.
