What strategies are effective for migrating mainframe systems to the cloud?

For decades, the mainframe has been the unshakable workhorse of the global economy, processing billions of transactions daily for banks, insurers, retailers, and governments. Its reputation for rock-solid reliability and security is well-earned. However, as we move further into the digital age, these legacy giants are becoming anchors on business agility.

The pressure to modernize is coming from all sides. IT budgets are strained by the high and often rising costs of proprietary mainframe maintenance. The pool of experienced COBOL and Assembler talent is shrinking rapidly, creating a critical skills gap. Furthermore, the monolithic nature of mainframe applications makes it incredibly difficult to integrate with modern APIs, leverage real-time data, or roll out new features at the speed the market demands.

Migrating to the cloud offers a path to escape these constraints, promising scalability, cost efficiency, and faster innovation. But moving mission-critical systems is a complex endeavor. It requires a well-planned strategy, not a blind lift-and-shift. Here are the most effective strategies for a successful mainframe-to-cloud migration.

1. Define Your "North Star" and Adopt a Multi-Pattern Approach

The first rule of mainframe modernization: Do not treat it as a single, monolithic IT project. Experts at AWS advocate for starting with a clear "North Star"—a vision articulated by the C-suite that answers three fundamental questions: Why are we modernizing? Where are we going? When will it happen? Without this executive alignment, organizations often end up with disjointed, tactical programs that fail to deliver full business value.

Once the vision is set, a disposition strategy is key. This involves recognizing that a "one-size-fits-all" approach doesn't work. A mainframe estate is diverse, containing different applications with different business needs. A comprehensive strategy involves decomposing the monolithic codebase into manageable chunks and selecting the right migration pattern for each workload based on business and technical criteria. These patterns generally fall into a few categories:

• Rehost (Lift and Shift): Moving workloads to a Mainframe-as-a-Service (MFaaS) provider with minimal code changes. This is often a quick win for meeting urgent data center exit deadlines.

• Refactor (Automated Transformation): Using specialized tools to automatically convert legacy code (e.g., COBOL to Java) and migrate proprietary databases to open-source alternatives. This preserves core business logic while making the application cloud-native.

• Reimagine (Rearchitect): For applications that need new features or a modern user experience, this involves breaking the monolith into microservices. This is the most complex pattern but offers the highest long-term agility.

2. Leverage the Power of GenAI and Automation

Perhaps the most significant shift in modernizing mainframes is the advent of Generative AI. Historically, "reimagining" applications was a high-risk, manual process prone to failure. Today, GenAI is changing the game by dramatically reducing the effort, cost, and timeline.

Leading best mainframe modernization services are now embedding AI agents into their workflows. These agents can analyze millions of lines of legacy code, extract business logic, automatically generate new code in modern languages, create test cases, and even fix bugs. For example, AWS Transform uses specialized agents to document business rules from COBOL applications, which can then be used to auto-generate user stories in agile project management tools.

Automation also extends to testing, which typically consumes over 50% of a migration project's time and budget. By implementing fully automated testing, organizations can ensure functional equivalency with the original system and conduct frequent, thorough test runs, building confidence before the final cutover. This powerful combination of AI and automation is making mainframe modernization accessible to a broader range of organizations.

3. Prove Value with a Pilot Project

Before diving headfirst into a full-scale migration, smart organizations start with a proof of concept. This de-risks the entire program and builds internal momentum.

Consider the case of Jonas Fitness, a provider of club management software. Facing a costly, aging mainframe and a shrinking COBOL talent pool, the company engaged in a proof of concept focused on just one application: its payment gateway. The success of this pilot gave them the confidence to move forward with a full modernization using AWS Blu Age.

The results were staggering. By refactoring their COBOL applications to Java and migrating to AWS, Jonas Fitness reduced its infrastructure costs by a remarkable 90%. They eliminated the need to run the mainframe 24/7, adopted modern development practices using containers, and future-proofed their business for innovation.

4. Prioritize Workloads Based on Value and Complexity

Not all mainframe applications are created equal. A successful disposition strategy involves using clear criteria to decide what to migrate and in what order.

• Business Value: Identify applications that, if modernized, could unlock new revenue streams, improve customer experience, or enable growth. If the business requires new features (like a modern mobile interface), these workloads should be prioritized for a "reimagine" pattern.

• Technical Complexity: Assess the source technologies. Niche technologies like Natural/Adabas or IDMS may have fewer refactoring options, potentially making a "replace" pattern more viable. Conversely, standard COBOL on Db2 is well-supported by automated refactoring tools.

• Vendor Timelines: Upcoming software license renewals can be a powerful catalyst. If you have an urgent deadline to exit a costly vendor agreement, a faster refactoring pattern might be preferable to a slower, more complex rewrite.

The GRAWE Group, an Austrian insurance company, provides a perfect example. They needed to migrate a core application with over 6 million lines of Natural code and an Adabas database. Because of the niche technology stack and the need to move quickly, they partnered with Deloitte for a targeted transformation. Using automated tools, they successfully converted the application to Java and the data to Oracle over a single weekend. The result? A 60% reduction in operating costs and a smooth transition to an open-systems platform.

5. Choose the Right Partner and Leverage Ecosystems

Given the complexity and critical nature of mainframe workloads, going it alone is rarely the best path. The market is rich with specialized service providers and cloud partnerships that can accelerate your journey. Recent industry reports from ISG consistently highlight leaders in this space, recognizing their deep expertise and innovative solutions.

When evaluating the best mainframe modernization services, look for partners that demonstrate:

• A Robust Partner Ecosystem: Top providers have strong alliances with major cloud hyperscalers (like AWS, Azure, and Google) and technology partners. This ensures you get access to the best tools, incentive programs, and technical expertise.

• GenAI Capabilities: Leaders are embedding AI into their assessment, code conversion, and testing processes, using proprietary platforms like Hexaware's RapidX™ to accelerate timelines and improve accuracy.

• Vendor-Agnostic and Flexible Solutions: The best partners, like DXC Technology, offer vendor-agnostic advice and flexible delivery models—whether you need help optimizing your current mainframe, moving to a Mainframe-as-a-Service model, or fully migrating to the cloud.

• Full-Scope Modernization: They go beyond just moving code, helping you re-engineer business processes, implement DevOps, and integrate your modernized applications with the rest of your digital ecosystem.

Meliá Hotels International's journey exemplifies the power of a strong partnership. Working closely with AWS, they set the ambitious goal of decommissioning their mainframe in two years, half the estimated time. With support from AWS Professional Services and the AWS Migration Acceleration Program, they split their monolithic central reservation system into microservices on Amazon EKS. The outcome was transformative: 60% cost savings, a 75% improvement in time-to-market, and the ability to scale effortlessly during peak demand.

Conclusion

Mainframe migration is no longer just about managing risk; it's about seizing opportunity. By defining a clear vision, embracing a multi-pattern strategy, harnessing the power of GenAI, and partnering with experienced leaders, organizations can turn their most critical legacy systems into a springboard for future innovation. The journey is complex, but as the success stories show, the destination—a flexible, scalable, and cost-efficient cloud future—is well worth the effort.