AWS Public Sector Blog

Modernize your legacy mainframe environment with AWS

For decades, public sector organizations have relied on large, legacy, mainframe solutions to reliably process high volumes of secure transactions. But now, Amazon Web Services (AWS) can help modernize your mainframe environment while helping reduce your budget and improve your analytics capabilities.

Legacy systems in the public sector

Mainframes have been around since the 1950s and remained a prominent element of many data centers in state and local government, defense organizations, and federal agencies due to performance, durability, and security. Mainframe solutions are essentially a fully integrated data center with hardware, software, and facility elements enclosed as a complete solution. In contrast to supercomputing clusters, which harness all of their power to work on a single problem, a mainframe uses all of its computing power to perform billions of smaller transactions. These systems are typically used by large organizations for critical applications, such as bulk data processing.

Facing challenges with mainframes

Public sector users face multiple challenges to continuing use of mainframes. First, mainframe solutions are expensive, with some deployments running as high as $16M per year, while consuming significant portions of IT budgets in the form of software, service agreements, and licensing. The vast majority of mainframe costs can be attributed to non-hardware expenses, which are forced onto customers on a yearly basis, or in the form of long-term, binding contracts.

Second, systems run on closed, proprietary software that can only be serviced by experts in COBOL or PL/I programming languages. These computing languages are considered obsolete, which makes finding or building solutions for the mainframe difficult. This outdated technology has no clear upgrade path. As a result, organizations want to reduce their dependency on a shrinking talent pool of mainframe coders, while looking for means to modernize their mainframes.

Third, as with any fixed infrastructure solution, there will come a time when the solution reaches its maximum capacity and leadership will need to decide whether to invest in another large and costly system or to move to the cloud. Adding an incremental mainframe solution increases total cost of ownership (TCO), whereas a cloud-based architecture allows IT managers to capture the value of elastic resources that can scale up or down as usage fluctuates.

Benefits to modernizing your mainframe

With proper guidance and consultation, organizations can see benefits from migrating legacy mainframe deployments to the cloud, such as lowered costs, accelerated innovation, boosted performance, and improved security. Organizations that move their mainframe workloads to the cloud can reduce their capital and operating costs by anywhere from 40% to 90%. Beyond pure cost reductions, some additional benefits include:

  • Modernization: Customers can embrace cloud benefits such as elastic resources, increased agility, and access to the latest technologies.
  • Data analytics capabilities: Customers can break data silos and make mainframe data sets available to a wider range of stakeholders and give access to analytics tools to derive more value from this locked data.
  • Technical debt reduction: Migrating your mainframe environment to the cloud allows organizations to retire costly on-premises systems. By breaking free from these expensive technologies, organizations gain flexibility that opens the door to experimentation and innovation.

Many public sector customers have migrated their mainframes to AWS for these reasons, including: UK Driver & Vehicle Standards Agency (reduced costs 50% by moving to AWS), US Air Force BES (saved $25M by moving to AWS), Finnish Railways, and Scholastic (cut 40% off its IT costs and increased organizational agility by moving to AWS).

Migration options and common workloads

There is no one-size-fits-all for mainframe modernization to AWS. AWS Professional Services and partners created methodologies to help plan and manage mainframe-to-cloud migrations, including seamless integration with AWS tools and technologies. Engage with our teams to determine which option meets your goals.

Some popular and successful patterns implemented by AWS customers include short-term migration with automated refactoring, short-term migration with emulator re-hosting, and augmentation with data analytics.

Below are some architectures that align to these common patterns:

Figure 1: Short-Term Migration with Automated Refactoring

Figure 1: Short-Term Migration with Automated Refactoring


Figure 2: Short-Term Migration with Emulator Re-Hosting

Figure 2: Short-Term Migration with Middleware Emulation


Figure 3: Augmentation with Data Analytics

Figure 3: Augmentation with Data Analytics


To help customers begin their mainframe modernization journey, AWS launched a series of webinars led by our experts and key partners, covering common mainframe migration patterns and best practices. Hear from AWS partners such as CANDID, ARRAY, and mLogica, as they detail their experiences while helping customers migrate their mainframe environments to AWS. You’re invited to attend our “Mainframe Modernization & Migration” webinar series, and hear experiences and lessons learned based on real-world customer modernization projects with AWS.