Considerations of Moving Applications Off the Mainframe
January 22, 2020
By Michael Crutcher and Monte Zweben
For decades, Mainframes have anchored industries such as banking, insurance, healthcare, retail, as well as the public sector. All of these industries require heavy-duty low latency transaction processing. Mainframes are designed to provide mission-critical applications with high availability, where downtime would be extremely costly or simply unacceptable.
But mainframe applications are being left behind as businesses strive to transform using distributed computing and public clouds. In large part, this is due to the perception that it’s overwhelming, even impossible, to modernize a mainframe application.
This perception is misguided. New technologies have lowered the barriers to mainframe modernization and deliver several key benefits, including cost reduction, business agility, and unlocking new AI application capabilities. Let’s investigate each of these gains.
Modernizing mainframe-powered applications to use inexpensive commodity hardware significantly lowers upfront mainframe capital expenditures as well as ongoing licensing and maintenance costs. Migrating to the cloud definitely provides unique benefits, but many customers with mainframe workloads also happen to have underutilized on-premises clusters that can be utilized to house modernized mainframe workloads. Mainframe application modernization that results in a containerized solution can often provide the best of both worlds. A Kubernetes approach, for example, can provide a pathway for abstracting away the underlying infrastructure and deploying it on-premises or in the cloud, acting as a bridge between the two options with little or no modification.
Migrating mainframe workloads to the Cloud results in greater business agility. Containerization makes applications significantly more agile because it allows applications to be deployed quickly and resized to accommodate changing infrastructure needs on-demand. It can be exploited both in the cloud or on-premises. Containerizing on-premises apps enables customers to amortize their existing infrastructure investments while providing a fast path to the cloud. The cloud offers pay-as-you-go pricing and easy access to a wide variety of computing infrastructure without the need for IT teams to support a vast number of potential hardware configurations.
Migrating off mainframes also provides a path to a more modern database that enables applications to horizontally scale out to accommodate a more substantial amount of data. It also enhances performance and concurrency by spreading existing data and workloads across unlimited commodity servers. Splice Machine (where I’m a co-founder and CEO) is an example of such a scale-out SQL RDBMS.
Additionally, mainframe developer and operator skills are in scarce supply. It can be easier to find qualified staff for mission-critical applications on more modern programming languages and infrastructure.
Containerization, scale-out databases, and a larger talent pool all lead to much better agility when modernizing mainframe applications.
Third — and the most important reason to migrate applications off the mainframe — is that it unlocks entirely new business outcomes thanks to AI. Modern environments can support this AI. Mainframe-based environments cannot.
Mission-critical applications that have served businesses well for years are being radically modernized through data and new software capabilities. For example, insurance systems no longer simply manage policies and claims. They need to use new data sources to power artificial intelligence and machine learning techniques that score risk, detect fraud or money laundering, and understand what additional options a policyholder might be interested in. And they have to do it all within milliseconds.
Mainframe migration enables established enterprises to keep up with, and even leapfrog, their venture-backed upstart competition, who have used data and AI since they were born. Applications need high performance and scalable, consistent, flexible access to data to do their jobs. When companies swap out their mainframe infrastructure to a converged platform (like Splice Machine), they instantly turbocharge their legacy applications. They instantly give them the ability to handle operational system-of-record workloads, analytical reporting requirements, and automated actions based on in-database machine learning. They instantly make them smart and able to act on predictions.
This data platform is infrastructure agnostic. It can be deployed directly or in containers orchestrated by Kubernetes. It can be provisioned on commodity clusters on-premises or on the cloud. Its unique ability to handle an extremely broad database workload without specialized data schemas and data movement makes it an ideal database for mainframe application migrations. Most importantly, it provides a path forward with machine learning that was not previously available to the application.
In part two of this blog, we will cover the various approaches available to businesses to migrate their mainframe-based applications to a modern platform.
To learn more about how to transform your business in 2020, download our white paper on application modernization and the critical role it plays in digital transformation.