It has been announced that Google Cloud is introducing a simpler, more risk-averse way for enterprises to migrate their legacy mainframe estates to the cloud. Google Cloud's newly launched service is based on technology originally developed by Banco Santander and aims to simplify planning and execution.

As a result, customers can perform real-time testing before they transition to Google Cloud Platform as their primary system to ensure their cloud workloads are performing as expected, running securely, and meeting regulatory compliance requirements – without stopping their application or negatively impacting user experience.

In his interview with Protocol on Tuesday, Nirav Mehta told: "This is a simple concept, but it is difficult to implement - hasn't been done yet," Nirav Mehta, Google Cloud's senior director of product management for cloud infrastructure solutions and growth, said. As compared to moving mainframe applications to the cloud, this solution will substantially reduce the risk associated with doing so." 

A parallel instance of mainframe workloads is created by using virtual machines on the Google Cloud Platform (GCP) through Dual Run. As Mehta describes, a launcher/splitter is an architecture consisting of the necessary mechanisms to duplicate activity - and return the "primary" response of the system - at each interface that drives the incoming requests or triggers the scheduled workload and can handle both.

A dashboard that displays real-time monitoring shows the differences in transaction responses between the mainframe and GCP deployments that are displayed on the dashboard. The single output hub also ensures that there is a single point of contact during the roll-out period for all batch information that needs to be sent out and collected.

Once the customers are comfortable with the use of their mainframes as backups, they can retire their mainframes or use them as storage.

As long as your mainframe is the primary system that handles customer requests, it should remain the system of choice for quite some time to come. You can consider the cloud instance as nothing more than a secondary system. This will also run the same requests as the regular system, Mehta explained. As part of your monitoring process, you maintain a record of the responses coming back from both the mainframe and Google Cloud. This is to determine whether the Google Cloud instance is working equally well as the mainframe. Then at some point, you switch over to using Google Cloud as your primary source of data and the mainframe as your secondary source of data.

The Dual Run device, which is currently in the preview stage, was developed for a wide range of industries, including the financial services, health care, manufacturing, and retail industries, and the public sector as well. Approximately 90% of North America's biggest banks still use mainframes, according to Mehta, while 23 of the 25 largest U.S. retailers use mainframes as well.

"All of these companies are looking to modernize their old mainframe applications and take them to the cloud to maximize security, scalability, and cost efficiency," he said. However, because these systems are so mission-critical - and mainframes are especially unique in this regard since they've been around for so long and contain so much legacy technology - they perceive a lot of risks, so they do not bring them to the cloud."

In May, Banco Santander, a Google Cloud customer, published a report about the progress it has made in digitizing its core banking platform. It said that 80% of its IT infrastructure had been moved to the cloud using software developed in-house called Gravity, to automate the process. The technology is an exclusive license that Google Cloud has acquired, and its engineers have been working with Santander during the past six months to optimize the technology to make it more suitable for end-to-end mainframe migrations for customers in a wide variety of industries. 

Mehta explained that they only had a very limited use case for the software. The relevance of the solution to any mainframe customer has been elevated to a substantial extent thanks to the changes we have made. This is a huge deal for anyone running mainframes because it allows them to access data remotely.