In the mainframe/cloud context, there are huge barriers to entry for getting mainframe data into cloud environments where it can be consumed by AI, ML, and advanced analytics applications. This is where Model9 makes a difference by making it easier for cloud application tools to consume the valuable data the mainframe holds. “We do this by copying mainframe data as-is into the cloud without any transformation, and then managing and manipulating that data on the cloud side, including transforming it into open formats from inside the cloud,” says Gil Peleg, CEO of Model9.
Model9 adopts a data-first/software-only approach to this type of mainframe modernization, allowing companies to move mainframe formatted data into the cloud faster and more efficiently than ever before. The Model9 Cloud Data Platform for Mainframe makes it easy to manage a connection between the mainframe and the cloud without requiring tape or emulated tape technologies to function. This eliminates legacy data management systems tied to legacy storage options that require specialized mainframe expertise to operate. Once in the cloud, Model9’s company’s data engine can transform mainframe data into open formats for use with cloud applications while not consuming additional mainframe resources.
“By putting data at the heart of the mainframecloud connection (instead of mainframe applications), IT leaders no longer have to wait for long, risky, costly, and uncertain migration projects to finish before being able to get insights from their mainframe data. In addition, this same process can be used to backup and archive data directly from the mainframe to the cloud and eliminate the need for complex and costly legacy storage,” Peleg notes.
Apart from cost reduction and simplification, Model9’s solution streamlines the journey of making mainframe data accessible to cloud tools, thereby allowing companies to democratize it.
Notably, a recent survey commissioned by Model9 found that 96 percent of IT leaders use a hybrid cloud model. The top benefit of a hybrid cloud strategy cited by respondents is flexibility, closely followed by resilience/disaster recovery. Model9’s solution greatly improves cyber resiliency and lowers risks. Model9 creates immutable copies either on the public or the private cloud. When sent to cloud object storage, the mainframe data can also be airgapped, which means an offline copy is maintained and can never be maliciously accessed.
Model9 demonstrated its robust capabilities while engaging with a leading U.S.-based transportation company. The company made a strategic decision to leverage cloud technologies in order to improve operational efficiency and wished to move its DB2 and other data to a AWS data lake, to be transformed for use with the Snowflake cloud data warehouse. To implement its data strategy, the company chose the Model9 cloud data management solution as a front-end for the Amazon S3 cloud storage service. With Model9, the company was able to replace its costly, proprietary tape systems with Amazon S3 cloud storage, to leverage its valuable mainframe data for business intelligence analytics using Snowflake.
With many such success stories under its belt, Model9 will continue to evaluate the inhibitors that companies encounter in managing and maintaining data in the mainframe/cloud interconnected ecosystem. The company seeks to leverage its expertise to help its customers optimize the business value of the mainframe data that they have in the most efficient yet secure manner. By creating a hybrid cloud that makes mainframe data available for cloud applications to consume, organizations can build a complete cloud data lakehouse for the mainframe, granting cloud AI and analytics controlled access to its data. That allows business leaders to better understand their customers, improve operations, deliver better services and products, and generate new revenue. “Our vision is to democratize mainframe data so all leaders in an organization can make better business decisions,” remarks Peleg.