By Eduardo Ciliendo, VP of Worldwide Strategy and Technology, Model9
Mainframes often sit outside organizations’ hybrid cloud strategies. It’s time to invite them to the party.
Enterprises have invested in hybrid cloud architectures as a way to provide flexibility and innovation to their organizations. Most companies with mainframes, however, have yet to successfully integrate them into their hybrid cloud strategy. In fact, our recent survey of IT leaders’ views on mainframe modernization revealed that the majority of mainframe modernization efforts are actually at odds with leaders’ stated goals for the hybrid cloud.
The most effective option for managing mainframe modernization in a way that complements hybrid-cloud initiatives is a data-first approach that leverages the scale and economics of the cloud. This approach removes the risk associated with application change and greatly accelerates time to value. When fully implemented, it delivers significant business, operational and financial benefits. Let’s examine three distinct ways aligning your mainframe modernization and hybrid cloud strategies can deliver value to your organization.
Mainframe data is often the most valuable data in enterprises, yet it is siloed from the rest of the business. Not having access to the business insights trapped in mainframe data often leads to blinds spots in a corporation’s data strategy. The goal is making mainframe data actionable in a way that is natural for a company’s data scientists, hence in formats that are easily accessible and cloud native.
With the right solution in place, opening up mainframe business insights can become seamless. Model9, for example, extracts mainframe data, both current and historical, in any format including Db2, VSAM, sequential and partitioned data sets, loads it into the cloud, and then transforms it on the cloud into standard open formats such as JSON or CSV. Extracting data at scale and then transforming it in the cloud completely changes the decades old Extract Transform Load (ETL) paradigm and turns it into a more efficient Extract Load Transform (ELT) approach that is more efficient and uses less resources on the mainframe.
This novel approach makes mainframe data actionable by allowing artificial intelligence (AI), machine learning (ML) and analytics applications to access it in the cloud via standard APIs and in formats that data scientists are well versed in. The end result is massive amounts of critical enterprise data, including sometimes decades of historical data, readily available in a cloud data lake to improve AI and ML algorithms and help enterprises with better decision making.
Although mainframes are usually thought of as secure, they are not impenetrable. And since mainframe data is mission critical to the organization, a single mainframe vulnerability could lead to a major breach, significant financial losses, and painful reputational damage. Mainframe modernization should also include a focus on protection against cyber threats. When mainframe data is included in a hybrid cloud environment, new opportunities to secure that mainframe data emerge.
One powerful way you can protect your mainframe data from cyber-attacks such as ransomware is by creating a third data copy that is immutable and air-gapped using cloud-based storage. Using immutable cloud storage has a number of distinct advantages over on-premise cyber resiliency implementations. Not only is a cloud-based data copy much cheaper and faster to implement, having data in the cloud opens up a world of additional resilience capabilities such as cloud based cyber forensics or the possibility to restore your data in a clean-room environment anywhere on the globe.
Cloud-based backups are a great example of how a hybrid cloud strategy is better than keeping mainframe data siloed on premise using proprietary legacy technology. Our survey revealed that leaders face many challenges with current backup solutions. Not only are proprietary backup solutions more expensive than open Object Storage but legacy protocols also hamper backup performance and cause lengthy backup windows that are not in line with today’s 24x7 business requirements. Legacy tape environments with a tendency of physical failure (e.g. stuck or failed tapes) furthermore consume critical IT personnel from doing more valuable work. Eliminating VTL and tape backup hardware and software by moving data backups into the cloud is a way to meet all of these challenges.
You can shorten the window with a solution like Model9 Manager, which uses TCP/IP with parallelism to transfer and load the data into the cloud object storage faster than with physical tape and even many virtual tape solutions. By redirecting mainframe data (backed up, archived, and full volume dumps) directly to object storage, on-premises or in the cloud, this approach eliminates the need for tape/VTL entirely.
Overall, backing up data to the cloud with Model9 Manager gives you better flexibility, reliability, convenient sharing of data, elimination of maintenance and updates hassles and no less important—significant cost savings!
Ensuring mainframe modernization and hybrid cloud initiatives complement one another should be a key priority for IT leaders. Companies should take a data-first approach that makes common cause between mainframe modernization and hybrid cloud strategies.\\
