Model9 used this year’s Arcati Mainframe Yearbook to look at a different way of modernizing mainframes, focusing on the benefits of a data-centric approach connecting the cloud and the mainframe. This smart approach naturally creates realistic, achievable steps that bring business benefits at each stage.
Model9 started by asking, “how many mainframe modernization efforts are on-going, falling behind the projected schedule, or over budget?” They suggested that the answer might be many because the focus of their planners was in the wrong place. Early efforts were on replacing mainframe hardware, and then mainframe software. But now, the integration of the mainframe and cloud is a favoured approach. How enterprise IT leaders build and manage the connection between the mainframe and the cloud will be the biggest story for mainframe professionals in 2022.
Initial efforts to bring mainframe data into the cloud have had minimal success and have not realized the full business potential. The reason is because these projects are not building a proper connection to capitalize on the value that mainframe data in the cloud can bring.
Model9 believes IT leaders should begin to think differently about mainframe modernization. It should be viewed as a data-centric business initiative that can deliver value in the short-term, and also create an environment conducive to ongoing optimization – instead of just an infrastructure update.
Taking a data-centric approach to mainframe modernization shifts the focus from mainframe applications to mainframe data. Instead of trying to establish long and complex roadmaps for changing mainframe applications, IT leaders should begin by focusing on using software-only solutions for moving mainframe data, still in mainframe format, into cloud storage solutions, and then managing the connection between the two.
New technologies allow mainframe professionals to migrate mainframe formatted data into the cloud via zIIP engines and TCP/IP – and store it in the cloud in object storage. Mainframe professionals can also use new, modern cloud data management software for the mainframe to create a bi-directional sync between the mainframe and cloud that does not require tape or emulated tape technologies to function.
Making this shift allows the mainframe to leverage all the advantages of the cloud: fully managed storage, ubiquitous access, and virtually unlimited capacity. This reduces labour costs and equipment investment for the organization, and allows businesses to change their focus from daily operational problems to formulating strategies to deliver value to their customers.
By integrating mainframe data into the cloud environment in this way, both IT leaders and mainframe professionals achieve several objectives.
1 This approach delivers immediate value while taking steps towards long-term modernization. Instead of one large, complex, project that is doomed to fail, using software to move mainframe data to the cloud is a more agile approach, where you can define smaller, more manageable sprints.
2 This approach breaks the silo surrounding mainframe data. Placing the data into the cloud – even when still in mainframe format – changes the mainframe from an isolated island into an integrated part of the technology architecture, giving mainframe professionals a seat at the broader IT table.
3 This approach can be used to securely eliminate tape/VTL backups, which brings cost savings and can improve disaster recovery – both in speed and accessibility in recovery scenarios.
In addition to meeting strategic objectives, a data-centric approach to mainframe modernization creates more business value in a number of other ways.
Taking a data-centric approach to mainframe modernization enables data gravity to advance modernization efforts. Data gravity is the idea that data and applications are attracted to each other (like object attraction in the Law of Gravity). As datasets grow, they become harder and harder to move and consequently, the data stays put. The data gravity causes applications and processing power to then move where the data resides. By placing mainframe data in the cloud, this creates a natural pull to connect mainframe data to cloud applications as well as to eventually bring mainframe applications to the cloud as appropriate. Fundamentally, it makes longer-term mainframe modernization projects easier to achieve.
Instead of managing backups and mainframe data on the mainframe, having mainframe data in the cloud allows mainframe data management to take place in the cloud. This shift allows companies to stop using IBM's HSM for storage management. While a great tool, HSM is often a top consumer of general-purpose compute (GCP) cycles and a big MIPS consumer. Moving mainframe data management to the cloud results in freeing up compute and MIPS for other higher-value purposes.
When data transformation takes place in the cloud using EC2 resources, this frees up valuable MIPS consumption for other projects. ELT (extract, load, transform) architecture can be used to deliver mainframe formatted data to object storage in the cloud, and then transform it into open formats for use in cloud applications. This eliminates proprietary data silos without consuming mainframe CPU or requiring changes to your mainframe applications. Performing mainframe data transformation in the cloud is less expensive and creates business value by reassigning mainframe processing power.
Having mainframe data in the cloud and the ability to transform it in the cloud makes it easy to connect into Business Intelligence (BI), Artificial Intelligence (AI), and Machine Learning (ML) tools and applications. This data can be analysed to provide new insights and help drive the intelligence of business applications where AI and ML are utilized.
The benefits created when taking a data-centric approach for bringing mainframe into the cloud are significant and have short and long-term impact. Here are the four key benefits that organizations realize:
- Modernization is facilitated.
- Mainframe compute is freed up.
- Costs are lowered.
- Creates a competitive advantage.
A data-centric approach to mainframe modernization is a very smart approach that naturally creates realistic, achievable steps that bring benefits at each stage. For organizations that are stuck in projects to move mainframe applications to the cloud, it's not too late to pivot and start making significant strides by moving data first.
You can read the full article from Model9 here.
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