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I&O Leaders DON’T Need to Refactor Mainframe Applications to Achieve a Cloud-first Strategy

Gil Peleg


Jun 30, 2021

Cloud-first strategies propose an optimistic ideal in which on-prem IT is a thing of the past and any imaginable function can be bought or created in the cloud. To be sure, this vision is based on a reality: There are many successful organizations that have been “born in the cloud” and many others that have successfully moved most or all functionality there, as well.

But I&O leaders of mainframe-based organizations, though often subjected to relentless questioning regarding potential financial benefits from moving to the cloud, know that the nature of mainframe and the “gravity” of the data and applications on premises, make a move to the cloud challenging, at best. For them, ‘cloud first’ can seem to be nothing but a chimera.

However, it doesn’t have to be that way. Modern tools put the cloud within reach as never before; initially as an adjunct to mainframe and, over the long term, perhaps even as a replacement if such a move actually makes business sense (and, it often does not!).    

Cloud is best considered as part of a mainframe modernization effort. The very unique characteristics of mainframe and mainframe applications means that migrating them to the cloud is difficult, requiring refactoring and/or rearchitecting, which is time-consuming, expensive, and risky. So, approaches that strengthen the mainframe while engaging with cloud make sense.

Blocked by Siloed Mainframe Data

Reluctance to attempt actual application migration to the cloud is an acknowledgement that the default approach trends not towards cloud first, but instead a ‘Mainframe + Cloud’ strategy. But the result is mainframe data silos that limit business options and reduce the utility of the data.

Siloing your mainframe data has an immediate business impact. Your most valued data is excluded from some of the most important analytical tools available, in particular cloud-based data lakes that have become a key tool for enterprises striving for agility and insight.

That absence of data also significantly limits the potential ROI of any cloud adoption and integration strategy because cloud capabilities will be missing a critical portion of the universe of relevant data. And, ultimately, it leaves your company in a straightjacket, restricting the potential dynamism of your IT organizations.

Data-led Migrations are the Key

Fortunately, this problem has a solution. Rather than taking the old-school approach of attempting to migrate mainframe applications all at once or keeping your data siloed, there is a modern alternative. It is based on the prescient idea that data itself is the answer. Data gravity is the colloquial term for the insight that data has power wherever it is located and can be accessed. That’s true when the data is locked exclusively in the mainframe environment and it is also true if it can be moved to the cloud. Move the data, according to this insight, and functionality will naturally tend to follow.

Put another way, moving the data is what matters. Once the data is available in a different environment the organization will evolve ways to access and use that data – either by migrating applications or by choosing to adopt a cloud capability that can deliver the same results with less cost and trouble.

Model9 delivers the capability to move your data and empowers you to choose when and, equally important, how much. For example, you can start with archival data that is used infrequently in the mainframe but has potentially limitless value in an analytics context. By moving that data to the cloud, you can free storage capacity on-prem (potentially allowing you to eliminate tape and VTLs). The mainframe can still access the data when needed but analytic tools in the cloud may use it much more often.

With data gravity increasingly centered in the cloud, you are in charge. You can continue to support mainframe while gradually building new applications and functionality in the cloud. Or, the data is there if you eventually decide on a full lift and shift. 

No matter the scale of movement required, Model9 can support it. Data can be moved without first having to select only files deemed relevant. All the data can be moved. And the further slicing and transformation into desired format can be accomplished in the cloud. You can enjoy all the benefits of mainframe data in the cloud, while still retaining the ability to refactor your mainframe applications only when you are ready, if at all

Model9 puts you in charge of your data and lets you put data gravity to work for your goals, allowing you to reshape your IT operations the way you want.

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About the author

Gil Peleg | CEO
Gil has over two decades of hands-on experience in mainframe system programming and data management, as well as a deep understanding of methods of operation, components, and diagnostic tools. Gil previously worked at IBM in the US and in Israel in mainframe storage development and data management practices as well as at Infinidat and XIV. He is the co-author of eight IBM Redbooks on z/OS implementation.
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