Mainframes are dead! Long live cloud computing!


Among the important things that has typically driven me nuts with the increase of cloud computing is the presumption that the demise of the mainframe is an inevitable conclusion. I’ve often discussed the reality that not all applications and data sets belong on the cloud, especially ones that reside on mainframes.Although I have often been laughed out of a meeting for this viewpoint, adoption patterns have proved me right. It’s often spun as a pushback on cloud computing itself, however it’s simply pragmatism.The truth is that we

‘re going to discover applications and data sets(more than you believe ), that are not viable to move to the cloud. I call this the point of saturation, when we’re done moving most of the applications to the cloud that are practical to relocate. I’ve had mainframe applications in mind when stating that, and for good reason.It can be done Those who push back on this assertion rapidly explain

that some tools and innovations permit older mainframe applications to be ported to a cloud service provider. These strong products established emulators and code converters to run mainframe-based applications on public cloud providers.Yes, you can go this path. However should you? The response is frequently no. Consider the additional expense, danger, and the truth that these applications will have value for a lot longer than many predicted.A study from application modernization company Advanced found that digital transformation is normally a top priority.

However, that often does not suggest the end for the mainframe. Indeed, only 6%of participants thought alternative innovations would change the mainframe soon. More than half of the business( 52% )plan to maintain or grow their dependency on mainframes. Additionally, half of respondents said mainframes are their favored platform for core applications (56 %). Coexistence is key I’ve always seen an integration and coexistence policy as a much better path, depending on how an enterprise uses the mainframe. Even with the explosive interest in generative AI where the mainframe will not be a favored platform (see the very same report ), mainframes become a main server of training data. They often have historic data that goes back 50 years. That’s indispensable for developing large language models, which must learn from old in addition to new information. I don’t indicate that we need to prefer a mainframe platform over any other platform; it should be relatively thought about– as all platform alternatives should be. Sometimes the cloud will be a better host, sometimes edge computing, and in some cases

, mainframes will continue to supply value. This” it depends “reaction drives everybody nuts, but it is generally the proper answer to these problems.This method develops a digital environment of many different platforms, all of which are the best platforms for the particular use cases. Hence, we also require to improve at handling intricacy and heterogeneity, which enterprises are not standing out at today. Enterprises are not able to discover value

in cloud release due to excessive functional intricacy and no finops oversight. Whether you use mainframes or not, you require to resolve that problem.I’m not advocating for mainframe platforms. They include problems, consisting of the huge one that mainframe designers and operators are retiring, and there is a shortage of mainframe talent. Numerous younger IT pros are not attracted to the mainframe space due to its absence of”coolness. “Nevertheless, those who comprehend mainframes and cloud-based platforms remain in high need, generally commanding salaries 20%-30%above their peers. Even cloud designers who understand how to interact with mainframes are frequently paid a premium. Are you noticing a pattern? I’m a pragmatist. We will use the platforms that can return the most worth to business. I

do not care what that is if it is the most enhanced solution. That must be an architect’s main objective. Copyright © 2024 IDG Communications, Inc. Source

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