While a few large companies like Johnson & Johnson got the rid of all their Mainframe-based applications and expect to run more applications in the Cloud than they currently do on their own infrastructure, the great majority of the Forbes Global 2000 organizations are still stuck at the beginning of the journey. If these large shops have initiated their move to the Cloud to reduce infrastructure costs, they’ll soon be confronted with technological, cultural and psychological hurdles which may hinder them to take full advantage – cost reduction, but also business value – of the Cloud. In this blog post series, we detail how to “lift & extend” and the pragmatic keys to establish a virtuous circle in your Cloud adoption strategy.
As we explained earlier in this post series, moving your application landscape to a Cloud-based infrastructure can act as an immediate cost reduction factor, liberating IT resources, even with a pure IaaS “lift & shift”. The CapEx portion of the IT budget decreases in favor of the OpEx that globally creates new investment opportunities.
We also described why a containerization of the application landscape (CaaS) is the compelling event that maximizes the Cloud economics and how it paves the road for a tighter conversation between development teams and IT and introduces an organizational disruption where Dev & Ops are part of the same application team that builds, deploys, delivers and operates applications.
Because not all applications necessarily require more intelligence, the PaaS migration of the application landscape is not a 1:1 effort. The reason why you’ll need to constitute a comprehensive, fact-based and systematic evaluation of your application landscape in order to know whether each application is a better candidate for IaaS, PaaS, CaaS, SaaS.
The cost reduction enabled by IaaS and the containerization of 80% of the application portfolio will finance the PaaS migration effort of the other 20%. These core apps that will dramatically increase the business value of your systems by adding big compute, machine learning, IoT, speech recognition, high scalability … to your apps.
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