The cloud solution team has an architect who has designed the target cloud solution or the selection and configuration of the different types of cloud technology—hopefully, while keeping the business requirements in mind. Unfortunately, in many cases, the solution looks like a who’s who of hyped technology, including serverless everything, edge computing using digital twins, containers, and container clusters all over the place. The fun really begins when all this technology turns into job descriptions and an army of retained and internal recruiters attempts to fill these roles.
Those of you who are out there looking for these skills understand that there are about 20 job reqs chasing a single qualified candidate. In some cases, it’s 50 to 1, with more jobs going unfilled, which delays cloud projects or, in some cases, cancels them outright.
In its “2021-2023 Emerging Technology Roadmap” based on surveys of 437 global firms, Gartner reported that IT executives see the talent shortage as the largest barrier to deploying emerging technologies, mostly cloud-based technologies such as databases, serverless, machine learning, containers, advanced storage, and analytics.
This is not new news, but what is news is the fact that many of these skills shortages may be self-inflicted wounds.
How? Many IT shops moving to cloud are overcomplicating the types of technologies they really need. They are using the 50 to 100 announcements from the annual hyperscaler conferences as shopping lists of technologies to deploy. In most of those cases, newer, hyped technologies may not be needed and are just complicating the proposed cloud solution, making hiring the skills you need almost impossible.
Take containers for instance. In many instances, they are justifiable considering that a distributed system is needed for a specific application and that some portability and clustered processing will be useful as well. Thus, architects push to containerize the applications by decoupling specific application functions and refactoring them as applications and data that exist within a container and perhaps a Kubernetes cluster of containers.
However, many applications of containers and container orchestration are a force fit. By using containers, the company is running up cost, complexity, and risk over a more conservative approach, such as lift and shift with some refactoring. Moreover, by using approaches and technologies that require skills that are more readily available, you’re able to hire and proceed with meeting the needs of the business faster, with less money and less operational complexity.
You might point out that in many instances newer technologies such as containers, AI, or serverless are needed. Of course. I’m not suggesting that we don’t use the weapons that we need to win. I’m suggesting that in many instances, the use of new technologies is not justified by the business case, and overkill runs up unnecessary costs and risk. We’ve all worked on projects where this is the case.
I’m now seeing cloud migration and net-new cloud-native projects stopped in their tracks due to the inability to hire the right skills based on the way that they defined the cloud solution. In many cases, we’re outsmarting ourselves.
David S. Linthicum is an internationally recognized industry expert and thought leader. His views are his own.
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