Generative AI may displace traditional cloud development

With the explosion of interest (and money) in generative AI, what will be left for traditional cloud service development and enhancement that companies need?

Interest in GenAI may displace traditional cloud services development
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Cloud computing conference season is here, and the theme is clear. Conferences are not focusing on general cloud computing services, such as storage, compute, security, and databases. Instead, they have become generative AI conferences . 

Please don’t get me wrong—I’m all in on generative AI and its ability to be a true force multiplier for many enterprises. Indeed, I’ve been focused on that emerging reality for a long time. However, I’m also a pragmatist, and I understand that concentrating on one area means they are not paying attention to what many are beginning to call “legacy cloud services.”

Cloud computing companies only have a limited number of resources to spend on technology R&D. It’s clear that a lot of money has been directed to generative AI in cloud systems. Thus, it’s easy to assume that those resources will be moved from traditional cloud services.

Of course, I’m not seeing what’s happening in development meetings and scrums. However, I’ve been a technology CTO for most of my career. I understand resources are finite and increasing spending on one area means reducing spending on others, even if overall R&D money increases.

Companies playing catch-up 

The tech press would lead you to believe that all enterprises are led by innovative technology leaders chasing the latest technology trend, which is now generative AI. Most companies leveraging cloud computing are still focused on just getting their current pipeline of migrated and net-new systems up and running in the cloud. They have not yet begun to consider what to do with generative AI—or serverless and containers, for that matter.

Many enterprises still depend on traditional cloud services. They are likely to suffer if providers slow down on evolving and improving those services due to a redirection to generative AI. What’s more, public cloud conferences, or any technology conference for that matter, will be a blast of generative AI use cases and product announcements rather than improvements to storage, compute, databases, security, operations, etc. Many companies have a few current generative AI projects going, but leaders are largely focused on keeping their business systems running well on public cloud providers where they are at the mercy of how the providers evolve their cloud computing platforms. 

What are enterprises to do?

Let’s say your company is not yet all in on generative AI, not because you don’t want to be, but because you’re focused on just getting your systems on the cloud and working well, hopefully in a cost-optimized way. Generative AI is a long way off, but you’ve noticed that your cloud provider’s development and support resources are focused there and not as much on the more traditional services you depend on. What can you do about this trend that could affect you negatively?

This is one of the downsides of using OPS (other people’s servers). You have some control as a customer, but ultimately, they are going to evolve the platform as they see fit and as they perceive the market. However, you can become the squeaky wheel if you can point to incidents where you’ve noticed lagging support and innovation. They do listen to that input, and if enough of their customers are calling them out, they will redirect resources. After all, they want to keep you as a customer and grow a happy customer base.

Before a bunch of people go off and claim that Linthicum is not down with generative AI, that is not the case at all. Put to proper use, it’s highly effective, and I think is game-changing in many instances. I have a course on it and write about it all the time.

However, I also have empathy for the rank-and-file tech worker just trying to keep systems working in the cloud. They need ongoing support no matter where this technology moves. They are foundational to the success of cloud and generative AI on the cloud. Let’s not forget that.

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