The proliferation of AI in cloud computing is empowering cloud practitioners to provide more value with less resources.

Drew Firment, Chief Cloud Strategist, Pluralsight

August 3, 2023

4 Min Read
Robot holding a cloud
Panther Media GmbH via Alamy Stock

At its core, the goal of cloud computing is to help organizations drive customer value. With many companies still struggling to tie cloud strategy to organizational outcomes, however, it’s not uncommon to get bogged down in the weeds of cloud consumption and lose sight of value creation. But cloud computing isn’t a science project -- you need to fall in love with solving the problem, not just achieving the solution for a good grade.

Of course, this is easier said than done for cloud practitioners. With the advent of DevOps shifting more responsibility to cloud practitioners than ever before, the job now requires a well-rounded, broad scope of responsibilities spanning development, operations, ethics, budgeting and beyond.

Cloud practitioners help grease the skids for innovation within an organization, but it’s often difficult to leave room for inventive thinking when dealing with a high volume of work. Luckily, the proliferation of artificial intelligence (AI) within the cloud is serving as an accelerator helping organizations deliver on their promise to truly benefit the customer.

AI puts a stethoscope to the value pipeline, identifying opportunities to build quality in from the onset, eliminate waste, and do more with less. When used well, the technology represents the next generation of value creation and can help organizations shift their cloud computing efforts away from consumption and towards creation.

How Cloud Practitioners Can Leverage AI

The application of AI technology within cloud computing will continue to evolve, but below are a few examples of how it could transform the daily roles of cloud practitioners.

Infrastructure Coding: In the same way that generative AI tools can create a website, they can be utilized to help code the fundamentals of cloud infrastructure. Building these basics takes up roughly 80% of a cloud practitioner's time, leaving only 20% to focus on the fit and finish. By shifting the labor of creating these basic elements of cloud infrastructure from humans to AI, cloud practitioners can spend more time adding value specific to their organization and customers’ needs.

Cost Considerations: Many organizations today are struggling with the consumption of cloud services rather than their optimization. And as many businesses grapple with a challenging economic climate, cloud practitioners must take tight budgets into consideration more than ever before. AI could help these practitioners by building infrastructures optimized for specific attributes as inputted by the user, such as cost or speed.

Strategic Decision Making: AI has the power to not only augment labor, but actually help cloud practitioners make smarter decisions. From a security perspective, identifying data anomalies in the cloud is a great use case example. AI can help monitor cloud environments for security issues and then proactively make recommendations on how to better build and operate to mitigate risk and avoid catastrophe.

It’s important to note that the goal of AI is not to replace cloud practitioners. Cloud computing came along to help with what Jeff Bezos coined as the “undifferentiated heavy lifting” of data centers—meaning that the customer doesn’t care what data center you’re using, they care about the value you’re bringing them. Your back-end technical operations are irrelevant to them if they don’t result in competitive advantage. The same applies to the cloud.

Now, AI can help cloud practitioners implement that same undifferentiated heavy lifting in the cloud. This allows them to move further up the stack, much closer to customer problems, and focus on driving value creation instead of consumption. 

As AI and the Cloud Evolve, So Must Skill Sets

There’s a lot of pressure on cloud practitioners today to make things faster, less expensive, and more secure. That being said, cloud practitioners shouldn’t be blinded by bright and shiny objects like AI. While it’s important to have pioneers investigating edge cases and keeping a pulse on the market, cloud practitioners must master delivering value on the basics first. You have to understand the fundamentals of cloud computing to take advantage of AI, and whiletechnologists may have significant experience in the cloud, the technology changes so quickly that even experts need continuous education to help manage and optimize the environments they helped build.

Perpetual learning is a part of the job, not a luxury. We’re still largely in the exploratory stages of AI, so cloud practitioners should actively look for opportunities to explore it. Set aside an hour or two per week to read an article, take an online course, or roll your sleeves up and try something hands-on. AI won’t transform cloud computing overnight, so allocating time to investigate and experiment will help flex that muscle so you’re ready for new applications as they arise. In time, AI will help put innovation back in the hands of practitioners, empowering them to move up the stack towards customer problems and drive the shift from consumption to customer value creation.

About the Author(s)

Drew Firment

Chief Cloud Strategist, Pluralsight, Pluralsight

Drew Firment is Chief Cloud Strategist at Pluralsight. He works closely with business and technology leaders to accelerate cloud adoption by migrating talent to the cloud. Drew was previously Director of Cloud Engineering at Capital One where he led enterprise cloud operations within their Cloud Center of Excellence and migrated the early adopters of Amazon Web Services (AWS) into production. He founded Capital One's cloud engineering college that drove a large-scale talent transformation and earned a patent for measuring cloud adoption and maturity. Drew is recognized by Amazon as an AWS Community Hero for his ongoing efforts to build inclusive and sustainable learning communities.

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