How cloud computing will evolve from hybrid to edge to AI-powered

Taking cloud computing to the next level will require Artificial Intelligence (AI) to play a big role in its work.

According to the World Meteorological Organization (WMO), there are ten basic types of clouds in all sorts of varieties. In today’s world, tech clouds aren’t all in data centres any more. Instead, many live entirely in private installations.

Since cloud computing has taken a tremendous leap forward in private premises installations, many organisations have experienced a dramatic increase and growth in digital information and e-commerce demands.

So, what does the future of cloud computing look like, and how will AI play a role in its development?

 

Cloud computing is evolving

On-demand, scalable, meterable, centrally managed computing infrastructure works. From startups to giant companies, it fits a wide range of business models. That’s why hybrid and multi-cloud are becoming so popular. Some applications work great in a public cloud, but other applications, usually due to latency, governance, or security issues, should be on-premises. Due to the fact that you can’t always count on one vendor to deliver a solution, multi-cloud is becoming more and more popular.

Several core business needs can be met by multi-cloud. It prevents single-vendor lock-in and avoids the huge costs that come with switching vendors. It lets you fail-over if one vendor has a problem or shuts down, and it allows IT operators to pick vendors that match their workloads.

While multi-cloud is usually defined as many clouds across vendors, you can also think of it as hybrid cloud. Depending on your needs, you might have both public and on-premise cloud services. There’s a good chance that multi-hybrid cloud will become more common in the near future.

These new fully hybrid cloud operations all benefit from scalability, meterability, manageability, and on-demandability, no matter how they’re distributed. As a result, you can adapt to constantly changing requirements while maintaining data control.
There’s also going to be a lot of growth in serverless computing, where the unit of measurement isn’t a whole server, but a workload, module, or application. With serverless, you don’t need to spin up a full VM or even a container and the modules just run when they’re needed. When an application has a wide range of traffic loads, serverless can save money and manage loads better.

 

The role of edge computing and 5G

As we move forward, edge computing will become more prevalent. Devices on the edge will get a lot more powerful, but they’ll also be more demanding, requiring large amounts of data to be handled in real-time and shared across organisations.

It’s going to be more connected, and unattended devices will be more common. When they get smarter and more powerful (AI and machine learning will play a big part in this), they’ll be able to do more in places with no or intermittent connectivity, or when there’s extreme weather.

This is where 5G (and eventually 6G) comes in. There’s no better way to handle intermittent connections than 5G, which switches frequencies and beamforms to get to areas traditional cellular can’t. It’s also putting a lot more intelligence in the field, so edge devices will be able to communicate with “the mothership” much more quickly and with more responsiveness.

 

The growth of AI in cloud management

The complexity of cloud environments will make management harder. Here’s how AI can help:

  • AI can handle a lot of basic IT management tasks, like resource allocation and scaling. Anywhere there’s a script, there’s an AI. AI will get to the point where it’s easier to set up than a script.
  • AI can provide insights into network operations and customer behaviour that can improve reliability and highlight opportunities, whether it’s customer usage patterns, sentiment analysis, workload impacts, or many other areas of observation.
  • You can expect AI to provide front-end and even second-tier support via chat and email. Aside from putting users in the hands of machines, it also frees up human technicians to deal with tougher problems.
  • More and more cloud services are adding AI components as a value-add, like ChatGPT. We’re expecting this trend to continue with more ways that AI can streamline and assist humans.

Security is important, too. A cybersecurity skills shortage and ever-increasing threats make preventing and mitigating attacks a top corporate priority – but it’s also getting harder and harder. As attackers get more sophisticated, they’re more experienced at launching successful attacks. There are more points of failure and more points that attackers can exploit as complexity increases.

Whether it’s in motion or at rest, even small companies manage a lot of information. We’re talking terabytes, petabytes, and exabytes of data. Software is the only way to manage data of that volume, moving at high speed.However, regular programming and pattern identification won’t keep up with the rapid changes and growth in bad actors.

In this case, AI isn’t just nice to have. Businesses will need AI to protect them where nothing else can keep up.

 

Recent Posts