AI/ML, edge and serverless computing top priority list for the year ahead

In Red Hat’s 2022 Global Tech Outlook report, more organizations indicated they are considering or planning to use most types of emerging technology. Here, “emerging technologies” include leading innovations such as artificial intelligence and machine learning (AI/ML), internet of things (IoT), blockchain and edge.

From June through August 2021, we surveyed 1,341 information technology (IT) leaders and decision makers to learn about their digital transformation journeys, their IT and non-IT funding priorities for the coming year, and the types of infrastructure they’re using to run their applications.

Top emerging technology workloads

We asked study participants, “What emerging technology workloads are you most likely to consider using in the next 12 months (or are currently planning on using)?” Respondents were asked to select all answers that applied. Here’s what they had to say.

The results aren’t terribly different compared to last year’s survey. 

This year there continues to be a large and growing interest in AI/ML, with 53% of respondents saying that this is one of their top priorities in the coming year, up 3% from last year.

Similarly, 49% of organizations said that Internet of Things (IoT) is a top priority in 2022, which skyrockets to 61% if you consider IoT and edge together. Combined, this is 5% higher than last year’s totals.

What’s notable is that the largest year-to-year jump is in serverless, or Function-as-a-Service (FaaS) computing. Forty percent of respondents said this is one of their top priorities for the coming year, up 6% over our 2020 survey.

How Red Hat can help

Red Hat offers an array of tools and services that can help organizations succeed in their emerging technology initiatives, including AI/ML, edge and IoT, and serverless computing.

AI/ML

AI/ML is an important evolution in computer science and data processing that is being adopted across a wide swathe of modern industries as they undergo digital transformation. Faced with a massive and ever-expanding flood of data generated by modern IT infrastructure and devices, organizations are finding it increasingly difficult to collect, process and analyze.

This is where AI/ML comes in, giving organizations a way to extract value from the flood of data to deliver business insights, automate tasks and advance system capabilities.

You can build a hybrid cloud platform for AI/ML workloads using Red Hat products such as Red Hat Enterprise Linux (RHEL), Red Hat OpenShift and Red Hat Middleware. Additionally, Red Hat partner solutions can help you innovate more quickly. 

If you don’t want to roll out your own hybrid cloud, Red Hat OpenShift Data Science is a managed cloud service that gives data scientists and developers a way to rapidly develop, train, test and iterate on machine learning and deep learning models in a fully supported sandbox environment. It gives you the ability to quickly deploy an integrated set of open source and partner tools to perform AI/ML modeling without having to wait for infrastructure provisioning.

Red Hat Consulting is also available to help organizations meet challenges like the adoption of DevOps and ML best practices, and an AI/ML Red Hat Open Innovation Labs residency is also available to help you accelerate your data science initiatives.

Edge and IoT

The Internet of Things (IoT) is made up of smart devices connected to a network. IoT creates new opportunities to gather data in disparate physical locations, and is directly related to the concept of edge computing.

Edge computing is a distributed computing model in which data is captured, stored, processed and analyzed at or near the physical location where it is created. Pushing compute power out to these locations enables a number of application benefits, including decreased latency, better reliability, and the flexibility and scalability of hybrid cloud computing.

Edge computing improves speed and performance by eliminating the need to shuffle data back and forth across (sometimes slow and unreliable) network connections. Data can be processed and insights gained more quickly, particularly in locations with intermittent connectivity. Regulatory and compliance requirements are also simplified because data can be held or scrubbed on location, rather than being shipped unprocessed over the internet.

With so much added complexity, however, there are challenges to edge computing. The Red Hat Edge portfolio addresses by giving organizations a cohesive strategy for building and managing applications across hybrid, multi-cloud and edge locations.

The portfolio includes Red Hat Enterprise Linux, Red Hat OpenShift and Red Hat Ansible Automation Platform. Red Hat Consulting can conduct an Edge Platform Architecture Review and suggest how to use the portfolio to enhance or scale your edge solution. 

As with AI/ML, a Red Hat Innovation Labs residency is available where you can bring IT and operational technology (OT) teams together and develop collaborative approaches to building these complex edge systems.

Serverless computing and FaaS

Function-as-a-Service (FaaS) computing involves building and running applications that don’t require server management. Instead, applications are bundled as one or more functions, uploaded to a platform, and then automatically executed and scaled as needed. FaaS is a way to implement serverless computing.

Developers only have to deploy their applications, and don't have to worry about where they’re run, how they’re run, how the network is handled or any of that other stuff. There are still servers, of course, but they are abstracted away from app development, streamlining the application development process.

Red Hat OpenShift Serverless can be used to build, deploy and run event-driven applications that will start based on an event trigger and scale resources as needed. Backed by Knative, OpenShift Serverless applications can run anywhere Red Hat OpenShift is installed. 

Conclusion

If you’re among the industry leaders planning to deploy any of these emerging technologies in the year to come, Red Hat can help. Learn more about our product offerings, and make sure your teams have the skills they need to deploy emerging technologies through our training and certification programs.

Learn more

• Red Hat 2022 Global Tech Outlook report

• Red Hat Edge

• Red Hat Edge Validated Patterns

• AI/ML on OpenShift: How Red Hat can help you operationalize your models

• Why and When you need to consider OpenShift Serverless