VMware updated its SD-WAN offerings, including its new SD-WAN Client, to help IT teams reduce the operational burden of managing increasingly distributed environments.

Abe Ankumah, VP of product management for VMware SASE, said with applications, users, and workloads becoming more fragmented, the enterprise IT connectivity and security footprint is now “very diffused.” The SD-WAN Client aims to provide consistent connectivity, performance, and security capabilities to remote workers.

VMware acquired the team, products, and IP of Ananda Networks in order to "accelerate the development of the SD-WAN Client.” The new PC and mobile soft client will “leapfrog” legacy remote-access virtual private networks (VPNs) via a cloud-delivered approach, enabling the transition to zero trust.

The SD-WAN client “takes all the benefits” of VMware’s SD-WAN solution for an enterprise's branch office and “makes that ubiquitous," Ankumah said.

“What's powerful about this soft client that we're introducing is it’s delivered as-a-service. Traditional VPN has been something that enterprises have to manage and maintain with a VPN head end within the island data centers,” he aded. “This is basically managed as-a-service the same way that an SD-WAN solution within the enterprise branch is managed as-a-service.”

The soft client is available at launch for Windows, Mac, iOS, Android, and Linux.

VMware is also expanding its SD-WAN and secure access service edge (SASE) footprint by adding 16 new points-of-presence (PoPs), mainly across Asia-Pacific/Japan, Europe, Middle East, and Africa, and Latin America.

Ankumah said one "massive trend" across enterprises is the increasing migration of workloads to the cloud. But what he calls the "bigger sub trend" is the fact that organizations are now relying on multiple clouds, or the so called "multi-cloud movement."

While he said this migration is solving some "really critical business needs," it's also coming with a set of challenges that enterprise IT teams need to be prepared to address.

“This is the context within which we're focused on solving the myriad of problems that come with this evolving environment,” Ankumah told SDxCentral. “And these problems have everything to do with the fact that when it comes to accessing cloud and [software-as-a-service] applications, the model of connecting through your enterprise's own data center only to hairpin out to that SaaS application is highly inefficient.”

This traditional model results in poor application quality and experience, especially when the types of applications being used are increasingly real-time collaboration applications. "Where applications are hosted and where users are located just increases that surface area in terms of security attacks," Ankumah said.

He added, “We've now gone over 200 PoPs as part of our expansion, and this is with the intention of supporting increasingly global enterprises wherever users are working from."

VMware additionally announced enhanced artificial intelligence (AI) for IT operations – or AIOps – capabilities within VMware Edge Network Intelligence, which integrates with the vendor's SD-WAN Edge.

Ankumah noted that in addition to workloads moving to cloud, in certain verticals, "we're increasingly seeing a subset of applications moving into the edge – edge-native applications, whether it's in manufacturing, whether it's retail, moving into the far edge."

"Anyone who's had to manage a large, complex, IT environment will tell you that the key things that they want to do is be proactive," he said. "They want to know about issues before their users call them and complain. They want systems that can actually take corrective action and also point them to root cause to prevent a reoccurrence of these issues."

Ankumah explained IT teams have had to manage and monitor environments in a "siloed fashion," often relying on employee skill and expertise for troubleshooting with very little help from the infrastructure that is "actually delivering the services."

Integrating AIOps capabilities driven by AI and machine learning (ML) provides problem detection and automatic root cause analysis and remediation.

This is possible based on the billions of telemetry inputs VMware receives from its production environments on a daily basis, according to Ankumah, which is used to feed and train ML algorithms to auto-heal and auto-remediate "the classic and list of problems that AI teams are increasingly faced with."