Tag Archives: Mist

Juniper Mist roadmap includes SD-WAN, security integrations

Juniper Networks plans to broaden the reach of its cloud-based Mist AI engine from access points and switches to security and SD-WAN products on the wired and wireless LAN.

The vendorĀ plans to finish by the middle of next year integrations between Juniper Mist and cloud-based versions of Sky Advanced Threat Prevention (ATP) and Contrail Service Orchestration (CSO). The former is Juniper’s malware detection service, and the latter is the management software for the company’s Contrail SD-WAN.

“[The integration] is something which has just started, so it’s beyond the design board,” said Sujai Hajela, who heads the Juniper company Mist. Hajela was CEO of Mist before Juniper acquired it this year.

Juniper bought Mist in an attempt to catch up with Cisco and Aruba, a Hewlett Packard Enterprise company, in the wired and wireless LAN market. Both companies are market leaders, according to Gartner’s latest Magic Quadrant report.

Before Mist, Juniper partnered with other vendors to combine wireless LAN technology with its campus switches. Today, Juniper has a wired and wireless portfolio with cloud-based analytics and management tools competitive with products from Cisco and Aruba. The latter two vendors introduced their cloud offerings in June.

Juniper Mist integration use cases

Hajela expects to formally release the Mist, CSO and Sky ATP integrations by early in the first half of 2020. At that time, the Mist AI engine will provide correlations on data drawn from access points (APs), Juniper’s EX campus switches, Contrail SD-WAN and Sky ATP.

The product integrations will let Mist’s AI engine solve a broader set of network problems on Juniper-based networks. Instead of stopping at APs and EX switches, the software could discover other bottlenecks, such as congestion on a LAN circuit managed through the Contrail SD-WAN.

With Sky ATP data, Mist could identify devices on the network that are infected with malware, giving IT staff the option of quarantining the group or booting them off the grid.

Pricing

Juniper plans to offer future Mist AI capabilities through a tiered pricing model. A standard tier, for example, would provide state information on network operations while a higher-priced tier would include advanced remediation of problems. Another level could consist of location-based services for retailers or asset management in a hospital.

“We’re going to provide you with a single, full vertical stack of software, and [let] you decide,” Hajela said during a recent interview.

Vendors focusing on installed base

Juniper’s Mist acquisition gives the vendor a wireless product it can sell to companies using the vendor’s networking gear. In 2018, Juniper ranked sixth in the global market for campus switching, according to Gartner.

However, some Juniper customers are keeping an open mind when it comes to their wireless LAN. The University of Washington is watching all the leading networking vendors as it draws up plans to transition to next-generation wireless technology, particularly Wi-Fi 6 and 5G.

The emerging technologies are disruptive enough to require significant changes to Washington’s campus network. “There’s just a huge point of change — of brand-new architectures — happening in the next year,” said David Morton, director of networks and telecommunications at the school.

Today, Washington’s wireless LAN comprises between 17,000 and 18,000 Aruba APs. The university manages the network with HPE and Aruba software and runs the campus’s wired network on Juniper switches.

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Mist automates WLAN monitoring with new AI features

Mist Systems announced this week that its Marvis virtual network assistant now understands how to respond to hundreds of inquiries related to wireless LAN performance. And, in some cases, it can detect anomalies in those networks before they cause problems for end users.

IT administrators can ask Marvis questions about the performance of wireless networks — and the devices connected to it — using natural language commands, such as, “What’s wrong with John’s laptop?” The vendor said the technology helps customers identify client-level problems, rather than just network-wide trends.

Marvis could only handle roughly a dozen basic questions at launch in February. But Mist’s machine learning platform has used data from customers that have started using the product to improve Marvis’ natural language processing (NLP) skills for WLAN monitoring. Marvis can now field hundreds of queries, with less specificity required in asking each question.

Mist also announced an anomaly detection feature for Marvis that uses deep learning to determine when a wireless network is starting to behave abnormally, potentially flagging issues before they happen. Using the product’s APIs, IT departments can integrate Marvis with their help desk software to set up automatic alerts.

Mist has a robust platform for network management, and the advancements announced this week represent “solid steps forward for the company and the industry,” said Brandon Butler, analyst at IDC.

Cisco and Aruba Networks, a subsidiary of Hewlett Packard Enterprise, have also been investing in new technologies for automated WLAN monitoring and management, Butler said.

“Mist has taken a unique approach in the market with its focusing on NLP capabilities to provide users an intuitive way of interfacing with the management platform,” Butler said. “It is one of many companies … that are building up their anomaly detection and auto-remediation capabilities using machine learning capabilities.”

Applying AI to radio resource management

The original promise of radio resource management (RRM), which has been around for 15 years, was the service would detect noise and interference in wireless networks and adjust access points and channels accordingly, said Jeff Aaron, vice president of marketing at Mist, based in Cupertino, Calif.

“The problem is it’s never really worked that way,” Aaron said. “RRM has never been real-time; it’s usually done at night, because it doesn’t really have the level of data you need to make the decision.”

Now, Mist has revamped its RRM service using AI, so it can monitor the coverage, capacity, throughput and performance of Wi-Fi networks on a per-user basis. The service makes automatic changes and quantifies what impact — positive or negative — those changes have on end users.

Mist has RRM in its flagship product for WLAN monitoring and management, Wi-Fi Assurance.

Service-level expectations for WAN performance

Mist will now let customers establish and enforce service-level expectations (SLEs) for WAN performance. The agreements will help Mist customers track the impact of latency, jitter and packet loss on end users.

The release of SLEs for the WAN comes as Mist pursues partnerships with Juniper and VMware to reduce friction between the performance and user experience of the WLAN and the WAN.

Mist also lets customers set service levels for Wi-Fi performance based on metrics that include capacity, coverage, throughput, latency, access point uptime and roaming.