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Juniper Networks Expands AIOps Capabilities

Juniper Networks announced several new enhancements that make it even easier to deliver predictable, reliable and measurable user experiences from client to cloud.

By integrating ChatGPT with Marvis, a virtual network assistant (VNA) driven by Mist AI, Juniper customers and partners can now easily access public-facing knowledgebase information using ground-breaking Large Language Models (LLM).

In addition, new Marvis integrations with Zoom enable superior video conferencing experiences while significantly reducing troubleshooting costs. With these enhancements, plus a new Wi-Fi 6E access point, Juniper is expanding its AIOps offering.

“AI is the next step in automating tasks that typically require a human IT domain expert, improving how IT teams operate the network with AI-driven tools like Marvis and its conversational interface,” said Bob Friday, Chief AI Officer at Juniper Networks. “Juniper Mist has always been a pioneer in utilizing proven AIOps to deliver assured user experiences from client to cloud, and with these latest LLM enhancements, Marvis will provide even more actionable knowledge and be an even more valuable member of the IT team.”

The Marvis VNA and its conversational interface were first introduced on June 7, 2018, as an essential part of IT, delivering proactive troubleshooting, predictive actions and exceptional insight into user experience via natural language processing and understanding (NLP/NLU). This enabled Juniper customers to easily delve into the network, user and application experiences (in real time) via simple language queries.

With the recent launch of LLM tools like ChatGPT, Juniper has been able to expand the conversational interface (CI) capabilities of Marvis to deliver even more human-like conversational capabilities, particularly with respect to documentation and support issues. Specifically, Marvis now leverages a LLM API to respond to user queries for technical documentation and other publicly available historical knowledge base information. For example, customers can ask Marvis “What do the Access Point LED lights mean?” or “List steps to configure Juniper campus fabric” and receive an accurate and direct response in the typical ChatGPT style in addition to a list of relevant documents.

Juniper is also leveraging 3rd party user-experience data from the Zoom cloud. By joining gigabytes of user experience Zoom data with gigabytes of network feature data, Marvis now has a deep learning model that can accurately predict user experience performance, allowing Marvis to use advanced AI/ML explainability techniques to quickly identify the root cause of video conferencing problems. In addition to real-time proactive troubleshooting (and self-driving corrective actions, if possible), Marvis learns trends to quickly detect and correct anomalies as well as predict future issues. This insight gives IT teams an edge in reducing Zoom support tickets and the time to repair issues.

Users can now leverage the Marvis conversational interface to easily access Zoom data insights via simple language queries, like “What was wrong with John Smith’s Zoom call?” or “List users with a bad Zoom experience.”

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Juniper Networks Expands AIOps Capabilities

Juniper Networks announced several new enhancements that make it even easier to deliver predictable, reliable and measurable user experiences from client to cloud.

By integrating ChatGPT with Marvis, a virtual network assistant (VNA) driven by Mist AI, Juniper customers and partners can now easily access public-facing knowledgebase information using ground-breaking Large Language Models (LLM).

In addition, new Marvis integrations with Zoom enable superior video conferencing experiences while significantly reducing troubleshooting costs. With these enhancements, plus a new Wi-Fi 6E access point, Juniper is expanding its AIOps offering.

“AI is the next step in automating tasks that typically require a human IT domain expert, improving how IT teams operate the network with AI-driven tools like Marvis and its conversational interface,” said Bob Friday, Chief AI Officer at Juniper Networks. “Juniper Mist has always been a pioneer in utilizing proven AIOps to deliver assured user experiences from client to cloud, and with these latest LLM enhancements, Marvis will provide even more actionable knowledge and be an even more valuable member of the IT team.”

The Marvis VNA and its conversational interface were first introduced on June 7, 2018, as an essential part of IT, delivering proactive troubleshooting, predictive actions and exceptional insight into user experience via natural language processing and understanding (NLP/NLU). This enabled Juniper customers to easily delve into the network, user and application experiences (in real time) via simple language queries.

With the recent launch of LLM tools like ChatGPT, Juniper has been able to expand the conversational interface (CI) capabilities of Marvis to deliver even more human-like conversational capabilities, particularly with respect to documentation and support issues. Specifically, Marvis now leverages a LLM API to respond to user queries for technical documentation and other publicly available historical knowledge base information. For example, customers can ask Marvis “What do the Access Point LED lights mean?” or “List steps to configure Juniper campus fabric” and receive an accurate and direct response in the typical ChatGPT style in addition to a list of relevant documents.

Juniper is also leveraging 3rd party user-experience data from the Zoom cloud. By joining gigabytes of user experience Zoom data with gigabytes of network feature data, Marvis now has a deep learning model that can accurately predict user experience performance, allowing Marvis to use advanced AI/ML explainability techniques to quickly identify the root cause of video conferencing problems. In addition to real-time proactive troubleshooting (and self-driving corrective actions, if possible), Marvis learns trends to quickly detect and correct anomalies as well as predict future issues. This insight gives IT teams an edge in reducing Zoom support tickets and the time to repair issues.

Users can now leverage the Marvis conversational interface to easily access Zoom data insights via simple language queries, like “What was wrong with John Smith’s Zoom call?” or “List users with a bad Zoom experience.”

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E-commerce is set to skyrocket with a 9% rise over the next few years ... To thrive in this competitive environment, retailers must identify digital resilience as their top priority. In a world where savvy shoppers expect 24/7 access to online deals and experiences, any unexpected downtime to digital services can lead to significant financial losses, damage to brand reputation, abandoned carts with designer shoes, and additional issues ...

Efficiency is a highly-desirable objective in business ... We're seeing this scenario play out in enterprises around the world as they continue to struggle with infrastructures and remote work models with an eye toward operational efficiencies. In contrast to that goal, a recent Broadcom survey of global IT and network professionals found widespread adoption of these strategies is making the network more complex and hampering observability, leading to uptime, performance and security issues. Let's look more closely at these challenges ...

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AWS is a cloud-based computing platform known for its reliability, scalability, and flexibility. However, as helpful as its comprehensive infrastructure is, disparate elements and numerous siloed components make it difficult for admins to visualize the cloud performance in detail. It requires meticulous monitoring techniques and deep visibility to understand cloud performance and analyze operational efficiency in detail to ensure seamless cloud operations ...

Imagine a future where software, once a complex obstacle, becomes a natural extension of daily workflow — an intuitive, seamless experience that maximizes productivity and efficiency. This future is no longer a distant vision but a reality being crafted by the transformative power of Artificial Intelligence ...

Enterprise data sprawl already challenges companies' ability to protect and back up their data. Much of this information is never fully secured, leaving organizations vulnerable. Now, as GenAI platforms emerge as yet another environment where enterprise data is consumed, transformed, and created, this fragmentation is set to intensify ...

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