Demonstrating Keysight’s AI Fabric Test Methodology

Event: AI Infrastructure Field Day 2

Appearance: Keysight Presents at AI Infrastructure Field Day 2

Company: Keysight Technologies

Video Links:

Personnel: Alex Bortok

This session provides an overview of the Keysight AI fabric test methodology, demonstrating key findings and improvements achieved through automated testing and the search for optimal configuration parameters. Alex Bortek, Lead Product Manager at Keysight Technologies, introduces the Keysight AI fabric test methodology using the Kai Data Center Builder product. The methodology guides users through the phases of designing and building an AI fabric, emphasizing the importance of topology selection, collective operation algorithms, performance isolation, load balancing, and congestion control. The methodology and related white papers are available for download via a QR code or the link below

The presentation delves into key terminology, including collective operations (broadcast, all-reduce, all-to-all), ranks, collective size, and data size. Metrics such as collective completion time, algorithm bandwidth, and bus bandwidth are defined and used to measure performance. Alex explains how bus bandwidth is a beneficial metric as it removes the number of GPUs from the equation and specifies the limiting factor that defines how long the collective operation will take. A testbed comprising four 800-Gbps port speed switches is described, emulating 16 GPUs/network cards running at 400 Gbps to assess fabric performance.

A demonstration highlights the impact of congestion control on network performance. By comparing scenarios with and without congestion control enabled, the presentation illustrates how fine-tuning DCQCN parameters can optimize bandwidth utilization and reduce congestion. The speaker uses the tool to showcase testing of different settings on the fabric to achieve the optimal configuration. The presentation concludes by mentioning Ultra Ethernet consortium membership and upcoming webinars detailing Keysight’s innovations in AI.


Maximizing the Performance of AI Backend Fabric with Keysight

Event: AI Infrastructure Field Day 2

Appearance: Keysight Presents at AI Infrastructure Field Day 2

Company: Keysight Technologies

Video Links:

Personnel: Alex Bortok

This session provides an overview of the Keysight AI (KAI) Data Center Builder solution and how it supports each phase of AI data center design and deployment with actionable data to improve performance and increase the reliability of AI clusters. The presentation explains how KAI Data Center Builder helps streamline the design process, optimizes resource allocation, and enhances the overall efficiency and stability of AI infrastructures to achieve superior performance and reliability. The discussion focuses on the performance of backend fabrics within AI clusters, highlighting Keysight’s expertise in creating solutions for companies that build various products, including microchips, smartphones, routers, 5G towers, and AI data centers.

Alex Bortok, Lead Product Manager for AI Data Center Solutions at Keysight Technologies, introduces the KAI Data Center Builder product, which is designed to test backend networks GPUs use for data exchange, especially during model training and inference. He distinguishes it from front-end network testing solutions like Keysight Sideperf. The presentation covers the capabilities of the KAI Data Center Builder in emulating AI workloads, benchmarking network infrastructure performance, fine-tuning performance, reproducing production issues, and planning for new designs and topologies. The product emulates the behavior of real GPU servers, reducing the need to purchase them for lab testing.

The presentation also highlights two key KAI Data Center Builder applications: Collective Benchmarks and Workload Emulation. Collective Benchmarks allows users to zoom in on a single transaction between thousands of GPUs, which allows network and system parameters to be fine-tuned. Workload Emulation considers that GPUs not only move data but also compute, and that there is a dependency between how much data you compute and how much data you will move. It is noted that Kai Data Center Builder is a part of the larger Kai Solution Portfolio. The presentation concludes by leading into a KAI Data Center Builder demonstration.


Building Trust at Scale. How Crusoe Validates Network Infrastructure for AI Workloads with Keysight

Event: AI Infrastructure Field Day 2

Appearance: Keysight Presents at AI Infrastructure Field Day 2

Company: Keysight Technologies

Video Links:

Personnel: Gavin McKee

In this session, Crusoe shares how they are actively testing frontend networks and inter-VM/host data transfers that feed their GPU clusters. By validating the performance, reliability, and scalability of its infrastructure early, Crusoe aims to identify and resolve issues internally, minimizing the chance that end customers will discover them first. This is a differentiator for them, which enables a more robust, production-ready AI platform. Crusoe is a vertically aligned AI infrastructure company powered by sustainable energy sources, including wind, solar, and geothermal. They build AI data centers, with a large project underway in Abilene, Texas.

Crusoe’s AI cloud platform offers infrastructure as a service, where customers consume GPU supercomputing via virtualized machines. They also provide managed AI solutions like AI as a service, inference, and workloads. Their mission is to build the world’s favorite AI cloud, purpose-built for AI, with enterprise-scale infrastructure. The company focuses on the design and engineering of data center networks, software-defined networking, and GPU-to-GPU fabrics, all optimized using NVIDIA reference architectures. They emphasize customer support, offering 24/7 assistance to address GPU systems’ complexities and potential issues.

Crusoe partners with Keysight to conduct rigorous testing to ensure optimal performance and stability, particularly focusing on stateful traffic and high connection rates. They simulate various workloads to stress the system and identify breaking points, provide deterministic performance, and prevent noisy neighbor issues in their multi-tenant environment. This proactive approach allows Crusoe to understand the system’s limits and provide transparent performance data to customers, ensuring a world-class service and preventing users from becoming beta testers. They use Cyperf as a traffic generator to understand the behavior of open-source OVS  and NVIDIA’s stack to optimize testing. Plans include incorporating Blackwell platforms, advancing telemetry and monitoring, and focusing on storage optimization, scale, and security.


Validating Frontend Networks to Optimize and Secure Low- Latency LLM Data Flow with Keysight

Event: AI Infrastructure Field Day 2

Appearance: Keysight Presents at AI Infrastructure Field Day 2

Company: Keysight Technologies

Video Links:

Personnel: Amritam Putatunda

As large language models scale, new challenges emerge – not only in maximizing GPU performance but also in validating the infrastructure that fuels the data pipeline used for training. On the front end, this includes securely ingesting user data from distributed cloud and customer environments into centralized AI data centers and ensuring high-speed, low-latency data transfer between VMs and hosts within the data centers. This session focuses on testing products that evaluate the performance, scalability, latency, reliability, and security of critical data pathways.

The presentation addresses the critical role of front-end networks in ensuring efficient data flow to data-hungry GPUs for LLM training. It highlights the two primary data movement patterns: north-south, involving data ingestion from sources like cloud providers and user environments, and east-west, which focuses on data transfer between virtual machines within the data center. Each of these patterns has unique testing demands, with east-west requiring ultra-low latency and high line rates, while north-south necessitates a balance of minimal latency and strong security to protect user data in transit.

Keysight’s solution, Cyperf, is a software-based traffic generator designed to emulate various application traffic types and measure key performance indicators like bandwidth, latency, connections per second, and security. Cyperf ensures that GPUs receive data with low latency, security, and at the promised rate of the network infrastructure. The presenter emphasized the importance of thoroughly testing all layers of the OSI model, especially the application layer, to avoid relying on end-users as beta testers. The presenter lauded Crusoe for proactively testing their front-end infrastructure to ensure optimal performance.


Rethinking the Role of Servers, a Tech Field Day Delegate Roundtable

Event: Next Gen HPE ProLiant Compute Deep Dive

Appearance: Tech Field Day Delegate Roundtable on HPE ProLiant

Company: HPE

Video Links:

Personnel: Stephen Foskett

The Tech Field Day delegate panel considers the day’s presentations, reacting to the major themes presented. At the HPE-hosted Deep Dive event on the next-generation ProLiant compute solutions, industry thought leaders convened to assess the wider implications of what HPE shared. The dialogue focused on how compute hardware has evolved well beyond being a commodity, and has entered a new phase where intelligent, use-case-driven design is vital. With AI moving to the forefront of enterprise workloads, the discussions centered on how organizations will need integrated solutions that blend hardware, security, platform management, and workload-specific optimizations to truly enable end-user outcomes.

As the panel discussed, HPE’s approach highlights the complex interplay between hardware and software, particularly in the era of AI. The panelists noted that hardware advancement, especially with alternating compute types such as GPUs and ASICs, is now often ahead of software capabilities, yet both components must evolve in tandem. HPE’s GreenLake and iLO7 developments were praised for enabling robust, secure management in edge scenarios—an increasingly vital requirement as compute resources expand beyond centralized data centers. The conversation also explored how AI’s success depends not just on computation, but on managing the full stack of requirements, from data readiness to inference optimization, regulatory compliance, and end-to-end security.

Security emerged as a principal theme, with HPE lauded for its security-first design strategy that extends from silicon customization to logistics, installation, and system management. Delegates emphasized the value of HPE’s holistic, layered ecosystem that aims to ease integration for customers and deliver complete, outcome-driven stacks—including partnerships with NVIDIA and others. Rather than simply selling servers, HPE is offering a sophisticated infrastructure platform tailored to diverse workloads and business contexts. The result is a coherent compute strategy that balances performance, power, cooling, management, and compliance within a rapidly evolving IT landscape, making HPE’s Gen12 ProLiant portfolio not just relevant but essential for forward-looking enterprises.


HPE ProLiant Compute AI Portfolio and Solutions

Event: Next Gen HPE ProLiant Compute Deep Dive

Appearance: AI and Computer Vision on HPE ProLiant

Company: HPE

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Personnel: Scott Shaffer, Viabhav Rastogi

The HPE ProLiant team presents their AI-ready server portfolio: PCAI, DL145, DL380a, and DL384. The team also discusses computer vision use cases with customers and considers compute as a foundation for AI. Presented by Scott Shaffer, CTO, HPE Compute, and Vaibhav Rastogi, Compute Solutions Manager. The presentation begins by emphasizing real-world enterprise applications of AI where HPE is helping customers unlock business value. Common use cases include predictive maintenance, self-checkout in retail, and fraud detection in finance. HPE distinguishes itself with expertise in both HPC and AI, leveraging know-how from Cray and SGI to meet infrastructure demands. The presenters note that while many AI proof-of-concepts fail to move into production, HPE’s customers see better success due to the company’s experience, comprehensive offerings, and ability to create full-stack, optimized solutions, from training to inference.

HPE’s AI portfolio is divided across edge to core implementations, with the ProLiant Gen 12 server line tailored to enterprise inferencing needs and private AI deployments. Servers such as the DL380a and DL384 are equipped to handle modern GPUs and versatile AI workloads. The new Grace Hopper platform is highlighted for its extreme performance through CPU-GPU integration via high-speed NVLink. HPE’s Private Cloud AI is introduced as an all-in-one as-a-service solution, integrating hardware, software, and networking to simplify AI adoption. Designed for flexibility, it supports small workloads to larger inference clusters and is model-agnostic, catering to diverse customer needs ranging from retail experiences to healthcare diagnostics. The platform also includes MLPerf benchmark results, showcasing its optimization and performance across popular AI models like LLaMA and Mistral.

Customer stories reinforce the practicality and adaptability of HPE’s AI solutions. Examples include a Portuguese firm enabling cashier-less shopping using HPE ProLiant servers, Bosch using digital twins and real-time sensor analytics for turbine maintenance, and a school district leveraging computer vision for security across 3,000 cameras. These scenarios demonstrate the edge-to-cloud continuum and the shift from generic AI approaches to complete business-driven workflows. HPE positions itself not just as a provider of compute but as a partner offering validated solutions with ISVs, robust security measures, edge capabilities, and AI-specific services. Ultimately, HPE aims to make AI a manageable, performant workload by applying their legacy of enterprise computing, building optimized, reliable infrastructure platforms amidst the evolving AI landscape.


HPE ProLiant Compute Cooling Technologies

Event: Next Gen HPE ProLiant Compute Deep Dive

Appearance: HPE ProLiant Liquid Cooling

Company: HPE

Video Links:

Personnel: Keith Sauer, Pranay Mahendra

The HPE ProLiant liquid cooling team presents a “show and tell” session focused on cooling innovation, direct liquid cooling (DLC) and closed-loop liquid cooling (CLLC). Presented by Pranay Mahendra, Mechanical and Thermal Engineer, and Keith Sauer, Mechanical Engineering Manager.

During the presentation, Keith Sauer first explains the integral work of the Houston-based engineering team responsible for designing the mechanical, thermal, tooling, and packaging elements of HPE ProLiant servers. He emphasizes how air cooling used to be treated as an afterthought, with teams historically relying on incremental improvements to manage higher thermal outputs. However, with rising power densities in hardware, traditional air cooling solutions have reached their limits. Pranay Mahendra picks up from this point to delve into the transition towards liquid cooling, highlighting HPE’s development of innovative closed-loop liquid cooling solutions that fit compact server formats like 1U, as well as direct liquid cooling systems designed to integrate into existing data centers.

Mahendra details how the closed-loop system involves internal radiators, pumps, and cold plates enclosed within the server, providing enhanced heat dissipation without needing external liquid infrastructure. These are capable of cooling up to 400–450 watts compared to traditional air-cooled configurations. The direct liquid cooling (DLC) solution, on the other hand, ties into facility-level liquid systems and offers even higher performance with significant processor temperature reduction, enabling sustained turbo modes and higher efficiency. He addresses practical concerns like leakage, which is mitigated through detection mechanisms and safety shutdowns, and stresses the cooling technology’s lifecycle and serviceability.

The session concludes with a broader discussion on the economics and deployment considerations of liquid cooling. The speakers underscore that while DLC offers compelling advantages for dense racks and high-power workloads, many data centers still operate below 29 kilowatts per rack and may prefer expanding air-cooling solutions. They compare different approaches—1U vs. 2U servers, air vs. liquid cooling—by examining cooling power, density, and total cost of ownership. Ultimately, HPE recommends careful evaluation of power, performance, and sustainability needs when considering a move to liquid cooling, emphasizing that air cooling remains viable depending on hardware configurations and customer infrastructure maturity.


HPE Server Management with Compute Ops Management and iLO

Event: Next Gen HPE ProLiant Compute Deep Dive

Appearance: Server Management with HPE iLO and OneView

Company: HPE

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Personnel: Andrew Elisavetsky, Chris Bradley, Chris Powell

The HPE ProLiant platform includes industry-leading management capabilities in iLO, including OneView and COM. This session features demonstrations of these features and functions. Presented by Andrew Elisavetsky, Technical Enablement, Chris Bradley, Technical Enablement Manager, and Chris Powell, Technical Enablement.

Chris Powell and Andrew Elisavetsky began the session by demonstrating the new capabilities of HPE’s iLO 7 management interface for Gen 12 servers and its integration with the Compute Ops Management (COM) platform. Powell highlighted how iLO 7 has been significantly revamped for intuitive usability, allowing users to manage servers from a geographic overview without relying on traditional inventory spreadsheets. They emphasized the benefits of connecting through the GreenLake platform, which enhances system visibility and control across edge and data center environments. Additionally, Powell showcased improvements in baseboard management controller security, including enforced TLS 1.2/1.3 encryption, integration with secure enclaves, remote key management, and regular firmware scanning with new protocols like SPDM to prevent rogue updates.

Andrew Elisavetsky demonstrated how to configure and manage systems using both iLO directly and with COM. He showed how initial server setup functions such as RAID configuration, BIOS tuning, and security settings could be done manually through iLO or scaled efficiently across fleets using server groups and shared profile templates in COM. Through server groups, users could automate BIOS settings, firmware updates, OS installations, and storage configurations. The updated COM interface simplifies lifecycle management and deployment workflows, especially across widespread environments such as retail or edge deployments, where systems can be delivered pre-configured directly to remote sites. These bulk configuration and automation tools become especially useful for managing large environments with minimal human intervention.

The presentation concluded by comparing COM with the long-standing OneView platform, clarifying that while COM introduces a modern, cloud-based alternative, HPE remains committed to OneView, especially in environments requiring on-premises management like government data centers. HPE acknowledged current limitations in declarative infrastructure management with tools like Terraform and Ansible but pointed to expanding API support and PowerShell commandlets as steps toward broader integration. Furthermore, the speakers underscored COM’s value in sustainability tracking and lifecycle reporting, providing critical insights like energy consumption and carbon footprint analysis, which support modernization efforts across mixed-generation hardware. Overall, HPE’s ProLiant compute management strategy is designed to unify edge and core environments under a single, scalable platform.


End-to-End Server Security with HPE iLO 7

Event: Next Gen HPE ProLiant Compute Deep Dive

Appearance: End-to-End Server Security with HPE iLO 7

Company: HPE

Video Links:

Personnel: Cole Humphreys, Luis Luciano

From chip to cloud, HPE ProLiant iLO 7 features many security innovations. Presented by Cole Humphreys, Server Security Product Manager, and Luis Luciano, Distinguished Technologist.

During this deep dive session, HPE outlined its comprehensive security approach to server infrastructure, emphasizing that cybersecurity threats are pervasive and increasingly targeting hardware vulnerabilities. HPE identified rising ransomware threats, the growing potential impact of AI in cyberattacks, and the huge financial losses associated with data breaches—especially profound for small and mid-sized businesses. As part of HPE’s Secure by Design strategy, ProLiant servers are architected to provide end-to-end security beginning in the supply chain, through server production, and into operational environments. This includes adherence to a secure development lifecycle, global operational support, and ongoing collaboration with industry standard and compliance frameworks like NIST, FIPS, PCI DSS, and HIPAA.

A central component of this security framework is the iLO 7 management chip, which introduces advanced capabilities such as Silicon Root of Trust (SROT) and a new secure enclave. The iLO 7 chip validates server components before booting, ensuring only authenticated firmware and hardware are allowed to operate. By embedding immutable firmware directly bound to silicon and incorporating new standards like post-quantum cryptography (PQC) compliance, HPE asserts its systems remain secure even against future quantum computing threats. The secure enclave also provides on-chip, level 3 FIPS-compliant key management with support for Safe Erase and backup to external HSMs like those from Talos, allowing customers to store encryption keys in a hardened environment without sacrificing accessibility. Moreover, HPE’s use of SPDM (Security Protocol and Data Model) enables attestation and validation of third-party hardware components such as GPUs, enhancing the zero trust model across external devices and integrations.

HPE also highlighted the centralized security dashboards available through Compute Ops Management (COM), enabling organizations to gain real-time visibility into server health and security posture across large fleets. Moreover, HPE discussed compliance best practices involving log sanitization for regulatory regulations like GDPR and HIPAA, and its approach to TLS certificate management in alignment with modern browser requirements. Beyond firmware and component-level concerns, the conversation expanded to the implications of managing security for peripheral systems like liquid cooling in high-performance environments and how security standards must adapt to interconnected dependencies. The session concluded by emphasizing HPE’s differentiation in the market due to its proprietary silicon, holistic secure development lifecycle, and forward-compatible security features, along with anecdotal examples of how their architecture shielded customers from industry-wide vulnerabilities impacting competitors.


HPE ProLiant Compute at the Edge

Event: Next Gen HPE ProLiant Compute Deep Dive

Appearance: HPE ProLiant Compute at the Edge

Company: HPE

Video Links:

Personnel: Chris Bradley, Gary Wang, Priya Sharma

The HPE ProLiant edge compute team presents the new DL145, focusing on unique workloads, security, and lifecycle management features of the platform. Presented by Priya Sharma, DL145 Product Manager, Gary Wang, Compute Solutions, and Chris Bradley, Technical Enablement Manager.

The presentation began with an overview of the edge computing landscape, emphasizing its differences from traditional data center environments and explaining the growing importance of edge deployments. Priya Sharma highlighted the shift in enterprise computing, as 25% of all servers are projected to be deployed at the edge by 2027, driven by latency-sensitive applications, data security needs, and real-time decision-making. She defined edge environments as uncontrolled, non-data center locations like retail stores, factory floors, and outdoor sites. HPE observed a need for purpose-built edge hardware, as many current edge deployments still rely on inadequate consumer-grade devices that can’t meet requirements for performance, reliability, environmental resilience, and remote manageability.

To address these challenges, HPE introduced the ProLiant DL145 Gen11 server, a compact, ruggedized edge platform designed from the ground up based on extensive customer feedback. Key features of the DL145 include a minimal footprint and wall-mount option for space-limited environments, quiet operation, filtration for dusty settings, and support for extreme temperatures. The server is powered by AMD’s 4th Gen EPYC Sienna CPU series with options ranging from 8 to 64 cores and includes up to eight storage drives delivering as much as 92TB capacity depending on drive types. Enhanced physical and cyber security features like chassis intrusion detection, self-encrypting drives, and integrated iLO 6 management are also included. Moreover, the DL145 supports high-performance GPUs like the NVIDIA L4 and L40S for inferencing and edge AI use cases.

Gary Wang elaborated on real-world deployment blueprints, illustrating how verticals like retail and manufacturing can benefit from a two-node DL145 configuration—one for AI analytics and another for traditional applications. Chris Bradley expanded on how HPE’s ComputeOps Management (COM), a component of the GreenLake platform, provides seamless, cloud-based infrastructure management for thousands of distributed edge devices. With tools like ILO for remote telemetry and Redfish API support, administrators can perform updates, monitor health, and ensure security compliance from a centralized interface. The HPE GreenLake ecosystem integrates compute, networking (Aruba), and storage (Electra), providing an end-to-end solution for modern edge environments.


HPE ProLiant Compute Gen12 Portfolio Overview

Event: Next Gen HPE ProLiant Compute Deep Dive

Appearance: HPE ProLiant Portfolio Overview

Company: HPE

Video Links:

Personnel: Darren Anthnoy

In this presentation, Darren Anthony highlights the long-standing innovation and evolution of the HPE ProLiant server platform, beginning with its debut in 1993. He traces the portfolio’s development through key milestones such as the introduction of four-processor blades in 2003, Gen 8 in 2012, Silicon Root of Trust in 2017, and Gen 11 in 2022. The newly launched Gen 12 servers build upon this legacy with significant advancements in security, performance, and efficiency, reaffirming HPE’s commitment to innovation in the face of evolving IT workloads and security threats.

A major feature of Gen 12 servers is the enhanced Integrated Lights-Out (iLO) 7 management processor, built upon HPE’s proprietary 64-bit ASIC. This includes a new secure enclave, effectively a hardware-based security module akin to a TPM, which provides tamper protection and cryptographic storage. These enhancements are HPE’s response to growing concerns from customers about hardware and supply chain security, especially as threats such as quantum computing become more prominent. The secure supply chain initiatives ensure server integrity from the factory floor to customer delivery, providing confidence to CISOs and infrastructure leaders alike.

Beyond security, Gen 12 also addresses modern application demands by supporting increasingly dense configurations and emerging workloads, such as AI and high-performance computing. Anthony discusses the challenges of thermal management as components grow more power-hungry, and notes HPE’s readiness for liquid cooling, calling back to decades of IP in this space. With support for advanced accelerators and collaboration with partners like NVIDIA and Intel, the Gen 12 lineup includes flexible platforms for edge, SMB, enterprise, and AI environments. This broad portfolio underscores HPE’s agility to meet a variety of workload needs while remaining forward-looking in compute infrastructure design.


Secure Your AI Applications with Microsoft Defender for Cloud

Event:

Appearance: Securing AI with Microsoft Security Copilot and Defender

Company: Microsoft Security

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Personnel: Neta Haiby

Neta Haiby, Partner Product Manager, Security at Microsoft, emphasizes the importance of securing AI applications with Microsoft Defender for Cloud. She highlights key security challenges organizations face when adopting AI, including data leaks, injection attacks, and regulatory compliance. AI security extends beyond traditional threats to include model vulnerabilities, prompt injections, and amplified data risks. Defender for Cloud provides a layered security approach, integrating security posture management, threat protection, and real-time monitoring across AI workloads. It enables visibility into AI assets, detects vulnerabilities, and helps developers remediate security gaps. As AI adoption grows, securing custom-built applications becomes essential to safeguarding data, models, and user interactions.

Being secure is the first step towards AI innovation. Join Microsoft Secure and learn how to harden your defenses by exploring new AI-first tools, demos, and best practices. Register now: aka.ms/GestaltITSecure #MSSecure


The Security Copilot Journey with Microsoft Security

Event:

Appearance: Securing AI with Microsoft Security Copilot and Defender

Company: Microsoft Security

Video Links:

Personnel: Nick Goodman

Nick Goodman, Partner Product Manager Security Copilot at Microsoft, shares Copilot’s evolution from a chat-based assistant to an integrated AI tool embedded in security workflows. Initially designed to assist analysts through queries, Security Copilot quickly adapted to automation and workflow integration within products like Defender and Intune. Key use cases include phishing investigations, SOC situational awareness, process verification, and e-discovery. Microsoft has introduced multi-tenancy, flexible capacity, and multi-workspaces to enhance usability. Additionally, new security agents will automate threat response, vulnerability management, and conditional access policy enforcement, reducing manual workload and improving real-time security operations.

Being secure is the first step towards AI innovation. Join Microsoft Secure and learn how to harden your defenses by exploring new AI-first tools, demos, and best practices. Register now: aka.ms/GestaltITSecure #MSSecure


Building a Community Around Network Automation with NAF

Event: Networking Field Day 37

Appearance: Networking Field Day 37 Community Sessions

Company: Tech Field Day

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Personnel: Scott Robohn

Find out more about the Network Automation Forum and the community that has sprung up around it. See the foundations of the organization and how they have grown to encompass so many areas as well as putting on their own highly-regarded conference on two continents. Get involved in NAF and spread the word with your community as well.


US Networking User Association Overview with Jason Gintert

Event: Networking Field Day 37

Appearance: Networking Field Day 37 Community Sessions

Company: Tech Field Day

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Personnel: Jason Gintert

Learn the journey that Jason Gintert has taken toward creating a vendor-neutral networking user organization. See the obstacles that he has overcome and learn about the team that enables USNUA chapters to exist all over the country. See how the local chapters work with a special guest speaker and find out how to get involved!


Selector AI Conclusions on the Future of Network Automation

Event: Networking Field Day 37

Appearance: Selector AI Presents at Networking Field Day 37

Company: Selector AI

Video Links:

Personnel: John Capobianco

In this wrap up, learn Selector.ai’s thoughts on the future of network automation. See how they are integrating AI copilots and RCA into environments and gleaning data from your network to help build more robust solutions to automation challenges. Get insights from Tech Field Day delegates on the challenges that need to be solved and where Selector.ai can help the most.


The Operational Twin: Past Present and Future of Your Network with Selector.ai

Event: Networking Field Day 37

Appearance: Selector AI Presents at Networking Field Day 37

Company: Selector AI

Video Links:

Personnel: John Capobianco

Learn all about operational twins in this video. See how past historical data and present insights from your network in real time can be combined in the operational twin to predict future performance and issues. In addition, find out how the operational twin leverages copilots and agents to provide full lifecycle management of your network infrastructure.


Selector AI RCA AI Agents: Closing the Loop on Automated Remediation

Event: Networking Field Day 37

Appearance: Selector AI Presents at Networking Field Day 37

Company: Selector AI

Video Links:

Personnel: John Capobianco

AI can help network operations teams with root cause analysis (RCA). Gone are the days of reactive troubleshooting. Instead, see how Selector.ai uses AI to assist with detection, diagnosis, and remediation of network issues automatically to create a self-healing network. Shown in the video is a demo of AI detecting an outage and automatically applying fixes to bring it back online.


Selector AI Copilot: Talking to Your Infrastructure

Event: Networking Field Day 37

Appearance: Selector AI Presents at Networking Field Day 37

Company: Selector AI

Video Links:

Personnel: John Capobianco

See network copilot in action! Learn how Selector.ai can talk to your network infrastructure and assist with troubleshooting, automation, and gaining insights on the state of your systems. Included is a demo of copilot working with a test system to show how it interacts with data and presets the results to operators.


Transforming IT Operations: The Power of AI Agents, RCA, and Operational Twins

Event: Networking Field Day 37

Appearance: Selector AI Presents at Networking Field Day 37

Company: Selector AI

Video Links:

Personnel: John Capobianco

In this session, learn how AI is transforming the world of network operations. The shift in the industry is leading towards AI-drive infrastructure management. Learn how Selector.ai is combining copilots, RCA, and Operational Twins together to help streamline your operations and ensure teams are working at peak efficiency.


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