With a combination of real-time performance monitoring and machine-learning driven analytics, Broadcom Software’s DX NetOps comprehensively simplifies the management of today's complex network architectures through high scale, unified network monitoring enabling full-stack analytics for assuring traditional, and software-defined and cloud architectures. 

AI training and inferencing are only as strong as the network paths they depend on. Whether data moves across your own infrastructure, a co-lo, or the public cloud — every hop matters. Latency, jitter, or loss at any point can silently degrade AI outcomes.

In this 15-minute webinar and live product demo, learn how advanced network observability enables full-path validation to ensure consistent performance across the entire AI data pipeline. We’ll show how to:
        •        Continuously validate network performance from GPU to storage to cloud
        •        Gain visibility into third-party and provider-owned segments
        •        Detect and troubleshoot path degradation in real time
        •        Ensure SLA compliance for AI model training and real-time inferencing

In the AI era, “good enough” networking doesn’t cut it. Join us to learn how to verify every link, every node, and every provider in the critical path — so your AI workloads stay fast, reliable, and accurate.

SMALL BYTES: #10 - No Blind Spots: Validate End-to-End Network Performance for AI Workload Success

Since Broadcom's acquisition of VMware, many have asked about the future of the trusted Voyence NCM. In a landscape where manual configuration errors are the #1 cause of preventable outages and tool sprawl creates more problems than it solves, a clear strategy for network integrity is more critical than ever.
Join us for this 15-minute  session where we'll show you how Broadcom is revitalizing Voyence NCM by including it as a core component of our industry-leading Network Observability platform. We're moving beyond uncertainty to deliver a unified, powerful solution.

The Strategic Future of Voyence NCM with Broadcom

AI workloads push networks to their limits — with massive data flows, bursty traffic, and ultra-low latency requirements. But when performance drops, is the culprit compute… or congestion?

In this 15-minute webinar and live product demo, we’ll show how advanced network observability can help you pinpoint congestion that’s throttling your AI pipeline. You’ll learn how to:
        •        Detect and isolate congestion points across AI training and inferencing paths
        •        Correlate traffic spikes with drops in model throughput or inference accuracy
        •        Monitor real-time link utilization, queuing, and buffer pressure
        •        Visualize data flows across east-west GPU communication and multi-cloud links

AI doesn’t tolerate slowdowns — and neither should your network. Join us to learn how to identify and eliminate the invisible congestion that could derail your AI performance.

SMALL BYTES: #9 - Uncover the Bottlenecks: Identifying Network Congestion Impacting AI Workloads

AI workloads are breaking traditional network designs. Yesterday’s hierarchical, tree-like topologies can’t keep up with the low-latency, high-throughput demands of today’s flat, high-radix architectures used in AI clusters and HPC environments.

In this 15-minute webinar and live product demo, we’ll explore how network observability helps NetOps teams regain clarity and control in the face of topology transformation. You’ll learn how to:
        •        Visualize and monitor flat, high-bandwidth topologies in real time
        •        Understand traffic flows in low-diameter, non-hierarchical environments
        •        Pinpoint performance hotspots in GPU-to-GPU and east-west traffic paths
        •        Simplify complexity with topology-aware observability

The network may have changed — but with the right visibility, managing it doesn’t have to be a mystery. Join us and find your NetOps innocence again, even in an AI-accelerated world.

SMALL BYTES: #8  - From Tree to Mesh: Rediscover NetOps Simplicity in AI-Era Network Topologies

AI workloads are breaking traditional network designs. Yesterday’s hierarchical, tree-like topologies can’t keep up with the low-latency, high-throughput demands of today’s flat, high-radix architectures used in AI clusters and HPC environments. In this 15-minute webinar and live product demo, we’ll explore how network observability helps NetOps teams regain clarity and control in the face of topology transformation. You’ll learn how to: • Visualize and monitor flat, high-bandwidth topologies in real time • Understand traffic flows in low-diameter, non-hierarchical environments • Pinpoint performance hotspots in GPU-to-GPU and east-west traffic paths • Simplify complexity with topology-aware observability The network may have changed — but with the right visibility, managing it doesn’t have to be a mystery. Join us and find your NetOps innocence again, even in an AI-accelerated world.

SMALL BYTES: #8 - From Tree to Mesh: Rediscover NetOps Simplicity in AI-Era Network Topologies

Join us for an exclusive webinar where Sean Armstrong, Head of Product Management, will unveil Network Observability Fall 2025 by Broadcom—a major step forward in lifting the operational burden from network teams. Discover how you can move from simply monitoring devices to proactively assuring the network experience for every user.

In this session, you will learn how to:

Prevent Outages: See how automating network configuration management can drastically reduce manual errors, ensure compliance, and provide a safety net for instant recovery.
Gain Deeper Insights: Learn how to correlate topology with network data and produce intelligent reports to get a true picture of service performance and identify root causes faster.
End the Blame Game: Discover how you can easily see hop-by-hop performance across networks you don't even own—like ISPs and public clouds—to definitively prove where the problem is.

What's New in Network Observability Fall 2025

AI training and inferencing generate highly bursty traffic patterns — overwhelming links, saturating buffers, and disrupting performance across the network. These sudden surges aren’t predictable with traditional tools, and without visibility, they’ll catch your team off guard.

In this 15-minute technical webinar and live demo, we’ll show how advanced network observability helps you:
        •        Detect and analyze bursty traffic patterns in real time
        •        Correlate AI workload phases with network utilization spikes
        •        Identify impacted links, interfaces, and application flows
        •        Proactively mitigate performance degradation during high-throughput training runs

Burst traffic is the new normal in AI-driven environments. Join us to see how to stay ahead of the surges — not buried by them.

SMALL BYTES: #7 -Tame the Bursts: Managing AI-Induced Traffic Spikes with Network Observability

VIDEO: SMALL BYTES: #7 -Tame the Bursts: Managing AI-Induced Traffic Spikes with Network Observability

AI workloads are dynamic, distributed, and unpredictable — and they’re already reshaping how networks behave. Sudden spikes in bandwidth demand, traffic rerouting between GPUs, and increased east-west flows can strain even the most robust infrastructures.

In this 15-minute webinar and product demo, see how network automation and observability work together to help you:
 • Respond instantly to unexpected AI-driven traffic shifts
 • Automate root cause analysis and remediation for performance issues
 • Scale intelligently with adaptive policies across hybrid environments
 • Reduce risk by eliminating manual guesswork in real-time operations

AI workloads won’t announce themselves — but your network can be ready. Join us to see how automation makes the difference between scrambling and staying in control.

SMALL BYTES: #6 - AI Won’t Wait — Automate Now: Stay Ahead of Network Performance Surprises

AI workloads are dynamic, distributed, and unpredictable — and they’re already reshaping how networks behave. Sudden spikes in bandwidth demand, traffic rerouting between GPUs, and increased east-west flows can strain even the most robust infrastructures.

In this 15-minute webinar and product demo, see how network automation and observability work together to help you:
        •        Respond instantly to unexpected AI-driven traffic shifts
        •        Automate root cause analysis and remediation for performance issues
        •        Scale intelligently with adaptive policies across hybrid environments
        •        Reduce risk by eliminating manual guesswork in real-time operations

AI workloads won’t announce themselves — but your network can be ready. Join us to see how automation makes the difference between scrambling and staying in control.

AI workloads demand more than just bandwidth — they require deterministic, lossless, and low-jitter network performance across distributed compute environments. From GPU clusters to multi-cloud data pipelines, even minor packet loss or latency variation can disrupt model accuracy and performance.

In this 15-minute technical session and live product demo, we’ll explore how to build a resilient network foundation that meets the strict delivery requirements of modern AI. Learn how to:
        •        Monitor and maintain lossless data transfer between GPU nodes
        •        Identify microbursts, buffer pressure, and congestion in real time
        •        Correlate traffic anomalies with application and infrastructure metrics
        •        Validate end-to-end performance across hybrid and edge architectures

If you’re architecting for AI at scale, resilient transport isn’t optional — it’s mission-critical. Join us and see how advanced network observability helps you meet the challenge head-on.

SMALL BYTES: #5 - Engineering Resilience: Preparing Network Infrastructure for Lossless AI Workloads

AI inferencing isn’t just fast — it’s real-time, and your network needs to keep up. From autonomous systems to edge intelligence, latency isn’t just a metric — it’s the difference between success and failure.

In this 15-minute webinar and live demo, learn how network observability can help you meet the ultra-low latency demands of AI workloads. We’ll show how to:
        •        Detect and resolve latency spikes before they disrupt inferencing
        •        Monitor critical paths across edge, core, and cloud
        •        Prioritize real-time traffic and eliminate performance blind spots
        •        Proactively tune your network for millisecond-sensitive applications

If you’re building latency-sensitive AI applications, your network needs to be just as intelligent. Let us show you how to make it happen — in real time.

SMALL BYTES: #4 Real-Time AI Needs Real-Time Networks: Managing Latency for Inferencing at Scale

SMALL BYTES: #3 Don’t Let AI Choke Your Network: Proactively Plan for Extreme Bandwidth Demands

Are you leveraging your AppNeta monitoring data to its full potential? This session focuses on AppNeta's powerful Tagging feature – key:value pairs designed to bring unparalleled organization and insight to your network operations. We'll dive into practical best practices for implementing Tags, covering essential strategies such as categorizing by physical location (System Tags), grouping by custom regions (Custom Tags), associating data with specific applications, business units, or even customer types. Discover how proper tagging facilitates quicker problem triage, more effective reporting, and a deeper understanding of end-user experience across distributed environments. This demonstration will equip you with the knowledge to implement a robust tagging strategy and unlock new levels of network performance analysis.

SMALL BYTES: Beyond Basic Filtering: Strategic Tagging for Enhanced AppNeta Network Visibility

"AI workloads don’t behave like traditional apps. They generate complex, high-bandwidth traffic that moves laterally — not just from client to server, but from GPU to GPU, node to node, and deep within distributed clusters.

In this 15-minute webinar and live demo, we’ll show you how to gain full visibility into these new traffic patterns using advanced network observability. Learn how to:
        •        Visualize east-west, north-south traffic within AI clusters, multi-clouds, hybrid work environments.
        •        Monitor GPU-to-GPU communication and detect bottlenecks
        •        Optimize bandwidth usage for training and inference workloads
        •        Prepare your infrastructure for scalable, high-performance AI operations

If your network still thinks in north-south, it’s time to evolve. Let us show you how."

SMALL BYTES:  #2 AI Workloads Aren’t Normal: Gain End-to-End Visibility into GPU-to-GPU, East-West, and Cluster Traffic

Monitoring just your web application's home page isn't enough; real user experiences involve multi-step transactions. This session will showcase AppNeta's powerful Web App Monitoring capabilities, extending beyond basic uptime. We'll start with how to set up core availability and load time monitoring, then swiftly advance to creating Browser Workflows with Milestones. Learn to simulate and validate critical user journeys, such as logging into an application, capturing performance metrics for each step. Gain proactive insights into end-user experience before issues impact your business. See it in action with a live demo.

SMALL BYTES: Beyond Uptime: End-to-End Web App Monitoring with AppNeta

"AI isn’t coming — it’s already here, and it’s hungry for bandwidth. With AI workloads consuming massive amounts of data during both training and inferencing, network infrastructure is under pressure like never before. In this 15-minute power session, we’ll break down what this data explosion means for your network — and how to stay ahead of it.

Join us for a fast-paced discussion and live demo where we’ll show how network observability can help you:
        •        Predict and prepare for surging AI traffic
        •        Identify bottlenecks before they impact performance
        •        Optimize paths across hybrid and multi-cloud environments
        •        Hold service providers accountable for real-time throughput and latency

Whether you’re running AI workloads now or planning your AI strategy, don’t miss this glimpse into the future of scalable, intelligent network operations.

SMALL BYTES: #1 - Is Your Network Ready for AI? Prepping for Massive Data Volumes with Observability That Scales

Small Bytes Series: Top 10 ways to get your enterprise network ready for AI's impact

AI workloads are bandwidth beasts — requiring massive, continuous data transfer between GPUs, clusters, and storage systems. Whether it’s model training or real-time inferencing, the pressure on your network is only going to increase.

In this 15-minute webinar and live demo, discover how to get ahead of the curve with network observability that empowers proactive bandwidth planning. We’ll cover how to:
        •        Forecast and allocate bandwidth for AI-heavy environments
        •        Identify under-provisioned links and latency-sensitive segments
        •        Optimize performance across hybrid and multi-cloud AI pipelines
        •        Avoid reactive firefighting with real-time traffic insights

Your network doesn’t have to be the bottleneck in your AI journey. Let us show you how to stay in control — before demand spikes.

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SMALL BYTES: #3 Don’t Let AI Choke Your Network: Proactively Plan for Extreme Bandwidth Demands

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Network Observability by Broadcom