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6 Reasons Every NetOps Team Should Use a Packet-Based Analytics Solution - Part 2

Jay Botelho

A new breed of solution has been born that simultaneously provides the precision of packet-based analytics with the speed of flow-based monitoring (at a reasonable cost). Here are 3 more reasons to use these new NPM/APM analytics solutions.

Start with 6 Reasons Every NetOps Team Should Use a Packet-Based Analytics Solution - Part 1

4. Reduce tool sprawl

Teams are sick of adding more and more tools. The new NPM/APM solutions consolidate key functionality and offer flexible new dashboards that allow teams to monitor the information that matters most to their organization and team. For example, monitor key applications like Office365, WebEx and Salesforce in a single dashboard that includes application performance, network performance, transaction quality and VoIP quality; metrics that in the past required several solutions from several vendors to achieve the same level of visibility.

5. Get an integrated packet view

It's not enough to just be notified of abnormalities and problems. When these happen, you need immediate access to the packets that matter so you can troubleshoot and remediate. Also, NetOps needs information on the worst-performing parts of their network. Many products only calculate and display averages of network metrics like latency, utilization and VoIP quality, which can obscure problems that only affect a small number of flows. For example, a typical network will have thousands if not tens of thousands of HTTP flows at any given moment. If only a few exhibit poor network latency, and the dashboard shows the average network latency for all HTTP (which many dashboards do), the few flows that exhibit poor network latency will be masked by the good performance of all of the other flows. This example illustrates the absolute need to be able to pick the worst flows, out of millions, at any given moment to make sure critical issues are not overlooked.

6. Monitor SaaS SLAs

Whether you're offering a service or using one, being able to validate the agreement is critical, especially if problems arise. Packet data doesn't lie, which means if you have that information, you have what's needed to ensure SLAs are being delivered. Using today's modern dashboards, you can set your SLA thresholds for network latency, application latency, transaction quality and VoIP quality, and let the software constantly monitor millions of flows and let you know when even a single flow exceeds your SLAs.

As mentioned above, there's real cost associated with any kind of operational downtime, so avoiding or at least minimizing these issues is a NetOps priority. Therefore, it's critical to maintain a high-quality end-user experience for employees and customers. The powerful new analytics tools available today allow IT teams to anticipate network and application performance problems and react in real time. Rather than waiting for complaints, it's now possible to monitor every aspect of network traffic and performance at an incredibly granular level, making network problems much more visible even as the speed and volume of network traffic rises dramatically. The vision of network continuity all day, every day, across the entire network, is finally here.

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In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

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6 Reasons Every NetOps Team Should Use a Packet-Based Analytics Solution - Part 2

Jay Botelho

A new breed of solution has been born that simultaneously provides the precision of packet-based analytics with the speed of flow-based monitoring (at a reasonable cost). Here are 3 more reasons to use these new NPM/APM analytics solutions.

Start with 6 Reasons Every NetOps Team Should Use a Packet-Based Analytics Solution - Part 1

4. Reduce tool sprawl

Teams are sick of adding more and more tools. The new NPM/APM solutions consolidate key functionality and offer flexible new dashboards that allow teams to monitor the information that matters most to their organization and team. For example, monitor key applications like Office365, WebEx and Salesforce in a single dashboard that includes application performance, network performance, transaction quality and VoIP quality; metrics that in the past required several solutions from several vendors to achieve the same level of visibility.

5. Get an integrated packet view

It's not enough to just be notified of abnormalities and problems. When these happen, you need immediate access to the packets that matter so you can troubleshoot and remediate. Also, NetOps needs information on the worst-performing parts of their network. Many products only calculate and display averages of network metrics like latency, utilization and VoIP quality, which can obscure problems that only affect a small number of flows. For example, a typical network will have thousands if not tens of thousands of HTTP flows at any given moment. If only a few exhibit poor network latency, and the dashboard shows the average network latency for all HTTP (which many dashboards do), the few flows that exhibit poor network latency will be masked by the good performance of all of the other flows. This example illustrates the absolute need to be able to pick the worst flows, out of millions, at any given moment to make sure critical issues are not overlooked.

6. Monitor SaaS SLAs

Whether you're offering a service or using one, being able to validate the agreement is critical, especially if problems arise. Packet data doesn't lie, which means if you have that information, you have what's needed to ensure SLAs are being delivered. Using today's modern dashboards, you can set your SLA thresholds for network latency, application latency, transaction quality and VoIP quality, and let the software constantly monitor millions of flows and let you know when even a single flow exceeds your SLAs.

As mentioned above, there's real cost associated with any kind of operational downtime, so avoiding or at least minimizing these issues is a NetOps priority. Therefore, it's critical to maintain a high-quality end-user experience for employees and customers. The powerful new analytics tools available today allow IT teams to anticipate network and application performance problems and react in real time. Rather than waiting for complaints, it's now possible to monitor every aspect of network traffic and performance at an incredibly granular level, making network problems much more visible even as the speed and volume of network traffic rises dramatically. The vision of network continuity all day, every day, across the entire network, is finally here.

Hot Topics

The Latest

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...