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How a Tap or SPAN Choice Impacts APM

Keith Bromley

For application performance monitoring (APM), many in IT tend to focus a significant amount of their time on the tool that performs the analysis. Unfortunately for them, the battle is won or lost at the data access level. If you don’t have the right data, you can’t fix the problem correctly.

This viewpoint is backed up by an APMdigest post back in August where Jim Frey cited some critical survey research. The research showed that "26% reported that their biggest challenge with incident response is that data exists, but they can’t access or analyze it easily." Key point – you need access to the right data at the right time to solve your problems.

This begs the question — how do I get the right data access?

The best source of data is from a network tap. A tap makes a complete copy of ALL the data passing through it. It is a passive device, so it does not alter any of the data and has a negligible effect on transmission time.

Taps are great because they are "set and forget." You simply plug the device into the network with a one-time disruption and you are done. No programming is required. Best of all, you can place taps anywhere in the network that you need data from — ingress, egress, remote offices, etc.

The one drawback to using taps is that if you install lots of them (which you will want to do), the amount of data feeds can overload the input ports to your APM tools. However, this issue is easily resolved by installing a network packet broker (NPB) to aggregate the data from the taps, filter the data as necessary, and then send that data on to the APM tool. This eliminates the overcrowding of the data ports on your APM tool.

An alternative to a tap is to use a mirroring port (also referred to as a SPAN port) off of your network switches. However, this is not recommended. One reason is that these ports are active devices, i.e. they can materially change data packet characteristics as the packets flow through the device. This is especially important when using data from these ports to diagnose problems.

In addition, bad packets (i.e. malformed packets) are dropped by the SPAN port. This ends up giving you a "digital view" of the situation, i.e. everything is fine and then there is a problem. Missing packets that could show degradation prior to data loss (which could have been useful to create a quicker diagnosis) is missing, along with any context as to what was happening before the problem began.

In the end, optimum data capture can be achieved using a tap and NPB. This results in a faster mean time to repair (MTTR).

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How a Tap or SPAN Choice Impacts APM

Keith Bromley

For application performance monitoring (APM), many in IT tend to focus a significant amount of their time on the tool that performs the analysis. Unfortunately for them, the battle is won or lost at the data access level. If you don’t have the right data, you can’t fix the problem correctly.

This viewpoint is backed up by an APMdigest post back in August where Jim Frey cited some critical survey research. The research showed that "26% reported that their biggest challenge with incident response is that data exists, but they can’t access or analyze it easily." Key point – you need access to the right data at the right time to solve your problems.

This begs the question — how do I get the right data access?

The best source of data is from a network tap. A tap makes a complete copy of ALL the data passing through it. It is a passive device, so it does not alter any of the data and has a negligible effect on transmission time.

Taps are great because they are "set and forget." You simply plug the device into the network with a one-time disruption and you are done. No programming is required. Best of all, you can place taps anywhere in the network that you need data from — ingress, egress, remote offices, etc.

The one drawback to using taps is that if you install lots of them (which you will want to do), the amount of data feeds can overload the input ports to your APM tools. However, this issue is easily resolved by installing a network packet broker (NPB) to aggregate the data from the taps, filter the data as necessary, and then send that data on to the APM tool. This eliminates the overcrowding of the data ports on your APM tool.

An alternative to a tap is to use a mirroring port (also referred to as a SPAN port) off of your network switches. However, this is not recommended. One reason is that these ports are active devices, i.e. they can materially change data packet characteristics as the packets flow through the device. This is especially important when using data from these ports to diagnose problems.

In addition, bad packets (i.e. malformed packets) are dropped by the SPAN port. This ends up giving you a "digital view" of the situation, i.e. everything is fine and then there is a problem. Missing packets that could show degradation prior to data loss (which could have been useful to create a quicker diagnosis) is missing, along with any context as to what was happening before the problem began.

In the end, optimum data capture can be achieved using a tap and NPB. This results in a faster mean time to repair (MTTR).

Hot Topics

The Latest

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

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 ...