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What is the Benefit of Network Visibility for Compliance?

Keith Bromley

While regulatory compliance is an important activity for medium to large businesses, easy and cost-effective solutions can be difficult to find. Network visibility is an often overlooked, but critically important, activity that can help lower costs and make life easier for IT personnel that are responsible for these regulatory compliance solutions.

Devices like network packet brokers (NPBs) allow you to mask sensitive data, perform packet slicing, implement lawful intercept, and discover rogue IT. Purpose-built compliance solutions can also use data filtered by NPBs to perform activities better, and also allow IT to demonstrate their regulatory compliance in an easy manner.

Here are some example use cases of what you can accomplish when a visibility architecture is combined with performance monitoring tools. An initial activity would be to integrate an NPB with your regulatory compliance strategy.

This will allow you to:

■ Provide masking of sensitive data. This includes data masking for one or more digits so that security and monitoring tools downstream don’t receive clear text data.

Remove the data packet payload with packet trimming. When packet header information is all you need, packet slicing allows you to eliminate the propagation of unnecessary and dangerous data within the payload of the packet.

Perform lawful intercept of data from specified IP addresses and VLANs. This provides an easy way to capture and forward data requested by court orders and government laws (like the Turkish 5651 law that requires logging of financial data).

■ Create regular expression search strings using application intelligence to enable better searches for specific data.

In addition, there are at least two areas where NPBs can help a security architecture to:

Discover rogue IT (unauthorized applications and devices), which helps avoid policy and compliance issues. Unknown applications can be identified so that IT can ascertain how and where those applications are being used.

Enforce IT policies, like detecting off-network storage and unapproved web-based email solutions. This allows IT to identify exfiltration of data which could be a potential security/compliance risk. For instance, a former employee could have stored a file to an off-network data storage and then could retrieve after leaving the company and no one would know about it.

Data from NPBs can also be fed to purpose-built compliance solutions and logging tools to support the demonstration of regulatory and endpoint compliance to auditors. The data being fed to these tools can be either lightly filtered or filtered based upon detailed Layer 2 – 4 and/or Layer 7 parameters. It all depends upon what you need and are looking for.

In the end, any regulatory compliance strategy is only as good as the quality of data that is being fed to the tools. The most important part of your regulatory compliance plan will be the architecture, as this piece will determine what, if any, policies and procedures are being adhered to.

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What is the Benefit of Network Visibility for Compliance?

Keith Bromley

While regulatory compliance is an important activity for medium to large businesses, easy and cost-effective solutions can be difficult to find. Network visibility is an often overlooked, but critically important, activity that can help lower costs and make life easier for IT personnel that are responsible for these regulatory compliance solutions.

Devices like network packet brokers (NPBs) allow you to mask sensitive data, perform packet slicing, implement lawful intercept, and discover rogue IT. Purpose-built compliance solutions can also use data filtered by NPBs to perform activities better, and also allow IT to demonstrate their regulatory compliance in an easy manner.

Here are some example use cases of what you can accomplish when a visibility architecture is combined with performance monitoring tools. An initial activity would be to integrate an NPB with your regulatory compliance strategy.

This will allow you to:

■ Provide masking of sensitive data. This includes data masking for one or more digits so that security and monitoring tools downstream don’t receive clear text data.

Remove the data packet payload with packet trimming. When packet header information is all you need, packet slicing allows you to eliminate the propagation of unnecessary and dangerous data within the payload of the packet.

Perform lawful intercept of data from specified IP addresses and VLANs. This provides an easy way to capture and forward data requested by court orders and government laws (like the Turkish 5651 law that requires logging of financial data).

■ Create regular expression search strings using application intelligence to enable better searches for specific data.

In addition, there are at least two areas where NPBs can help a security architecture to:

Discover rogue IT (unauthorized applications and devices), which helps avoid policy and compliance issues. Unknown applications can be identified so that IT can ascertain how and where those applications are being used.

Enforce IT policies, like detecting off-network storage and unapproved web-based email solutions. This allows IT to identify exfiltration of data which could be a potential security/compliance risk. For instance, a former employee could have stored a file to an off-network data storage and then could retrieve after leaving the company and no one would know about it.

Data from NPBs can also be fed to purpose-built compliance solutions and logging tools to support the demonstration of regulatory and endpoint compliance to auditors. The data being fed to these tools can be either lightly filtered or filtered based upon detailed Layer 2 – 4 and/or Layer 7 parameters. It all depends upon what you need and are looking for.

In the end, any regulatory compliance strategy is only as good as the quality of data that is being fed to the tools. The most important part of your regulatory compliance plan will be the architecture, as this piece will determine what, if any, policies and procedures are being adhered to.

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The Latest

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...