How to Improve Cloud Computing with Visibility

Keith Bromley

One of the current challenges for IT teams is the movement of the network to the cloud, and the lack of visibility that comes with that shift. While there has been a lot of hype around the benefits of cloud computing, very little is being said about the inherent drawbacks.

For instance, once you give up control of the network infrastructure, you lose the ability to capture important packet data from tap and span ports. This data is necessary for troubleshooting and performance analysis. Monitoring and forensic tools still need to perform deep packet inspection to perform application performance monitoring (APM) analysis and troubleshooting activities.

In addition, while many of the cloud vendors will tell you that they offer security and visibility capabilities, this is in regards to their portion of the cloud (the infrastructure), not your workspace. Their touted “security solution” is often just an access list. If you’ve operated a data center before, are access lists the only thing you did to secure your network? I think not.

However, there is a remedy. You can deploy a virtual tap into a container within your cloud environment. This allows you to capture the specific types of packet data that you are looking for within your portion of the cloud environment. Once the tap captures the data, it can be copied and sent on to either your cloud-based, or on-premises based, tools for further analysis.

One important note. Make sure that the virtual tap you deploy can scale continuously. Otherwise, you will encounter significant problems as you spin up new apps and services. One of the problems will be lost monitoring data. If a virtual tap is overloaded, it simply cannot collect the requisite data and the data is lost. At that point, another virtual tap (or set of licenses for the tap) needs to be installed to capture the additional monitoring data. This human intervention requirement will throttle your ability to be effective. If the tap can scale continuously, then this limitation is removed and the monitoring solution can scale as you spin up more apps and services.

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How to Improve Cloud Computing with Visibility

Keith Bromley

One of the current challenges for IT teams is the movement of the network to the cloud, and the lack of visibility that comes with that shift. While there has been a lot of hype around the benefits of cloud computing, very little is being said about the inherent drawbacks.

For instance, once you give up control of the network infrastructure, you lose the ability to capture important packet data from tap and span ports. This data is necessary for troubleshooting and performance analysis. Monitoring and forensic tools still need to perform deep packet inspection to perform application performance monitoring (APM) analysis and troubleshooting activities.

In addition, while many of the cloud vendors will tell you that they offer security and visibility capabilities, this is in regards to their portion of the cloud (the infrastructure), not your workspace. Their touted “security solution” is often just an access list. If you’ve operated a data center before, are access lists the only thing you did to secure your network? I think not.

However, there is a remedy. You can deploy a virtual tap into a container within your cloud environment. This allows you to capture the specific types of packet data that you are looking for within your portion of the cloud environment. Once the tap captures the data, it can be copied and sent on to either your cloud-based, or on-premises based, tools for further analysis.

One important note. Make sure that the virtual tap you deploy can scale continuously. Otherwise, you will encounter significant problems as you spin up new apps and services. One of the problems will be lost monitoring data. If a virtual tap is overloaded, it simply cannot collect the requisite data and the data is lost. At that point, another virtual tap (or set of licenses for the tap) needs to be installed to capture the additional monitoring data. This human intervention requirement will throttle your ability to be effective. If the tap can scale continuously, then this limitation is removed and the monitoring solution can scale as you spin up more apps and services.

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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 ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

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 ...

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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 ...

Empowering the Human Side of the Autonomous IT Age

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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 ...

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