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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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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.

Hot Topics

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...