APM Data Gathering in Cloud Solutions

Keith Bromley

Application performance monitoring (APM) is important regardless of what platform you run your applications on. However, cloud environments can be particularly difficult for two reasons. First, there is an attitude that everything is taken care of for you. While some functions are taken care of for you, other functions will be "add-ons" that you need to purchase and append to your cloud instance.

Still other functions, like the collection of packet data for deep packet inspection (DPI), are not even available as part of the offering from your cloud vendor. You need to buy and install those types of capabilities separately, if you want them.

And you should want packet data. According to a Dimensional Data study, 80% of the study participants did not have the data they need to monitor public cloud environments accurately. Nearly half said that their lack of cloud visibility has led to application performance issues. Half also indicated that the tools provided by public cloud vendors were inadequate to support monitoring.

This leads to the second issue — you need the right tools to collect and analyze your cloud data. Lack of proper monitoring will typically result in compliance issues and potential security issues.

Both of these issues can be remedied with the collection of proper the data. That data can then be sent on to a data lake for storage and then analysis by DPI tools or artificial intelligence.

So, how do you collect this data?

The answer is that you will need to install some sort of packet data collection solution yourself. The trick is to make sure it copies the full packet data. Unnecessary headers or payloads can be deleted later on, but you want to capture all of it up front so that you have options. Your collection tool also needs the ability to have settings so that you capture only the specific data that you need. Otherwise, if you try to copy everything, or almost everything, you will have to pay for a lot of data storage — which will become expensive.

To be clear, we are talking about capturing the complete data packet. Summarized data, log data, etc. have their place but real problems can be missed when you only look at snippets of data. Don’t cheat yourself and find yourself in a bind down the road, invest in a good packet data capture solution upfront.

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APM Data Gathering in Cloud Solutions

Keith Bromley

Application performance monitoring (APM) is important regardless of what platform you run your applications on. However, cloud environments can be particularly difficult for two reasons. First, there is an attitude that everything is taken care of for you. While some functions are taken care of for you, other functions will be "add-ons" that you need to purchase and append to your cloud instance.

Still other functions, like the collection of packet data for deep packet inspection (DPI), are not even available as part of the offering from your cloud vendor. You need to buy and install those types of capabilities separately, if you want them.

And you should want packet data. According to a Dimensional Data study, 80% of the study participants did not have the data they need to monitor public cloud environments accurately. Nearly half said that their lack of cloud visibility has led to application performance issues. Half also indicated that the tools provided by public cloud vendors were inadequate to support monitoring.

This leads to the second issue — you need the right tools to collect and analyze your cloud data. Lack of proper monitoring will typically result in compliance issues and potential security issues.

Both of these issues can be remedied with the collection of proper the data. That data can then be sent on to a data lake for storage and then analysis by DPI tools or artificial intelligence.

So, how do you collect this data?

The answer is that you will need to install some sort of packet data collection solution yourself. The trick is to make sure it copies the full packet data. Unnecessary headers or payloads can be deleted later on, but you want to capture all of it up front so that you have options. Your collection tool also needs the ability to have settings so that you capture only the specific data that you need. Otherwise, if you try to copy everything, or almost everything, you will have to pay for a lot of data storage — which will become expensive.

To be clear, we are talking about capturing the complete data packet. Summarized data, log data, etc. have their place but real problems can be missed when you only look at snippets of data. Don’t cheat yourself and find yourself in a bind down the road, invest in a good packet data capture solution upfront.

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Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

Why AI in IT Is Producing High Productivity but Heavy Workloads

AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

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The Incident Load Is Rising, but Recovery Times Aren't Moving

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

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If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

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