Skip to main content

Application Performance Management is More Than Application Performance Monitoring

Application Performance Management (APM), as defined by the industry, is focused on monitoring — because you can’t manage what you can’t see. But, there are other functions involved in managing application performance. 

For instance, this month we saw news that Outlook.com’s outage was due to a failed firmware update. Monitoring is a key element of ensuring application performance — however, other functions, such as patch management, are necessary to proactively prevent service failures. Below are a few practical considerations when delving into managing application performance.

Measuring Application Performance — What Should You Care About?

Before you start to monitor anything, you need to understand the expectations from the application’s end-users. This will help you focus on the metrics that really matter and prioritize the type of monitoring solution that is required.

For instance, is up/down monitoring adequate? Is an agentless solution sufficient? Or is something more robust needed to collect log files and so on? It’s your duty to weigh the needs of the business (i.e. what’s the impact if monitoring is not in place?) against the cost of the monitoring solution.

Having the end-user conversation will also help you understand the resource requirements for an application. Oftentimes, applications are deployed with more resources than is actually needed to meet performance objectives.

Time to Measure and Monitor — How Do You Know Application Performance is Out of Whack?

Let’s first answer this question by understanding some of the things that can go wrong:

Resources are constrained. This could happen because there is an influx of demand on the application (more users/customers). Some apps simply use more memory the longer they run. Processes can get out of control. Resource constraints can also occur if resources are shared between applications (e.g. in a virtual environment where too many VMs on the same server, SAN capacity, etc.).
 
Services stop. This can be caused by a fatal exception, etc. These things happen unexpectedly, so it’s good to have monitoring in place to alert you when a service has stopped so you can restart it immediately.

Hardware fails. Power supplies go kaput, fans break, temperature spikes, and hard drives fail. These hardware failures can and do happen, so you need advanced warning to find them and fix them quickly.

Someone changed something and it broke. Oftentimes, configuration changes can lead to performance problems. Did the Web team update the site? Was there a software update outside of a change request? Keep these peripheral factors in mind.

You’ve been hacked. According to a recent study by Ponemon Institute, survey participants experienced almost two cyber-attacks per week, many of which are DDOS attacks, as witnessed recently by Brian Krebs’ website.

Software requires updating. More often, software needs to be updated due to vulnerabilities; however, many updates fix functional bugs. In the Outlook.com example mentioned above, some functional updates can cause service outages if not applied timely and correctly.

From step 1, you have an idea of where you should focus how much of your effort. Taking it to the next step is a little tricky. For example, your application owner needs the application to be available Monday – Friday between the hours of 8 a.m. and 5 p.m., he expects no more than 1,000 users at once, and he expects users to be able to process a transaction in three minutes. 

With this information, you know critical alerts should fire during these business hours, it’s acceptable to perform software/firmware updates on the weekends or in the evening, and you have a baseline of acceptable performance from the end-user.

This application is comprised of several different components, including a Web server, application server, database and underlying hardware, storage, and networking elements. The SysAdmin is a jack of all trades who knows a little about a lot. What does it mean to monitor the SQL database? How does the SysAdmin monitor slow queries or table locks? What is a good value or a bad value? What should the threshold be? 

Luckily, there are tools that can automate a lot of the guessing and manual reporting when it comes to application performance. Tools these days should provide intelligence to what should be monitored, historical data for benchmarks/troubleshooting, and also the ability to get to the necessary details quickly.

What to Look for in Tools that Help Manage Application Performance

Application and server monitoring tools should be able to monitor across multiple components of the application to include server hardware, virtual machines, processes, services and performance metrics specific to a particular application. Tools should also provide thresholds based off best practices of what can be adjusted with historical insight as needed.

Patch management tools should provide information on which systems are out of compliance, be able to patch systems at discrete times, and inform IT when patches fail.

Configuration change management toolsshould identify and repair unauthorized configuration changes.

The time and cost associated with implementing APM tools should certainly outweigh the cost of application degradation or outage, and the IT labor costs of manually finding and fixing the problem.

ABOUT Jennifer Kuvlesky

Jennifer Kuvlesky is a Product Marketing Manager for SolarWinds, specializing in systems management. She has made her home in Austin, the high-tech capital of Texas, for more than 15 years, specializing in product management, strategy and marketing with solid knowledge of the systems and application and virtualization management market segments. Connect with Jennifer Kuvlesky on twitter @jenniferkuvlesk.

Related Links:

www.solarwinds.com

IT Budget Help: 4 Steps to Align IT Spending to Business Goals

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

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 ...

Application Performance Management is More Than Application Performance Monitoring

Application Performance Management (APM), as defined by the industry, is focused on monitoring — because you can’t manage what you can’t see. But, there are other functions involved in managing application performance. 

For instance, this month we saw news that Outlook.com’s outage was due to a failed firmware update. Monitoring is a key element of ensuring application performance — however, other functions, such as patch management, are necessary to proactively prevent service failures. Below are a few practical considerations when delving into managing application performance.

Measuring Application Performance — What Should You Care About?

Before you start to monitor anything, you need to understand the expectations from the application’s end-users. This will help you focus on the metrics that really matter and prioritize the type of monitoring solution that is required.

For instance, is up/down monitoring adequate? Is an agentless solution sufficient? Or is something more robust needed to collect log files and so on? It’s your duty to weigh the needs of the business (i.e. what’s the impact if monitoring is not in place?) against the cost of the monitoring solution.

Having the end-user conversation will also help you understand the resource requirements for an application. Oftentimes, applications are deployed with more resources than is actually needed to meet performance objectives.

Time to Measure and Monitor — How Do You Know Application Performance is Out of Whack?

Let’s first answer this question by understanding some of the things that can go wrong:

Resources are constrained. This could happen because there is an influx of demand on the application (more users/customers). Some apps simply use more memory the longer they run. Processes can get out of control. Resource constraints can also occur if resources are shared between applications (e.g. in a virtual environment where too many VMs on the same server, SAN capacity, etc.).
 
Services stop. This can be caused by a fatal exception, etc. These things happen unexpectedly, so it’s good to have monitoring in place to alert you when a service has stopped so you can restart it immediately.

Hardware fails. Power supplies go kaput, fans break, temperature spikes, and hard drives fail. These hardware failures can and do happen, so you need advanced warning to find them and fix them quickly.

Someone changed something and it broke. Oftentimes, configuration changes can lead to performance problems. Did the Web team update the site? Was there a software update outside of a change request? Keep these peripheral factors in mind.

You’ve been hacked. According to a recent study by Ponemon Institute, survey participants experienced almost two cyber-attacks per week, many of which are DDOS attacks, as witnessed recently by Brian Krebs’ website.

Software requires updating. More often, software needs to be updated due to vulnerabilities; however, many updates fix functional bugs. In the Outlook.com example mentioned above, some functional updates can cause service outages if not applied timely and correctly.

From step 1, you have an idea of where you should focus how much of your effort. Taking it to the next step is a little tricky. For example, your application owner needs the application to be available Monday – Friday between the hours of 8 a.m. and 5 p.m., he expects no more than 1,000 users at once, and he expects users to be able to process a transaction in three minutes. 

With this information, you know critical alerts should fire during these business hours, it’s acceptable to perform software/firmware updates on the weekends or in the evening, and you have a baseline of acceptable performance from the end-user.

This application is comprised of several different components, including a Web server, application server, database and underlying hardware, storage, and networking elements. The SysAdmin is a jack of all trades who knows a little about a lot. What does it mean to monitor the SQL database? How does the SysAdmin monitor slow queries or table locks? What is a good value or a bad value? What should the threshold be? 

Luckily, there are tools that can automate a lot of the guessing and manual reporting when it comes to application performance. Tools these days should provide intelligence to what should be monitored, historical data for benchmarks/troubleshooting, and also the ability to get to the necessary details quickly.

What to Look for in Tools that Help Manage Application Performance

Application and server monitoring tools should be able to monitor across multiple components of the application to include server hardware, virtual machines, processes, services and performance metrics specific to a particular application. Tools should also provide thresholds based off best practices of what can be adjusted with historical insight as needed.

Patch management tools should provide information on which systems are out of compliance, be able to patch systems at discrete times, and inform IT when patches fail.

Configuration change management toolsshould identify and repair unauthorized configuration changes.

The time and cost associated with implementing APM tools should certainly outweigh the cost of application degradation or outage, and the IT labor costs of manually finding and fixing the problem.

ABOUT Jennifer Kuvlesky

Jennifer Kuvlesky is a Product Marketing Manager for SolarWinds, specializing in systems management. She has made her home in Austin, the high-tech capital of Texas, for more than 15 years, specializing in product management, strategy and marketing with solid knowledge of the systems and application and virtualization management market segments. Connect with Jennifer Kuvlesky on twitter @jenniferkuvlesk.

Related Links:

www.solarwinds.com

IT Budget Help: 4 Steps to Align IT Spending to Business Goals

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

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 ...