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Why APM is Valuable to Every Part of Your Business

Matt Watson

Virtually every business depends on mission-critical software to run their business. Any slight application slowdown or outage can lead to legions of unhappy employees or customers. Application Performance Management (APM) solutions can help monitor for performance issues, but they can also be used to gain insights to proactively improve performance as well.

APM is not just a tool for IT Operations. APM has grown into an essential tool that can be utilized by many departments within your business.

IT Operations

When you think of APM, you normally think about IT operations using it for monitoring mission-critical applications. Instead of only monitoring servers and infrastructure, APM solutions can help better track performance at the application level. Including overall performance, key transactions, and much, much more.

Development Teams

APM solutions collect a lot of data. Including code level performance, overall application usage and performance, metrics, log messages, errors, real user monitoring, and more. All of this data can be very valuable for developers when it comes to researching bugs in production. It can also be used to identify parts of an application that can be optimized and validating those performance optimizations.

Developers can also use APM in QA to test and validate the performance of their code before it gets to production.

QA

Traditionally, APM is thought to be used mostly in production. However, APM can be extremely valuable as part of your QA process to find problems before they get to production. It could be used to look for any overall change in performance, new application errors found, load testing validation and more.

Database Administrators

Most APM solutions track the performance of SQL queries. This can be useful information for your DBAs to augment other tools they may also have. They could potentially use APM for various monitoring capabilities. For example, monitoring how often a specific SQL query is taking or how often it is being called.

Product Owners and Executives

The product owner ultimately cares a lot about the application, its functionality, usage, service availability and performance. APM gives product owners visibility into the performance of their application and potentially into metrics around how much it is being used. APM dashboards are popular with product owners and other executives in a company.

Customer Service

When a customer calls and says your application is slow, what do you do? After a quick login test to your app, your customer service member would likely tell the customer that everything seems to be working fine, and the problem is likely on their end.

The problem is a user could be accessing your application on a different server, database, or even in a different data center. If your customer service team has access to basic APM dashboards, they could leverage those to better understand if any application problems may exist or not with more certainty. They also wouldn’t have to bug the IT department every time a customer complains.

Sales and Marketing

Major application outages are always a big PR problem for marketing teams, but hopefully they can use it to instead rave about how fast your application is! They could also use it to gather insights into how parts of your application are being used. Just like your customer service team, your sales team is going to get flooded with calls if your site is down.

Conclusion

Application performance is important to your entire business. APM solutions collect an amazing out of data and usually provide very flexible reporting options. I would encourage you to think of ways to leverage the value of it anywhere that you can.

Matt Watson is Founder and CEO of Stackify.

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Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

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Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

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In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...

Why APM is Valuable to Every Part of Your Business

Matt Watson

Virtually every business depends on mission-critical software to run their business. Any slight application slowdown or outage can lead to legions of unhappy employees or customers. Application Performance Management (APM) solutions can help monitor for performance issues, but they can also be used to gain insights to proactively improve performance as well.

APM is not just a tool for IT Operations. APM has grown into an essential tool that can be utilized by many departments within your business.

IT Operations

When you think of APM, you normally think about IT operations using it for monitoring mission-critical applications. Instead of only monitoring servers and infrastructure, APM solutions can help better track performance at the application level. Including overall performance, key transactions, and much, much more.

Development Teams

APM solutions collect a lot of data. Including code level performance, overall application usage and performance, metrics, log messages, errors, real user monitoring, and more. All of this data can be very valuable for developers when it comes to researching bugs in production. It can also be used to identify parts of an application that can be optimized and validating those performance optimizations.

Developers can also use APM in QA to test and validate the performance of their code before it gets to production.

QA

Traditionally, APM is thought to be used mostly in production. However, APM can be extremely valuable as part of your QA process to find problems before they get to production. It could be used to look for any overall change in performance, new application errors found, load testing validation and more.

Database Administrators

Most APM solutions track the performance of SQL queries. This can be useful information for your DBAs to augment other tools they may also have. They could potentially use APM for various monitoring capabilities. For example, monitoring how often a specific SQL query is taking or how often it is being called.

Product Owners and Executives

The product owner ultimately cares a lot about the application, its functionality, usage, service availability and performance. APM gives product owners visibility into the performance of their application and potentially into metrics around how much it is being used. APM dashboards are popular with product owners and other executives in a company.

Customer Service

When a customer calls and says your application is slow, what do you do? After a quick login test to your app, your customer service member would likely tell the customer that everything seems to be working fine, and the problem is likely on their end.

The problem is a user could be accessing your application on a different server, database, or even in a different data center. If your customer service team has access to basic APM dashboards, they could leverage those to better understand if any application problems may exist or not with more certainty. They also wouldn’t have to bug the IT department every time a customer complains.

Sales and Marketing

Major application outages are always a big PR problem for marketing teams, but hopefully they can use it to instead rave about how fast your application is! They could also use it to gather insights into how parts of your application are being used. Just like your customer service team, your sales team is going to get flooded with calls if your site is down.

Conclusion

Application performance is important to your entire business. APM solutions collect an amazing out of data and usually provide very flexible reporting options. I would encourage you to think of ways to leverage the value of it anywhere that you can.

Matt Watson is Founder and CEO of Stackify.

Hot Topics

The Latest

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...