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5 Key Challenges for Proactive Application Performance Management

TRAC's research shows that IT first learns about performance issues when business users bring it to their attention in 37% of cases. Additionally, many end-users never complain about issues with application performance as they simply abandon the application or a website.

The ability to prevent issues with application performance before they impact business users results in measurable operational and business benefits, but still many end-user organizations are not successful in meeting this goal. TRAC's research shows that only 41% of organizations have a 50% or better success rate in identifying performance issues before they impact business users.

Some of the key reasons why the prevention of performance problems is still a major issue for organizations include:

1. APM strategies predominantly focused on troubleshooting

Even though APM solutions that organizations are purchasing often include strong capabilities for proactive management, organizations tend to use these solutions for troubleshooting only. This comes as a result of:

- internal strategies for managing IT services that are predominantly focused on “firefighting”

- the lack of resources and time needed to support a learning curve and the provision of additional internal resources required to take advantage of features for proactive management

2. Baselining and alerting

Timeliness and accuracy of performance alerts play a significant role in enabling proactive APM. From a cost-savings perspective, there is a significant difference between being able to alert the IT team about issues as they happen as opposed to several minutes later.

The process for defining performance baselines determines how early organizations can detect potential performance issues and, therefore, define an organization's ability to mitigate the negative impact of application performance issues on their business.

3. Collaboration between production and pre-production teams

Production and pre-production teams must be able to speak a common language so organizations can identify potential performance bottlenecks before applications go to production thereby improving their success rate in preventing performance issues. Application transactions can serve as the common language between these groups. Organizations must deploy technology capabilities that will enable collaboration between production and pre-production teams.

4. Advanced APM analytics

Effective strategies for proactively managing application performance issues call for next-generation analytics that enable organizations to perform "what-if" analyses and to automatically detect performance anomalies. Not having these types of capabilities in place makes it more difficult to identify problems early and resolve them before they impact business users.

5. Monitoring the impact of change

Organizations are reporting that many performance problems are caused by changes – in usage patterns, application features, new infrastructure or service delivery type. However, many organizations do not have capabilities in place to analyze how these changes could impact application performance from the end-user's perspective.

ABOUT Bojan Simic

Bojan Simic is President and Principal Analyst at TRAC Research, a market research and analyst firm that specializes in IT performance management. As an industry analyst, Simic has interviewed more than 2,000 IT and business professionals from end-user organizations and has published more than 50 research reports. His domain knowledge includes insights into end user experiences, best-practices in deploying solutions for IT performance management, and strategies of related solution providers.

Prior to joining TRAC Research, Simic was a lead analyst for Network and Application Performance Management research at Aberdeen Group. He is frequently quoted in leading industry publications and has presented his research findings at more than 30 market facing events.

Simic's coverage area at TRAC Research includes application and network monitoring, WAN management and acceleration, cloud and virtualization management, business service management and managed services.

Bojan holds a BA in Economics from Belgrade University in Belgrade, Serbia and an MBA from McCallum Graduate School of Business at Bentley University.

Related Links:

www.new.trac-research.com/

IT Performance Monitoring in 2013 – Key Market Trends

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

5 Key Challenges for Proactive Application Performance Management

TRAC's research shows that IT first learns about performance issues when business users bring it to their attention in 37% of cases. Additionally, many end-users never complain about issues with application performance as they simply abandon the application or a website.

The ability to prevent issues with application performance before they impact business users results in measurable operational and business benefits, but still many end-user organizations are not successful in meeting this goal. TRAC's research shows that only 41% of organizations have a 50% or better success rate in identifying performance issues before they impact business users.

Some of the key reasons why the prevention of performance problems is still a major issue for organizations include:

1. APM strategies predominantly focused on troubleshooting

Even though APM solutions that organizations are purchasing often include strong capabilities for proactive management, organizations tend to use these solutions for troubleshooting only. This comes as a result of:

- internal strategies for managing IT services that are predominantly focused on “firefighting”

- the lack of resources and time needed to support a learning curve and the provision of additional internal resources required to take advantage of features for proactive management

2. Baselining and alerting

Timeliness and accuracy of performance alerts play a significant role in enabling proactive APM. From a cost-savings perspective, there is a significant difference between being able to alert the IT team about issues as they happen as opposed to several minutes later.

The process for defining performance baselines determines how early organizations can detect potential performance issues and, therefore, define an organization's ability to mitigate the negative impact of application performance issues on their business.

3. Collaboration between production and pre-production teams

Production and pre-production teams must be able to speak a common language so organizations can identify potential performance bottlenecks before applications go to production thereby improving their success rate in preventing performance issues. Application transactions can serve as the common language between these groups. Organizations must deploy technology capabilities that will enable collaboration between production and pre-production teams.

4. Advanced APM analytics

Effective strategies for proactively managing application performance issues call for next-generation analytics that enable organizations to perform "what-if" analyses and to automatically detect performance anomalies. Not having these types of capabilities in place makes it more difficult to identify problems early and resolve them before they impact business users.

5. Monitoring the impact of change

Organizations are reporting that many performance problems are caused by changes – in usage patterns, application features, new infrastructure or service delivery type. However, many organizations do not have capabilities in place to analyze how these changes could impact application performance from the end-user's perspective.

ABOUT Bojan Simic

Bojan Simic is President and Principal Analyst at TRAC Research, a market research and analyst firm that specializes in IT performance management. As an industry analyst, Simic has interviewed more than 2,000 IT and business professionals from end-user organizations and has published more than 50 research reports. His domain knowledge includes insights into end user experiences, best-practices in deploying solutions for IT performance management, and strategies of related solution providers.

Prior to joining TRAC Research, Simic was a lead analyst for Network and Application Performance Management research at Aberdeen Group. He is frequently quoted in leading industry publications and has presented his research findings at more than 30 market facing events.

Simic's coverage area at TRAC Research includes application and network monitoring, WAN management and acceleration, cloud and virtualization management, business service management and managed services.

Bojan holds a BA in Economics from Belgrade University in Belgrade, Serbia and an MBA from McCallum Graduate School of Business at Bentley University.

Related Links:

www.new.trac-research.com/

IT Performance Monitoring in 2013 – Key Market Trends

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...