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Can Application Performance Management Boost CX?

Komal Lopez

Today, there are multiple market research studies that discuss and estimate a thriving growth for the application development segment. The market scenario seems relevant and business-ready for the growing popularity of applications.

Technavio Market research analysts have estimated the revenue growth story in the application development and integration market. They have predicted that the market will steadily grow and post a CAGR of almost 5 percent by 2020. Some of the key reasons cited for growth are development of faster and user-friendly processes and prevention of redundancies.

Enterprise application technologies offer businesses the advantage to get valuable information about their customers and build mutually beneficial customer experiences and relationships. It helps to collate distributed and scattered information and enables faster processing for desired outcome. Ultimately, customer experience is at the core of every technology innovation and process.

In order to keep the performance and functioning of the applications upbeat, enterprises are increasingly considering application performance management (APM). APM helps to monitor and manage performance and availability of software applications, enabling teams to keep a check on any possible issues with the application's performance problems. This helps them to keep up the application's service levels and business relevance intact.

The APM market is expected to hit $4.98 billion by 2019, which is a growth of 12.86 percent from $2.72 billion in 2014. Some key reasons being, APM helps to enhance the end user experience and sustain the quality of service with various software systems deployed at different levels in the delivery chain. This being said, APM is majorly considered by enterprises to ensure the desired customer experience (CX).

Let's look at how APM helps in ensuring absolute customer experience.

Analyzes Data on Real-Time basis

The software solutions presented by APM help boost productivity of the application's working process. It automates various functions and helps analyze the massive data that is collected by the application almost on a real-time basis. With the data insights, enterprises are able to dig deeper into customer preferences and reduce the response time to resolve any kind of customer grievances. This directly helps businesses to address any issue related to ensuring customer experience.

Build Visibility into the Application

With effective planning and implementation of APM, teams can achieve the much-needed visibility into how applications perform across the technology stack, irrespective of where they are located. Whether the application is located within a legacy system or on a Cloud, APM enables you to monitor the application's performance across all the enterprise users.

The transparency and visibility gained helps to determine the ultimate experience received by the end users. So, in case of a performance issue you would be able to understand where the issue is within the technology stack — network, servers, database, and application code or end-user device. Ultimately, it helps in addressing the technical root cause even before the end users face it and complain.

APM further helps in effectively identifying issues, determine changes in IT environment, or any kind of degradation of services. This helps enterprises get into the defense and prevention mode rather than a reactive mode, resulting in enhanced productivity and reduction in unplanned instances/issues.

Get More Service-Centric

As mentioned above, APM helps to gain better visibility into the application, which ensures that IT services meet the required parameters of business scope. It includes various aspects such as real-time reporting, service level compliance, commitment to service delivery and more. APM enables you to get context analytics, which helps measure impact of the application on the business. This helps in presenting ultimate commitment to service delivery.

It provides ways to develop customer engagement mechanisms and drive revenues by providing visibility to make data-driven, service-based investment decisions. APM tools automatically collate performance data and track system resource utilization that helps gain in-depth insights on resource consumption. Eventually, it gives enough background data to allocate costs and develop service contracts with cloud or hosting vendors.

Moreover, it also helps in planning your resources and building a strategic approach for performance management by implementing APM tools. This further helps in eliminating redundancies and boosting the enterprise's efficiencies/capabilities.

Aggressively Approach IT Management

In general, APM helps in building a relevant performance strategy for your application's design and development levels. This helps enhance your IT organization's proactive management skills. It gives the developers visibility into the code's performance through the development process and bring the desired performance levels to speed while deployment of the application.

This helps the IT operations team to get the needed notifications and alerts about any discrepancies in the production and get a view into the latest reports. These diagnostics enable teams to troubleshoot and cohesively resolve the issues without any possible conflicts.

In Conclusion

Whether you follow an Agile or a Waterfall methodology for development, it is ultimately important to address customer's issues and boost customer engagement. The market challenges are increasing and the need to please the end customer is definitely a priority. Enterprises are finding ways to deal with these challenges and bringing in tools to make the necessary impact.

APM is thus critical to ensure that the application does what it is supposed to do — empower teams and ultimately ensure the desired customer experience. Performance of the applications is very much critical to ensure profitability and sustainability in a challenging market scenario. This means, the need for APM will only rise, as applications will get more complex and will need more and more third-party integrations. Enterprises will need good and relevant tools to make this possible.

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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 ...

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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 ...

Can Application Performance Management Boost CX?

Komal Lopez

Today, there are multiple market research studies that discuss and estimate a thriving growth for the application development segment. The market scenario seems relevant and business-ready for the growing popularity of applications.

Technavio Market research analysts have estimated the revenue growth story in the application development and integration market. They have predicted that the market will steadily grow and post a CAGR of almost 5 percent by 2020. Some of the key reasons cited for growth are development of faster and user-friendly processes and prevention of redundancies.

Enterprise application technologies offer businesses the advantage to get valuable information about their customers and build mutually beneficial customer experiences and relationships. It helps to collate distributed and scattered information and enables faster processing for desired outcome. Ultimately, customer experience is at the core of every technology innovation and process.

In order to keep the performance and functioning of the applications upbeat, enterprises are increasingly considering application performance management (APM). APM helps to monitor and manage performance and availability of software applications, enabling teams to keep a check on any possible issues with the application's performance problems. This helps them to keep up the application's service levels and business relevance intact.

The APM market is expected to hit $4.98 billion by 2019, which is a growth of 12.86 percent from $2.72 billion in 2014. Some key reasons being, APM helps to enhance the end user experience and sustain the quality of service with various software systems deployed at different levels in the delivery chain. This being said, APM is majorly considered by enterprises to ensure the desired customer experience (CX).

Let's look at how APM helps in ensuring absolute customer experience.

Analyzes Data on Real-Time basis

The software solutions presented by APM help boost productivity of the application's working process. It automates various functions and helps analyze the massive data that is collected by the application almost on a real-time basis. With the data insights, enterprises are able to dig deeper into customer preferences and reduce the response time to resolve any kind of customer grievances. This directly helps businesses to address any issue related to ensuring customer experience.

Build Visibility into the Application

With effective planning and implementation of APM, teams can achieve the much-needed visibility into how applications perform across the technology stack, irrespective of where they are located. Whether the application is located within a legacy system or on a Cloud, APM enables you to monitor the application's performance across all the enterprise users.

The transparency and visibility gained helps to determine the ultimate experience received by the end users. So, in case of a performance issue you would be able to understand where the issue is within the technology stack — network, servers, database, and application code or end-user device. Ultimately, it helps in addressing the technical root cause even before the end users face it and complain.

APM further helps in effectively identifying issues, determine changes in IT environment, or any kind of degradation of services. This helps enterprises get into the defense and prevention mode rather than a reactive mode, resulting in enhanced productivity and reduction in unplanned instances/issues.

Get More Service-Centric

As mentioned above, APM helps to gain better visibility into the application, which ensures that IT services meet the required parameters of business scope. It includes various aspects such as real-time reporting, service level compliance, commitment to service delivery and more. APM enables you to get context analytics, which helps measure impact of the application on the business. This helps in presenting ultimate commitment to service delivery.

It provides ways to develop customer engagement mechanisms and drive revenues by providing visibility to make data-driven, service-based investment decisions. APM tools automatically collate performance data and track system resource utilization that helps gain in-depth insights on resource consumption. Eventually, it gives enough background data to allocate costs and develop service contracts with cloud or hosting vendors.

Moreover, it also helps in planning your resources and building a strategic approach for performance management by implementing APM tools. This further helps in eliminating redundancies and boosting the enterprise's efficiencies/capabilities.

Aggressively Approach IT Management

In general, APM helps in building a relevant performance strategy for your application's design and development levels. This helps enhance your IT organization's proactive management skills. It gives the developers visibility into the code's performance through the development process and bring the desired performance levels to speed while deployment of the application.

This helps the IT operations team to get the needed notifications and alerts about any discrepancies in the production and get a view into the latest reports. These diagnostics enable teams to troubleshoot and cohesively resolve the issues without any possible conflicts.

In Conclusion

Whether you follow an Agile or a Waterfall methodology for development, it is ultimately important to address customer's issues and boost customer engagement. The market challenges are increasing and the need to please the end customer is definitely a priority. Enterprises are finding ways to deal with these challenges and bringing in tools to make the necessary impact.

APM is thus critical to ensure that the application does what it is supposed to do — empower teams and ultimately ensure the desired customer experience. Performance of the applications is very much critical to ensure profitability and sustainability in a challenging market scenario. This means, the need for APM will only rise, as applications will get more complex and will need more and more third-party integrations. Enterprises will need good and relevant tools to make this possible.

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 ...