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The Ultimate Guide To Application Performance Management '24

The Ultimate Guide To Application Performance Management '24The Ultimate Guide To Application Performance Management '24

Businesses need to monitor their system performance and resolve technical issues rapidly. For example, slowdowns or errors within the ERP system can stop the whole company from functioning: orders can not be served, suppliers can not be paid, etc.

Companies can use APM tools to prevent these issues. APM refers to application performance management or application performance monitoring. Since APM tools facilitate monitoring the availability and performance of systems, they can help detect problems and run root-cause analyses to enable quick resolution of these problems.

What is APM?

An application performance management (APM) software tracks the performance and availability of digital assets like applications and websites. It notifies users if there are problems related to these systems. These problems can be response time disruptions or load time delays that prevent users from accessing task-related applications correctly. APM can also foresee possible problems by detecting early warning signs that might presage future issues. Here is Wikipedia’s definition of APM:

Application performance management (APM) is the monitoring and management of performance and availability of software applications. APM strives to detect and diagnose complex application performance problems to maintain an expected level of service.

How does it work?

APM tools can integrate into your digital assets and monitor every action in real-time. Here is how an APM tool works step by step:

  1. Monitoring business apps if they behave normally
  2. If something is not healthy, notifying related IT teams about the problem
  3. Collecting and analyzing the data in the context of the impact on the business and detecting the source of the problem
  4. Adapting the application environment to fix similar issues before they impact the business
Source: AppDynamics

Above, you can find an example of an APM interface. APM monitors information on almost any metric that plays a role in application availability. Although metrics might change according to business needs, here are some performance metrics that APM collects:

  • Response time
  • Error rate
  • CPU usage
  • Customer satisfaction
  • User experience
  • Number of instances
  • Request rates
  • Application availability/uptime
  • Garbage collection (GC)

Why is APM important now?

APM helps companies manage their increasingly complex operations due to an increase in a number of applications and increased data per application.

As we explained in detail in our RPA article, the number of applications is increasing rapidly. For example, there are more than 3.6 million apps available for Android users. A similar situation exists for other cloud and on-prem apps.

The amount of data created in each app is increasing rapidly. A sign of that is the increasing amount of time people spend in front of their desktops and other devices. For example, people were spending more than 3 hours on their mobile apps in 2019 which is increasing ~5% per year.

The increased number of applications and populated data increases the need for monitoring because businesses own more applications to run and more users to satisfy. With performance monitoring and root-cause analysis becoming vital, companies need APM tools to collect and process the increased amount of application data so they can detect performance issues on time.

What is the APM Conceptual Framework?

Gartner designed the APM Conceptual Framework for an overall understanding of a five-dimensional APM model. The framework outlines five dimensions and describes their potential benefits:

End-User Experience

Real-time monitoring helps businesses to gain insights for performance trending and predictive analysis. According to Gartner’s framework, this dimension provides at least 80% of the APM value in terms of application visibility for the business. We also agree that this is the most impactful dimension. There are numerous public examples of end-user experience issues causing significant financial and reputational damage. 

This dimension has two main components: passive and active. Passive monitoring is usually an agentless appliance that can be implemented with limited operational risk using network port mirroring. On the other hand, active monitoring, also known as synthetic monitoring, consists of artificial bots that help report on system availability and predefined business transactions. You can also read more about synthetic monitoring in this article.

These components are good complements: When used together, they help provide visibility on application health during both peak and off-peak hours.

Runtime Application Architecture

This dimension is vital for automating the process of mapping transactions and applications to underlying infrastructure components. While APM tools can identify the dependency mappings automatically, expert knowledge can be used to further refine the results with an understanding of how network topologies interact with the application architecture. It becomes a critical component to build on while implementing an overall runtime architecture solution because it helps lay the foundation for event correlation and provides the basis for a general understanding of how network topologies interact with application architectures.

Business Transactions

Not all application performance can be measured by end-user experience. For example, there are automated B2B processes where companies commit to SLAs. APM solutions can be used to monitor such SLAs and track root causes for issues in SLA levels.

Deep Dive Component Monitoring (DDCM)

This component usually targets the web, application, and messaging servers of businesses. It provides real-time information about the J2EE and .NET stacks. A robust solution shows a clear path from code execution to the URL rendered, and finally to the user request. 

Analytics / Reporting

Standardization of application performance data is essential for businesses. While raw data from digital assets provides flexibility in reporting, it allows for answering a wide variety of performance questions as they arise. However, too much information can make analytics harder. Thus, APM tools need to be able to identify key issues and summarize findings.

What are its benefits?


  • helps prevent issues before they affect a large number of users by alerting administrators regarding abnormal application behavior.
  • reduces Mean Time to Resolution (MTTR) enabling faster issue resolution thanks to root cause analysis capabilities
  • reduces manual troubleshooting effort by identifying root causes. APM saves time for IT professionals since they no longer need to search through each event log to identify root causes

What are the main capabilities of APM?

APM collects and analyzes application data to track application availability and performance. It foresees or detects technical problems and aims to solve them quickly. Below are the main capabilities of APM:

Anomaly Detection

An APM software identifies abnormal issues and responds to them rapidly. These issues are detected when performance metrics don’t conform to the usual patterns. The duration of the identification process depends on the depth of data collected, sensitivity and accuracy of the algorithms.

Root Cause Analysis

By running a root cause analysis, APM aims to determine the probable cause of the problem within the business system.

To run a root cause analysis, APM constructs a causality chain linking cause and effect. The probable cause is connected to the impacted applications. With this methodology, APM can focus on the cause of the problem.

Root cause analysis also enables identifying the impact of system changes. IT teams can calculate the potential impact of any planned changes in this way and take action accordingly.


APM tools can support the analytics capabilities of an enterprise with their data collection capabilities. Businesses can leverage APM tools to monitor their key performance indicators (KPIs), including financial metrics. For example, shopping cart abandonment rates, shopping cart conversions, and even the financial value of a transaction are some of the KPIs that can be tracked for e-commerce companies.

Who are its potential users?

Application Monitoring by IT Operations Teams

IT operations teams are generally tasked with keeping the system infrastructure operating efficiently and smoothly. The most common use of APM in IT operations is to track application health and identify application problems. APM can achieve this by monitoring application performance and sending early-warning notifications of performance issues. Plus, it can run root cause analysis to understand the reasons for performance issues and avoid them happening again.

Application support teams need  They have a wide range of tasks, from root cause analysis to code development that holds the application and infrastructure together. Thus, APM tools play a critical role in tracking application performance and identifying root causes if any problems occur.

IT professionals can also leverage workload automation (WLA) tools to automate, schedule, and execute IT workflows over multiple platforms from a centralized point. WLA tools can track the execution of these tasks on different platforms or applications and help IT teams detect errors and optimize IT workflows.

DevOps Teams

DevOps teams need to detect and diagnose issues quickly, as well. They need to ensure their code quality and effectiveness for recent releases. While planning deployments and changes, running tests and measuring performance metrics are essential. APM tools can be used to assess the risks in planned deployments and help DevOps teams evaluate the impact of planned application or infrastructure changes.

Application Owners or LOB (Line-of-Business) Managers

While IT teams generally inform application owners and LOB managers about performance metrics, the information is rarely at the right level of granularity to make business decisions. With APM tools, managers can benefit from detailed metrics and end-user experience data to detect trends to improve their decision making.

What are the alternatives to APM?

Without an APM solution, here are a few alternative solutions that might help companies detect and solve their performance issues in case of abnormal application behavior.

Synthetic transactions

A synthetic transaction means a transaction is created to execute against business software for performance measuring. Depending on the complexity of the software, building a basic program that calls a service and validates the response can run synthetic transactions.

However, synthetic transactions only detect performance issues and can’t identify the cause of the problem. Plus, it might not distinguish between a real problem or a usual slowdown in the system. Feel free to read our article about synthetic monitoring for more details.

Manual monitoring

Companies can manually monitor their systems by tracking real-time performance. For that, they can add performance monitoring codes to their system and record performance metrics in the database.

The challenge with this option is how to gain insights about collected real-time performance metrics. Developers need to determine what the standard parameters are, how to identify performance issues and how to discover root causes. Besides, the performance monitoring code added to the system might reduce your system performance, and the code might also include bugs.

Wait for customers to call customer support

While this is the easiest option, this option would reduce customer satisfaction and have a longer response time to solve performance-related issues.

What are the leading companies in APM? 

While technology companies like Google, Oracle offer APM solutions for businesses, there are small-medium-sized companies and startups that also provide these solutions. Here are brief descriptions of two of the common APM tools.

AppDynamics by Cisco: Acquired by Cisco in 2017, AppDynamics provides real-time monitoring, business insights, anomaly detection, and end-to-end visibility for the entire application stack with its user-friendly interface. The company aims for its users to spend less time fixing issues and more time focusing on their primary tasks.

Dynatrace: With its AI-powered tool, Dynatrace automatically monitors application/database performance and discovers any technical issues. It also covers any monitoring solution, including languages supported, application architectures, cloud, on-premise or hybrid, enterprise apps, SaaS monitoring, and more.

Below you can find an extended list of APM vendors:


  • AppDynamics by Cisco
  • Azure Application Insights
  • Google Cloud Console
  • Google Stackdriver Monitoring
  • Huawei Mobile Cloud
  • Microsoft System Center
  • Oracle Enterprise Manager


  • AdRem Software
  • Atatus
  • Catchpoint
  • Checkmk
  • Datadog
  • dotMemory
  • Dynatrace
  • Exoprise
  • FusionReactor
  • Instana
  • Instrumental
  • Logic Monitor
  • Nagios XI
  • New Relic
  • PRTG Network Monitor
  • Pulse Secure
  • Raygun
  • Red Hat
  • Retrace
  • Rigor
  • Scout APM
  • Sematext
  • Site24x7 APM
  • SolarWinds
  • SplunkEnterprise
  • Sumo Logic

If you have questions on Application Performance Management (APM) tools, feel free to contact us:

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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