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Application Performance Monitoring 101

By: Iryen
  |  May 1, 2023
Application Performance Monitoring 101

In this guide, let’s dive deep into Application Performance Monitoring (APM) and how it works. We’re going to establish the difference between monitoring and management. Additionally, understand how to leverage APM’s full potential and its role among the different parts of the organizations, not just the technical department. 

Modern applications bring value to every organization in today’s information age. These applications provide quick responses and real-time problem-solving. Therefore, the applications require a top-notch performance. 

Organizations use the concept of Performance Engineering as a tool to combat performance failures. However, the rise of complexities among web technologies makes performance monitoring more difficult.  

For example, at the backend, there are intertwined mashups of concerns from infrastructures, dependencies, and others. The highly-distributed, multi-tier, multi-element architectures based on different app development frameworks add difficulties in application performance monitoring. 

To get the gist of what’s happening during application performance monitoring we need to understand that all applications are different. As an example, a Business to Consumer (B2C) solution needs monitoring on the performance of their web applications. Business owners require a flawless delivery of the expected end-user experience.

On the other hand, a retail organization using an ERP solution must monitor end-to-end user experience. It includes both internal stakeholders and end-user experience.

With the different types of applications and their complexities, developers and businesses need to level up their monitoring techniques. This is where APM comes into play.

Defining Application Performance Monitoring

Application Performance Monitoring is a solution for capturing and measuring performance metrics. Its main objective is to define Service Level Agreements (SLAs) for the different performance metrics. 

Management and monitoring are often interchangeably used. Hence, it is appropriate to establish its difference. 

  • Management – it has a broader scope of strategies in managing the app’s overall performance. It is a more proactive approach to performance engineering. 
  • Monitoring – falls under the management category. It plays a critical role as it points out that there is a problem within your application and provides a reactive approach.

To fully understand, let’s have an actual use case.

For example, monitoring solutions will alert you when your Python app has memory spikes. However, management solutions take it a step further. It will help you mitigate issues, starting with code application dependencies, memory trends, and user experience. 

It means monitoring informs that users encountered problems. Management helps find the root cause of why these problems occurred. As a result, the latter provides a complete strategy ensuring full visibility into the app performance.

Furthermore, application performance monitoring tools are easy to set up. Their architecture is either intrusive or non-intrusive.  Meaning, these tools are generally designed to run outside of the application container. For example, you can find latent bugs using Prefix. Prefix can run on the second monitor and regularly initiates connections at predefined time intervals.

Also, application performance monitoring tools are comparatively lower in cost. Its design works primarily with obtaining different performance metrics such as queue length, heap size, concurrent users, thread pool size, etc.). 

These tools work best when combined with system monitoring tools such as CPU utilization, memory utilization, etc to provide a holistic view of performance across your applications when paired with user experience management tools. 

How does it work?

Since application performance monitoring is one of the aspects of Performance Engineering, it works by:

  1. Tracking your app’s behavior if it is within normal parameters; 
  2. If not, it will start sending alerts; 
  3. Collecting data with the source of the problem;
  4. Analyzing data and logs;
  5. Offering insight into the possible root cause.

Five Major Elements to Monitor

With the number of performance metrics, it is difficult on what to prioritize. Here is a summary of the APM Conceptual Framework from Gartner to help you know what metrics to monitor.

End-user experience 

The end-user experience is a high priority metric to monitor. This type of monitoring provides alerts on how a software application behaves from a user’s point of view. Such examples include slow loading time, downtime, or errors (e.g., HTTP errors). 

Application Runtime Architecture 

Monitoring the application architecture includes dependency mappings. It understands how the network topologies interact and follows the process of discovery, modeling, and display. The mapping out of all the application’s components and how it is interconnected provides a clear setup and makes problem detection easier.

Business transaction profiling 

Business transaction profiling starts with analyzing the flow of every user transaction. It then isolates specific interactions where performance issues are present. This type of monitoring is also known as tracing

It tracks the user’s journey and works around from frontend to backend. It finds the exact line of code, database query, or third-party integrations that affects application performance.

Application deep-dive analysis 

This process collects performance metrics from all the components in the application infrastructure. A robust monitoring solution executes a clear path starting with code execution (e.g., springs, struts, etc.) to the URL rendering, user request, and the origin of the request.

Analytics and Reporting 

The fifth part of the conceptual framework refers to analyzing and reporting data. It identifies usage patterns, trends, and performance issues. Developers can leverage this feature in almost all applications performance monitoring since it helps build a better plan in dealing with errors before they happen and affect end-users.

Note: In 2016, Gartner Research updated its conceptual framework into three main functional dimensions:

  • From End-user Experience Monitoring (EUEM) to Digital experience monitoring (DEM);
  • It combines the three formerly separate dimensions Application Topology Discovery and Visualization, User-defined Transaction Profiling, and Application Component Deep-dive) to Application discovery, tracing and diagnostics (ADTD);
  • Analytics and Reporting to  Application Analytics (AA).

Netreo is a great example of reporting and analytics done right. Its reporting and analytics engine is meant to be self-contained and has full automation capabilities. Netreo provides statistics from virtually any device on your network: Bandwidth. Errors. CPU. Memory. Disc. You name it. They use automated reports to turn performance into usable statistical data or information to assist IT managers, engineers, and anyone else in the business or IT decision-making process. These reports can include multi-year tables, graphs, pie charts and more. And because Netreo stores three years of historical trending data by default, you get instant access to trends and comparative long-term historical analysis.

Monitoring and Collecting the Right Data

In the previous section, I’ve introduced the conceptual monitoring framework. However, in actual situations, most application performance monitoring tools commonly track two types of metrics:

  • end-users experience app performance
  • infrastructure resources performance

However, in dealing with the most critical application performance monitoring metrics, consider the following areas:

  • User satisfaction or Apdex scores
  • Average response time
  • Error rates
  • Number of application instances
  • Request rates
  • Application and server CPU usage

All about Alerts

Alerts play a vital role in software development and performance monitoring. It should coincide with your operational SLAs. Once SLAs are established, the IT department should examine the right application performance metrics, the logging and alerting mechanisms to use. Remember, it is important to establish the relevant alerts and the right platform to use across the enterprise. 

However, this is a case-to-case basis as most enterprises have dedicated Systems Management teams. They are responsible for managing their central alerts and report dashboards, either using their customized messaging systems or integrating alerts via Slack, JIRA, Webhooks, and others. 

In dealing with alerts, there should be a concrete definition of the types of alerts and their thresholds. Establish its relevance concerning the entire process and operational SLAs. Both business and technical leads should acknowledge it. 

Additionally, Systems Management teams should work on defining the rules. These rules include who will receive what type of alerts (depends on relevance) across the enterprise. For example, you should not bother your CTO with non-critical issues in the middle of the night. Right?

How to choose the right monitoring solution

When APM tools come to mind, it is often associated with technical people. However, there are other departments across the organization that can reap the benefits of these tools as well. 

Product Owners

APM tools help product owners in examining how well their product’s features work. These tools help POs understand the journey of their users. APM tools with metrics like Apdex help POs determine whether to focus on user experience improvement, add product features, or reduce customer churn rate.  


APM helps DevOps teams detect new commits, releases and builds, and correlate them with performance issues as they occur. These monitoring tools aid DevOps pipeline to the next level as it provides quantifiable feedback to application developers.

Application Support and Helpdesk

Application and customer support teams benefit from an APM tool. By using the APM tool’s dashboard, support teams can re-evaluate customer’s sessions and pinpoint relevant metrics, causing performance errors. For instance, they can identify what tier is causing problems. Then, relay it to the development or DevOps teams for troubleshooting. 

Business Intelligence (BI)

Application monitoring also provides business analytics. Thus, marketing teams can leverage their use. In a digital user experience, marketing analysts can gain access to customer journeys and measure their user satisfaction. 

For example, on an e-commerce website, the marketing and development team investigate factors between failed and abandoned carts to page speed. From there, the marketing department may offer optimization insights to improve overall customer experience and increase conversion rates.

Proactively Improve your Application Performance

Whether you opt to choose management or monitoring in dealing with performance issues, it boils down to three important processes. In performance engineering, the basic process includes knowing, capturing, and analyzing. 

Most application performance monitoring tools entail the knowing and capturing processes only. For instance, Stackify Prefix falls under this category. Besides being easy to use and able to provide actionable insights, it monitors performance at code-level. It depicts end-user experience, simulates functional and non-functional tests while coding, and offers insights for possible recurring issues.

Indeed, applications are responsible for delivering mission-critical services to business users or customers. Therefore, you must have the processes and tools to know, capture, analyze, and measure the performance of your application. Take note of the addition of measure here. 

That is where application performance management comes in.  Stackify Retrace is an all-in-one performance management solution that offers a new era in Performance Engineering. Retrace is a solution where logging meets monitoring and works for both developers and DevOps. 

It is a full lifecycle application performance management solution that knows, captures, analyzes, and measures data, integrated errors and logs, and failed transactions to manage application health and performance.

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