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Application monitoring is another technological innovation that assists organizations in ensuring optimal performance and providing insights into their system’s health. Application monitoring tracks metrics and indicators, identifies issues, and optimizes resources to enhance the working of the system.

Here is a guide on Application monitoring and how businesses can use APM tools. 

What is Application Monitoring? 

Application monitoring means tracking various metrics and indicators to ensure optimal performance within an application. There are indicators within the applications that measure, analyze, and optimize, pinpointing performance issues. Application monitoring is an integral component for gaining insights into user experiences, and providing areas for improvement. These metrics and indicators, known as Key Performance Indicators (KPI) involve response time, error rates, application behavior in real-time, and user interactions.  

Application monitoring that infuses traditional and modern approaches is effective:

  • Traditional monitoring approaches include infrastructure monitoring. It focuses on server, network, and database monitoring.
  • Modern approaches include application-centric monitoring. It monitors application behavior, dependencies, and user experiences.

The blending of these approaches results in assisting organizations in understanding their application, problems, and improvement areas.

What Application Monitoring Tools do?

Application performance management utilizes tools to provide developers with visual representations of dependency and flow mapping. Visuals aid in gaining a better understanding and connections between events.  

Application monitoring involves an app dashboard that provides an overview of application performance. It also draws attention to issues by sending alerts.

Monitoring systems have system logs with a threshold value bar, allowing the main server to detect problems when the set threshold is surpassed. Unified monitoring servers are connected with all the other servers. These threats and alerts from servers are detected and sent to the main monitoring server. 

Monitoring agents in each server collect information depending on how you have configured it. When a pre-defined threshold is surpassed, the IP of a specific server is tracked, and the alert is sent to the main server, enabling the developer to take action and address the abnormality.

Application monitoring involves resource utilization monitoring such as CPU consumption, memory usage, network bandwidth, etc. to identify potential problems. These anomalies impact the usual functioning and performance of the app.

Application monitoring offers detailed insights on operational aspects by utilizing technologies such as cloud-based load balancing, web servers, and scalable architectures to give real-time insights, enhance positive user experiences, identify problems, and aid developers in taking prompt actions. 

Challenges of Application Monitoring

Application monitoring enhances efficiency, but it has challenges: 

Misaligned Timestamps 

Inadequate configuration in the system or exclusion of platform dependencies leads to misaligned timestamps leading to incomplete understanding of application behavior and problems. This means that the system cannot correlate events accurately across various data resources. 

Alert Fatigue 

The system can generate numerous alerts or false alarms, leading to alert fatigue. The operators are overwhelmed with work and become desensitized to these alerts. Due to this, they might miss a critical error. Effective tools such as filter noise, and specifying error alerts can reduce fatigue and overloading. 


The application monitoring landscape has expanded, including multiple services, microservices, and cloud environments, creating complexity. If a centralized monitoring server is absent, then organizations use other tools such as performance, server, and user monitoring tools, creating a fragmented landscape. 

Data Management 

Application monitoring involves analyzing various data from logs, events, bugs, metrics, and indicators. The data volume is considerably large, for analyzing and reporting in due time. Due to this, there is a need for robust data management capability to analyze data coming from various resources and make alerts promptly. 

Data Volume 

Application monitoring has a large volume of incoming data, increasing workload and user traffic. Data coming from various resources might slow down the network. Moreover, there is tool fragmentation, making it a challenge for a unified view of the entire system.

Tool fragmentation is due to complex IT structures, involving data from APM, network, and security monitoring. Using multiple monitoring tools leads to failure to identify the root problem. 

Continuous changes 

Technology in the present age is continuously evolving, creating complications in monitoring. These frequent changes make it difficult to make connections between the events and cannot trace the dependencies accurately. 

Silos Solutions 

Different monitoring solutions tend to create data towers that slow the detection and diagnosis of root issues. There is a lack of collaboration between multiple monitoring tools, impeding an effective understanding of the application’s performance. 

Types of Application Monitoring 

As hinted previously, Application Monitoring deals with several critical and distinct aspects of the application infrastructure and performance. Because of it, there are several types of APM according to its main objective. Here are the types of Application Monitoring:

Performance Monitoring

Performance monitoring involves tracking the metrics such as response time, and latency. It identifies bottlenecks such as slow database queries, latency, and CPU spikes to optimize the application and user performance. 

Security Monitoring 

It involves monitoring data security events such as unauthorized access attempts, vulnerabilities in the system, suspicious activities, malware attacks, or phishing scams. It helps identify these threats, enabling organizations to protect their sensitive data and maintain their applications. 

Resource Utilization Monitoring 

Resource Utilization Monitoring tracks the consumption of resources such as CPU, disk space, memory usage, and network bandwidth to optimize efficient resource allocation. It helps in identifying resource bottlenecks, ensuring effective performance of the server. 

Log Monitoring

It involves aggregating and analyzing log data. These logs are generated by the application and other network components. Log monitoring helps identify bugs, and security events and provides insights for a better understanding of the application and its landscape. 

User Experience Monitoring 

User experience monitor tracks and analyses user’s interactions and feedback. This tracking involves analyzing page load times, uptime, downtime, saturation, transaction rates, and user engagement. 

End-to-end monitoring 

This type of application monitoring involves analyzing the front end, back end, and other components. This entire stack analysis helps ensure a complete understanding of the server and applications. 

Availability monitoring

It monitors the availability of hardware, uptime, and accessibility of applications. It tracks the downtime of servers or other disruptions, ensuring that operators resolve the issues. 

How to choose an Application Monitoring Tool? 

  1. Observability: Consider selecting an Application monitoring management solution that allows you to monitor and observe dependencies via dashboards. Full stack observability ensures comprehensive visibility of the entire environment, enabling operators to make informed decisions and changes accordingly. 
  2. Deployment: Choose a monitoring solution whose deployment is easy with minimal impact on the infrastructure. Furthermore, APM provides deployment models, select a model that aligns with your organization’s future needs, these models might include on-premises or cloud-based deployment models. 
  3. Scalability: Select a model that can accommodate your organization’s future needs in handling large volumes of data, data ingestion rate, collecting, analyzing, and storing data. Moreover, choose an APM tool compatible with your infrastructure, and new technology such as micro services, cloud services, etc. 
  4. Cost and licensing: While choosing Application monitoring, consider the total cost of ownership (TCO). Price tiers include licensing fees, maintenance charges, implementation costs, or any other subscription charges. 
  5. Integration: Pick APM solutions that integrate with IT Management and DevOps tools. Strong integration capabilities allow seamless interoperability among various systems. It enhances workflows and integration with incident management, configuration management, and network monitoring, increasing the operability of an organization’s servers. 
  6. Capabilities: Select a tool that provides enhanced capabilities, such as analytical capabilities. These features reduce mean time to resolution due to extensive anomaly detection, root cause analytical, predictive analytical, threshold smart alerts, and event connections capabilities. 
  7. Evaluate features: Evaluate features of the application monitoring model before selecting it. Ensure that it utilizes automation to reduce the manual effort. Automation features include automated alerts, generating reports, incident connections, etc. Similarly, evaluate if the tool meets your security and compliance requirements. APM tools for adding security offer data encryption, audit trails, access control, etc.  

Application Monitoring Best Practices 

  • Defining Objectives: Define your monitoring objectives and choose a monitoring type depending upon your requirements. Define what you need to focus on, whether, it’s user experience, data monitoring, anomaly monitoring, etc. Clear and well-defined objectives assist in what aspect of application performance has to be covered. 
  • Relevant metrics: Select relevant metrics and indicators that enhance your organization’s productivity and system. Based on objectives, focus on metrics that are relevant, such as error rate, user experience response time, input and output, interface, etc. 
  • End-to-end and Real-Time Monitoring: Implement full-stack monitoring to gain an overview of the entire system. This gives visibility to all infrastructure components, including frontend and backend. Real-time monitoring implementation aids in detecting, diagnosing, and responding to anomalies in real time. Operators can set up selective alerts and can address the issues promptly. 
  • User experience Monitoring: Track user experience metrics, such as loading time, response span, etc. for better understating of end-user experience. 
  • Choosing the right APM tool: Select the right APM tool considering factors such as features, compatibility, scalability, cost, and consumption. Ensure that the APM tool aligns with your infrastructure and can handle large volumes of data per your requirements. 
  • Centralized data: Centralized monitoring data helps in giving easy and promotes interoperability. Additionally, you can utilize visualization tools and accessible tools for the dashboard to monitor and evaluate data on a unified plane. 
  • Automated Monitoring: Utilize a tool that has automated monitoring setups. Automation helps in prompt responses and reduces manual effort. Automated tools can collect data in real-time and analyze it. This also ensures continuous monitoring, detecting patterns, and identifying issues. 


We live in a world where businesses continuously rely on digital tools to ensure maximum productivity and output. Application monitoring helps them maintain systems healthy, enhancing operational efficiency and business growth. It tracks the software behavior in real-time and detects problems for prompt solutions.

Application monitoring ensures the reliability and efficiency of the ecosystem, as a critical practice among businesses to ensure a comprehensive understanding of their systems. 

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