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9 Key NodeJS Metrics You Need To Keep an Eye On

NodeJS Logging is crucial for application development, and understanding NodeJS metrics is vital for optimizing performance. Imagine easily monitoring and analyzing your Node.js application's performance to ensure smooth operation. This blog will provide valuable insights into Node.js performance monitoring and metrics, helping you enhance your applications and ensure optimal functionality.

To help you achieve your objectives in performance monitoring, Alerty offers a NodeJS logging tool that simplifies tracking and analyzing your Node.js applications, allowing you to optimize performance effectively.

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Table of Contents

Understanding NodeJS Metrics

NodeJS performance metrics are quantitative measurements that provide insights into:

  • Application performance
  • Resource usage
  • Overall health

These metrics are crucial for monitoring as they help developers and system administrators identify potential issues, optimize performance, and ensure a smooth user experience.

Comprehensive Performance Monitoring

Node Application Metrics instruments the Node.js runtime for performance monitoring and provides the monitoring data via an API. The data can also be visualized using the Node Application Metrics Dashboard.

Essential Aspects of Monitoring Node.js Applications

  • Monitoring, measuring, and reporting software quality over time
  • Tracking performance and availability closely
  • Using application performance management (APM) solutions for staging or production environments
  • Employing APM tools like Alerty to optimize performance

Key Considerations for Large-Scale Enterprise Node.js Applications

  • Scalability
  • Flexibility
  • Availability
  • Performance

An organization's metrics are often related to the most crucial runtime problems encountered in the Node.js application. Monitoring performance metrics is essential to:

  • Avoid downtime
  • Ensure optimal application performance
  • Prevent customer loss

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Why You Need To Monitor NodeJS Metrics

Monitoring Node.js performance metrics has several benefits that can help you maintain your applications' optimal performance. 

Benefits of Monitoring Node.js Applications

  • Maintains and manages application performance for optimal end-user and developer experience
  • Eases troubleshooting at both backend and frontend levels
  • Allows you to address issues before they worsen
  • Provides insights into application speed, user delays, and traffic volume
  • Offers information and suggestions for improving application performance

Alerty: All-in-One Monitoring and Incident Management for Modern Apps

Alerty is a cloud monitoring service for developers and early-stage startups, offering:

  • Application performance monitoring
  • Database monitoring
  • Incident management

Alerty supports technologies like NextJS, React, Vue, and Node.js, helping developers efficiently identify and resolve issues.

  • Monitors databases including Supabase, PostgreSQL, and RDS
  • Tracks key metrics such as CPU usage and memory consumption
  • Offers quick incident management and Real User Monitoring (RUM) for optimizing user experience
  • Provides Universal Service Monitoring for dependencies like Stripe API, OpenAI, and Vercel
  • Utilizes AI for simplified setup and cost-effective solutions compared to competitors
  • Designed for ease of use with quick setup and integration with tools like Sentry

Perfect for developers and small teams seeking efficient, affordable monitoring solutions. Catch issues before they affect your users with Alerty's NodeJS logging tool. Start today!

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9 Key NodeJS Metrics You Need To Keep an Eye On

1. User-facing Latencies

Any API's purpose is to pass data from one interface to another, such as a mobile app. As a result, it's vital to ensure that the API works as intended from the user's perspective. During user interactions, you want to avoid any unwanted latencies or delays. Evaluating user-facing latencies is to check that the API functions correctly.

Establishing a Performance Baseline for Node.js Applications

You must first set a baseline before evaluating the application's performance. Any departure from the two standard deviations or less baseline is considered normal. If any Node.js performance measurement exceeds this, your API will act strangely. 

Identifying the Transaction Entry Point

After establishing a baseline, you can evaluate transaction performance by determining the entry point or interaction that initiates the user transaction. The entry point for a Node.js API is usually an HTTP request, but depending on the infrastructure, it could also be a WebSocket connection or a service call.

Testing Application Ecosystem Performance

After identifying the entry point, you can test the app ecosystem's performance to see if it's running within typical parameters (baseline + 2 standard deviations). For example, you discover that the response time differs from the average response time for that user transaction by more than two standard deviations. 

Impact of Time on User-Facing Metrics

Excessive deviation shows that the application is behaving abnormally. The user-facing metric may change depending on the time of day and week that the measurement takes place. The data obtained during this measurement will impact future baselines for that time of day and week. The progression reflects the user experience better than any other metric since it accounts for the evolution of the user-facing application. 

You must monitor all components of the user interface while assessing user-facing latencies, including:

  • Content size
  • Error rates
  • Response times
  • Request rates

2. External Dependencies

External dependencies can take many forms:

  • Dependent web services
  • Legacy systems
  • Databases 

Understanding and Monitoring External Dependencies

External dependencies are systems with which your application interacts. We may not have control over the code inside external dependencies, but we typically have control over their configuration. So, knowing when they're working well and when they're not is crucial. 

Isolating Issues: Application vs. Dependency

We also need to distinguish between issues with our application and issues with dependencies. All applications use external or backend services, and these interactions can significantly impact their overall performance. 

Examples of external dependencies:

  • Legacy systems
  • Caching layers
  • Databases
  • Queue servers
  • Web services 

Managing Configurations for Optimal Performance

Although developers have no control over the code of these backend services, they can manage their configurations. As a result, it's vital to evaluate their performance to see if they need to be reconfigured. You'll also need to determine whether the application's slowness is due to internal issues or external requirements.

Baseline and Impact of Backend Latency

An APM tool should be able to distinguish between the application and external services automatically. Sometimes, you may need to alter the monitoring program to discover external dependency behavior. You'll need a baseline to measure the performance of these external dependencies, just like you do with user-facing latencies. Despite connecting asynchronously, latency in backend services can impair performance and the user experience in a Node.js application. 

The following are some examples of exit calls:

  • External web-service APIs
  • Internal web-services
  • NoSQL servers
  • SQL databases

Measuring your application's response times as it communicates with external dependencies can detect trouble areas and enhance performance.

3. Event-Loop Blocking

Do you know why the processes in the Node.Js application are faster? This is because the event loop performs requests asynchronously without blocking them, known as non-blocking I/O.

How Node.js Handles Asynchronous Operations

The event loop is a construct of JavaScript. Its primary purpose is to carry out a block of synchronous code. Usually, even loop executes each request one by one. But since Node.Js runs on single-threaded and non-blocking, it processes tasks through callbacks. As a result, code from two or more transactions will merge and wait in the Event Queue. It can block the event loop and affect the performance of another transaction.

Event Loop Bottlenecks and Performance Implications

The model indeed ensures faster transactions. Nevertheless, the performance of transactions in the Event Queue can slow significantly. So, monitoring the event loop and identifying a request's behavior is vital before processing it. 

4. Memory Usage and Leaks Metric

Stacks

  • Store temporary variables created by functions
  • Variables are declared, stored, and initialized during runtime

Heaps

  • Contain dynamically allocated memory
  • The maximum heap size for a single process is 1.5GB

Memory Leaks: The Node.js Pitfall

This is why memory leaks are a common issue in Node.js applications. Memory leaks occur when the application code reserves a memory allocation in a heap and fails to free the memory even when it’s no longer needed. 

Garbage Collection: Node.js's Memory Management Tool

Failure to release the reserved memory causes a rise in memory usage, resulting in a spike in memory usage on the machine. Since Node.js is based on the V8 engine, it has a built-in garbage collector (GC) to manage the developer’s memory. The garbage collector releases the memory claimed by variables no longer needed.

Identifying and Addressing Memory Leaks

If you notice memory usage for a process is increasing quickly, and garbage collection isn’t periodically reducing usage, you may be experiencing a memory leak. It’s challenging to track the root cause of a memory leak, so you’re often better off addressing it as soon as you notice a rise in memory usage rather than attempting to debug or troubleshoot it. 

Metrics to watch when monitoring memory usage include the following:

  • Process heap usage
  • Released memory between garbage collection cycles
  • Process heap size

5. Garbage Collection Metrics for Node.js

In the V8 runtime, garbage collection stops program execution. There are two types of garbage collection: 

Scavenging

It uses incremental garbage collection cycles to process only a part of the heap at a time. This is very quick. 

Full Garbage

Full garbage collection cycles reclaim memory from objects and variables that survived multiple incremental garbage collection cycles. Because they pause program execution, they are executed less frequently.

By measuring how often a full or incremental garbage collection cycle is executed, you can see how it impacts the time it takes to reclaim and how much memory is released. Comparing the released memory with the size of the heap can show if there is a growing trend, leading you to figure out if you have a memory leak.

Because of everything mentioned above, you should monitor the following Node.js garbage collection metrics:

  • Time consumed for garbage collection
  • Counters for full garbage collection cycles
  • Counters for incremental garbage collection cycles
  • Released memory after garbage collection

6. Application Topology

The last Node.js performance measurement metric you will want to monitor is the layout of your application’s critical functions and connections or application topology. The cloud has generally changed the application topology structure, making it more flexible to accommodate user demand. Monitoring your topology will indicate if the size of your environment is optimal for your needs.

Evaluating User-Facing Load and Server Capacity

When assessing your application topology, you must measure your user-facing load and container performance. To determine if you have enough servers to satisfy your user-facing demand, refer to the baseline plus two standard deviations when the load increases during peak times. When the application slows down consistently, it indicates the need to increase the number of servers.

Assessing Container Performance and Scaling Needs

The same applies when assessing container performance. If any of your server tiers come under appreciable strain during operations, you need more servers for that tier. Actions based on an assessment of one server will not be appropriate, as the load may be due to factors other than use, such as garbage collection. Nevertheless, when the tier as a whole is under duress, you can safely assume it cannot handle the load it receives. 

7. Incomplete Cleanups

Another source of memory leaks needs to be completed cleanups. Node.js applications automatically trigger the garbage collection cycle to identify “dead” regions of memory – memory used by inactive objects in the heap – for cleanup. 

The Impact of Inactive Objects on Heap Usage

Each cleanup will leave the heap free of inactive objects, but that only sometimes happens. Some objects stay in the heap, taking up memory, and may grow. These inactive objects increase memory usage, classifying them as memory leaks. 

Monitoring Heap Usage for Memory Leaks

Monitoring the heap usage before and after garbage collection will indicate if you are harboring potential leaks in the form of inactive objects. If the heap usage continues to grow even after several cycles of garbage collection, then that indicates a possible leak.

Resolving Memory Leaks Through Heap Analysis

If that happens, you can collect heap data to identify the classes and objects that tend to stay in the heap so you can formulate a management plan. You can then perform a heap dump to clear it. Heap dumping significantly taxes the application, so executing it when it is unused might be best. 

8. Backend Service Latencies

All applications interact with some form of external or backend services, which can profoundly affect your application's overall performance. The external dependencies may be:

  • Legacy systems
  • Caching layers
  • Databases
  • Queue servers
  • Web services 

Managing External Dependencies

While developers may not control the code of these backend services, they can manage their configurations. Therefore, it is critical to assess their performance to determine if reconfiguration is needed. You will need to determine if the application's slowdown is due to problems with the application or its external dependencies.

Monitoring External Dependency Performance

Typically, an APM tool can automatically distinguish between the application and external services. Sometimes, you may be required to tweak the monitoring program to identify external dependency behavior. As with user-facing latencies, you need a baseline to measure the performance of these external dependencies. 

With a Node.js application, latency in backend services can alter performance and affect the user experience despite interfacing asynchronously. Exit call types may be:

  • External web-service APIs
  • Internal web-services
  • NoSQL servers
  • SQL databases

When you measure your application’s response times when communicating with external dependencies, you can identify problem areas and improve performance. 

9. CPU Profiling

CPU profiling allows developers to see the cost of computational tasks. High CPU usage might mean that specific tasks are computationally intensive or not optimized. For example, if a specific API endpoint for image processing consistently uses a high CPU percentage, it might need optimization or offloading to a dedicated service.

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Best Tools For Monitoring NodeJS Metrics

Alerty: NodeJS Logging

Alerty is a cloud monitoring service for developers and early-stage startups, offering:

  • Application performance monitoring
  • Database monitoring
  • Incident management

It supports technologies like NextJS, React, Vue, and Node.js, helping developers identify and fix issues. 

  • Alerty monitors databases such as Supabase, PostgreSQL, and RDS
  • Tracking key metrics like CPU usage and memory consumption
  • It features quick incident management and Real User Monitoring (RUM) to optimize user experience
  • Its universal service monitoring covers dependencies like Stripe API, OpenAI, and Vercel 

Alerty uses AI to simplify setup, providing a cost-effective solution compared to competitors. It is designed for ease of use, allowing quick setup, and integrates with tools like Sentry, making it ideal for developers and small teams needing efficient, affordable monitoring **Catch issues before they affect your users with Alerty's NodeJS logging tool today!**

Built-in Node.js Profiler

The built-in Node.js profiler is a command-line tool that allows developers to gather performance data without needing external libraries. To use it, you simply start your application with the --prof flag:

bash
node --prof app.js

This command initiates profiling, generating a log file that records stack traces of JavaScript and C/C++ code execution. After running your application under load, you can process the generated log file using:

bash
node --prof-process isolate-0x<number>-v8.log

The output provides detailed insights into function calls, execution times, and performance bottlenecks, enabling developers to pinpoint areas that require optimization. This profiler is particularly useful for identifying CPU-intensive tasks and understanding how time is spent within the application.

Chrome DevTools

Chrome DevTools offers a more visual approach to profiling Node.js applications. To get started, you need to run your Node.js application with the --inspect flag:

bash
node --inspect app.js

Once your server runs, you can open Chrome and navigate to chrome://inspect to connect to your Node.js instance. In the DevTools window, you can access the Performance tab to record a performance profile. You can simulate user interactions or load tests by clicking the record button and then stop the recording to analyze the results.

The Main section of the performance profile displays a flame chart that visualizes the call stack and time spent on each function. This allows developers to easily identify which parts of the code consume the most resources. The Bottom-Up tab provides a detailed list of function calls ordered by their execution duration, making spotting performance bottlenecks straightforwardly.

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What Are Some Best Practices to Follow?

Determine What to Monitor

Node.js metrics monitoring starts with understanding what to monitor. Key metrics such as latency, error rates, and throughput are fundamental. Identifying critical logs and events is equally crucial in directing monitoring efforts where they matter the most. Tools like Alerty can help streamline this process. 

Prioritize and Configure Alerts

Alerts are the first line of defense against potential performance issues. Categorize alerts into high-priority and low-priority types. High-priority alerts demand immediate attention, while low-priority alerts can be reviewed later. Adjust settings to identify and address urgent metrics to prevent issues quickly.

Direct Alerts to the Right Team Members

The effectiveness of an alert is not just in its timeliness but also in who receives it. When setting up notifications, especially for critical incidents, ensure they are directed to the team members equipped to handle the issue. This ensures that any raised concerns are addressed promptly and by the right expertise.

Optimize Code and Avoid Synchronous Operations

Node.js excels with its asynchronous capabilities. To utilize its full potential, developers should focus on improving their code and avoiding synchronous tasks. Keeping operations non-blocking keeps applications responsive, ensuring efficient performance and improved user experiences.

Harness Caching

Caching is crucial for fast data retrieval in Node.js applications. By storing frequently accessed data in a cache, developers can significantly reduce database loads and speed up response times. Effective caching strategies ensure a seamless user experience with reduced latency and consistently fast data access.

Stay Vigilant for Memory Leaks

Memory leaks are silent performance killers in Node.js applications that can gradually degrade system efficiency. Continuous monitoring and dedicated tools are essential for identifying and fixing these sneaky issues. Addressing memory leaks promptly ensures sustained application performance and a consistent user experience.

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Catch Issues Before They Affect Your Users with Alerty's NodeJS Logging Tool

Alerty is a cloud monitoring service tailored for developers and early-stage startups, providing a suite of tools for:

  • Application performance monitoring
  • Database tracking
  • Incident management

Comprehensive Technology and Database Support

Alerty supports a range of technologies, including NextJS, React, Vue, and Node.js, enabling developers to identify and resolve issues swiftly. One notable feature of Alerty is its support for various databases like Supabase, PostgreSQL, and RDS, where it meticulously monitors key metrics such as CPU usage and memory consumption to maintain smooth operations. 

Efficient Incident Management and User Experience Optimization

Alerty's robust incident management capabilities and Real User Monitoring (RUM) feature work to enhance user experiences by efficiently resolving potential issues before they impact end-users. The Universal Service Monitoring aspect of Alerty is particularly beneficial, covering vital dependencies such as:

  • Stripe API
  • OpenAI
  • Vercel

Alerty leverages AI to simplify the setup process, delivering a cost-effective monitoring solution compared to its counterparts in the market. 

​Universal Service Monitoring and AI-Powered Setup

The user-friendly design of Alerty enables developers and small teams to set up monitoring quickly, integrating seamlessly with tools like Sentry to streamline the entire monitoring process. With Alerty, developers can proactively address issues with their NodeJS logging, ensuring a smooth user experience and efficient operations. 

Your Partner for Optimal Performance and User Experience

Alerty is a compelling choice for teams looking for an efficient and wallet-friendly monitoring solution that promotes seamless operations and exceptional user experiences. Don't let performance bottlenecks and downtime disrupt your users' journeys – deploy Alerty's cutting-edge NodeJS logging tool today!

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