Top Node.js Monitoring Tools

February 1, 2021

Often, applications may not work as efficiently as they should. This responsibility of carrying out preventive and curative maintenance lies on application developers. Customers using your application as a developer may spend a lot of money trying to repair the applications without your guidance. It would be best to have an effective monitoring solution to keep track of your application’s behavior.

Node.js monitoring

Node.js monitoring involves closely keeping track of an application’s performance and availability. Developers do this by finding bugs and fixing errors. Node.js monitoring uses application performance management (APM) tools to watch over apps. APM is an essential tool when monitoring and optimizing the performance of apps.

This article shows you what you should monitor in Node.js and explains various Node.js monitoring tools.

What you should monitor

1. Log management

Log management entails information about the application lifecycle regulation with service-level logs. Logs help you all through the follow-up process. Whether it is troubleshooting existing issues or planning new features, log agents enable you to capture server logs.

Database logs, application logs, and infrastructure logs impact users. Logs helps in supporting APM with infrastructure-level logs.

In Node.js, you may need to carry out a performance, debugging, error tracking, and analysis logging.

2. Request rate

You’re responsible for understanding the amount of traffic your application generates. This is a key performance index for an application’s success. This metric binds the other metrics since they all hinge on the frequency of traffic.

Knowing the dynamics that affect how your application scales is important. It keeps you aware of the rate of correlation with monitoring. At this point, tracking concurrent users cannot be emphasized enough.

3. Application availability

It is equally important to verify, monitor, and measure whether your application is online. Most companies use this method to determine uptime for service level agreements.

With a web application, you can check availability using a scheduled HTTP check. Retrace, a Stackify monitoring tool has the potential to run such HTTP ping checks every minute if needed.

4. Resource use

Adequate optimization of services helps manage resources more effectively. This helps reduce costs and lower latencies. So, choosing the best APM tool is the starting point in the right direction.

Eliminating technical defects reduces the need to scale up application architecture whenever traffic increases. Monitoring the CPU memory use is a vital step towards sustaining optimal traffic.

5. Downtime and system health

Frequent unsolicited downtime for an application can be costly. It is essential to have a monitoring solution that scrutinizes system behavior. This helps you make timely adjustments to avoid downtime. Thus, frequent and continuous improvement enables you to establish trust with your customers.

6. Error rates and handling

For prompt error handling, you need an APM monitoring solution. Such a tool informs you of recurring error codes from 4XX/5XX status codes, runtime errors, and application crashes. 5xx status codes are designed for instances where the server is aware that it is incapable of executing the requested method or has erred. 4xx codes are for the cases where the client seems to have erred.

It would be best if you never relied on your developers or users to do the troubleshooting for you.

7. Latency

Slow servers in applications make customers impatient. It has been argued that customers spend less than three seconds on a slow loading page. To control this attrition by customers, make sure you collect data on a service level. There are several APIs that can help you ensure complete latency analysis for each of the services.

Node.js monitoring tools

App Metrics

App Metrics has an application dashboard that indicates the performance metrics of running Node.js application. It is easy to use the module. All you need is to install it and place it at the top of the main Node.js source file.

App Metrics is an open-source project developed and serviced by IBM. It is primarily focused on providing the template for excellent application metrics spread across various tasks. These tasks include network speed, data transaction, database query performance, CPU and memory use, and garbage collection.

With vital tools like appmetrics-dash, App Metrics provides an excellent web interface to monitor applications. App Metrics can also be used as middleware to build a monitoring application making it one of the top tools for Node.js performance testing.


Stackify’s Retrace is an application performance management tool that helps developers check for bugs during app development and provides quality analysis. It ensures apps are performing and meeting the needs for which they were designed, by administering deployments. The monitoring solution supports PHP, Ruby, Node.js, Python, Java, and .NET applications.


PM2 helps you run applications in Node.js much easier. As a process manager, it lets you run apps in cluster mode. Expert developers utilize PM2 in running live production workloads and monitoring the same from a web interface.

One of PM2’s top features is web interface integration for application health monitoring. Others are application and error log management, hot-reload, log streaming, and auto-clustering. Most importantly, it helps with the management of multiple Node.js applications.


To create a Prometheus-data directory, you first have to navigate to the Node.js application’s root directory. Once you’ve done this, run the Prometheus Docker container. Since the Prometheus container is running, you can add the needed configuration in your Node.js application.


The best feature that Clinic.js has is its high performance capabilities with no downtime. It assures users a predictable resource usage and the ability to scale effectively based on load. It helps users visualize what is going on inside the node process. It is time-saving.

Clinic.js is an open-source library combining three essential tools in Bubbleprof, Flame, and Doctor. It works efficiently for Node.js-based application after integration. Clinic.js can troubleshoot symptoms like low CPU usage, frequent event loop delay, garbage blocking, and a misleading number of active handles, that may indicate several potential problems.


AppSignal introduces great performance monitoring and error tracking to the Node.js ecosystem. AppSignal supports JavaScript applications, TypeScript applications, and several frameworks and packages with selected plugins. AppSignal was specially designed to use on a server.

Express Status Monitor

As a JS developer, managing your server is crucial. GitHub, an Express Status monitor library, helps developers take full control whenever there is an error or overload on the server. It is an open-source tool that monitors Express.js, which is one of the most popular framework used in Node.js.

With Express Status Monitor, it is possible to regulate response times, request frequency, status code, average overload, and CPU utilization.


When it comes to application availability and other vital metrics, developers cannot simply wish monitoring away. The cost of development is skyrocketing, and custom-designs after an application is released can be an uphill task. As such, developers have to fully utilize these application performance management tools to reduce time wastage. This article has gone a long way to discussing top Node.js monitoring tools to help you in selecting the best monitoring solution.

Peer Review Contributions by: Linus Muema

About the author

Eric Kahuha

Eric is a data scientist interested in using scientific methods, algorithms, and processes to extract insights from both structural and unstructured data. Enjoys converting raw data into meaningful information and contributing to data science topical issues.

This article was contributed by a student member of Section's Engineering Education Program. Please report any errors or innaccuracies to