Optimizing Load Balancing Strategies for Scalable Node.js Applications Using PM2 Monitor

By: Himanshu Tiwari, International Center for AI and Cyber Security Research and Innovations (CCRI), Asia University, Taiwan, nomails1337@gmail.com


This study investigates the incorporation of PM2 Monitor, a commonly utilized process manager for Node.js applications, into load balancing algorithms with the aim of enhancing the performance and scalability of online applications. Load balancing is a critical component in the distribution of incoming traffic over several servers or instances, hence assuring the reliability and fault tolerance of the system. Node.js, renowned for its event-driven architectural design, is widely favoured as a framework for constructing web applications that can efficiently handle large-scale demands. By utilizing the capabilities of PM2 Monitor, we conduct an examination of the installation of several load balancing methods and evaluate their effects on performance and resource use. The objective of this study is to offer practical knowledge and recommendations for the efficient scaling of Node.js applications, taking into account crucial aspects such as performance, scalability, and fault tolerance. By conducting experiments and performing research, we assess the trade-offs associated with various load balancing solutions in order to enable informed decision- making in the realm of web application development.


In the current digital age, where online services and applications have become an integral part of our daily existence, it is crucial to ensure their accessibility, scalability, and dependability. Load balancers are essential components of the modern IT infrastructure at this point. Load balancers play a crucial role in efficiently distributing network traffic across multiple servers or resources in order to optimize performance, increase fault tolerance, and enhance the user experience overall.

Imagine a prominent e-commerce website or social media platform that is simultaneously accessed by millions of users. Without load balancing, a single server would endure the brunt of this heavy traffic, resulting in sluggish response times, possible system failures, and a poor user experience. Load balancers, on the other hand, function as traffic managers, intelligently distributing incoming requests across a cluster of servers so that no single server becomes overloaded.

Contemporary web applications encounter the formidable task of effectively managing escalating user traffic while simultaneously upholding optimal performance, dependability, and resilience. Load balancing is an essential element of web architecture since it effectively tackles these difficulties by evenly spreading incoming requests among different servers or instances. In the present scenario, Node.js [1] has garnered significant acclaim as a framework for constructing scalable online applications, owing to its non-blocking, event-driven architectural design.

In order to optimize the scalability and performance of Node.js applications, developers frequently employ tools such as PM2 (Process Manager 2). PM2 provides critical functionalities for managing Node.js applications in a production environment, encompassing process clustering [2] and monitoring capabilities via PM2 Monitor. The objective of this study is to examine the incorporation of PM2 Monitor into load balancing techniques in order to enhance the performance of Node.js applications.

What is Load balancer

Fig 1. Load Balancer

A load balancer is an essential component of network infrastructure that mediates between incoming network traffic and a cluster of servers or resources. Its primary objective is to distribute network traffic across these servers in a balanced and efficient manner to ensure optimal resource utilization, maximize availability, improve scalability, and enhance the overall performance and dependability of applications and services.

Here are some essential characteristics and functions of load balancers:

  1. Traffic Distribution: Load balancers distribute incoming requests, including web page requests, API calls, and network connections, uniformly across multiple servers. This prevents any single server from becoming overloaded, which could result in sluggish response times or service interruptions.
  2. High Availability: Load balancers can detect server failures or unresponsive resources and automatically route traffic to healthy servers. This guarantees that the system will continue to function even if some servers experience problems.
  3. Scalability: Load balancers make it easier to horizontally scale resources by adding more servers to the cluster. As traffic increases, more servers can be added to handle the load, and the load balancer will also distribute traffic to the new servers.
  4. Session Persistence: In certain circumstances, it is essential to maintain a user’s session continuity. Load balancers can be configured to always direct a user’s requests to the same server, preserving their session state.
  5. Health Monitoring: Load balancers continuously monitor the health of servers by sending periodic health-check requests. If a server fails to respond or meets specific failure criteria, the load balancer may remove it from rotation until it recovers.
  6. Security: By acting as a barrier between the internet and internal servers, load balancers can provide an additional layer of security. They can perform tasks such as SSL termination, thereby protecting servers from certain types of attacks.
  7. Traffic Management: Load balancers can be configured to prioritise certain types of traffic, apply access control rules, and perform content-based routing to ensure that various request types are handled appropriately.

PM2 Process Manager:

  1. Process Management:
    • PM2 makes it easier to deploy and manage Node.js processes.
    • It can effectively manage Node.js applications by starting, stopping, and restarting them as processes.

2.     Real-Time Monitoring:

  • It offers real-time monitoring of resource usage, including CPU and memory usage, as well as application status.

3.     Process Clustering and Load Balancing:

  • Create multiple instances of your application using PM2’s Process Clustering and Load Balancing feature.
  • It distributes incoming requests equally among these instances and restarts crashed ones automatically.

4.     Process Configuration:

  • It enables ecosystem configuration files or JSON configuration of applications, making it simpler to manage settings consistently across various environments.

5.     Startup Scripts and System Integration:

  • It has the ability to produce startup scripts for a number of init systems.
  • It makes sure that programs launch automatically when the server boots, improving dependability.
Fig 2. How PM2 works in production environment [5]

·       Simplified Node.js Process Management:

  • The diagram illustrates how PM2 simplifies the management of Node.js processes.
  • Multiple Node.js applications can be effortlessly started, stopped, and restarted, which simplifies deployment and administration.

·       Built-in Log Management:

  • it includes robust log management features.
  • It is capable of capturing application logs, including standard output and error streams, and facilitates log rotation for effective file size and retention management.

·       Comprehensive Performance Metrics:

  • it collects and displays a vast array of performance metrics, such as CPU and memory utilization, request response times, and error logs.
    • These metrics can be accessed through an integrated dashboard or integrated with external monitoring tools.

How PM2 Works :

Fig 3. Flowchart to explain the process of PM2

The explanation of the Flowchart:

  1. Starting off: The process begins by initiating a Node.js application with PM2.
  2. Start Node.js Application: PM2 launches the Node.js application specified as a managed process.
  3. Monitor Application: PM2 continuously monitors the health and performance of the application.
  4. Is Application Running? : PM2 determines whether or not the Node.js application is running.
  5. If the application is operating normally, PM2 will continue to monitor it.
  6. No. If the application has stopped or crashed, PM2 restarts it automatically.
  7. Application Restart: PM2 restarts the application to ensure that it is operational.
  8. Stop Application: If you command PM2 to stop the application explicitly, the process will be terminated.
  9. Application Stopped: The process is complete once the application is stopped.
Fig 4. Implementing RabbitMQ with PM2 [6].

This diagram depicts the fundamental lifecycle of a Node.js application managed by PM2. Node.js applications in production environments rely heavily on the monitoring and automatic restarting capabilities of PM2.

Messaging facilitates the connectivity and scalability of software applications. It allows applications to interact, form larger systems, and interface with user devices and data. By segregating the data transmission and reception processes, asynchronous messaging effectively decouples applications.

This concept incorporates a variety of scenarios, including data delivery, non-blocking operations, push notifications, and the use of messaging patterns such as publish/subscribe, asynchronous processing, and work queues.

RabbitMQ [7] functions as an intermediary during the messaging process in its capacity as a messaging broker. It facilitates the exchange of messages between applications and assures their secure storage until they are received.

This system serves two fundamental purposes:

This application is liable for message dissemination. These messages are transmitted to the RabbitMQ Broker, which manages message queues for services that have subscribed for specific message types. Consumers are applications that have subscribed to the Broker and desire to consume messages from the corresponding message queues.

Stress Test:

Fig 5. Stress test to check capabilities of PM2

As evident from the table above, it is apparent that the stress test assists us in effectively distributing the load between instance ID 1 and instance ID 2 through the utilization of pm2 in cluster mode.


This research concludes by optimizing load balancing strategies for scalable Node.js applications utilizing the PM2 Monitor. Load balancing is essential for distributing incoming traffic and ensuring system fault tolerance and reliability. Node.js, with its event-driven architecture, is a popular choice for developing web applications that can handle large-scale demands, and PM2 offers useful features for managing Node.js processes in production environments.

The goal of the project is to provide developers and system administrators with practical guidance by conducting experiments, collecting performance data, and comparing various load balancing techniques. The objective is to empower decision-makers in web application development with tools to improve performance, scalability, and robustness in Node.js applications.

PM2 simplifies Node.js process management, provides real-time monitoring, supports process clustering and load balancing, and integrates with a wide range of init systems and logging solutions. The study also introduces RabbitMQ as a messaging broker to facilitate Node.js application communication and scalability.

This research contributes to the understanding of load balancing in contemporary web application architecture and provides actionable insights for optimizing the performance of Node.js applications in real-world scenarios by investigating the incorporation of PM2 Monitor into load balancing algorithms.


  1. Node.js,” [Online]. Available: https://nodejs.org/en/.
  2. Clustering,” [Online]. Available: https://nodejs.org/api/cluster.html.
  3. Wu, B., & Jin, Z. (2015). Research on Load Balancing Strategy of Standalone Multi-core Cluster based on Node.js. Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics. https://doi.org/10.2991/icmii-15.2015.152
  4. A. Sterling, “NodeJS and Angular Tools for JSON-LD,” 2019 IEEE 13th International Conference on Semantic Computing (ICSC), Newport Beach, CA, USA, 2019, pp. 392-395, doi: 10.1109/ICOSC.2019.8665625.
  5. Iduwe, B. (2021, November 5). Load balancing your NodeJS app with NGINX and PM2. Medium. https://bencoderus.medium.com/load-balancing-your-nodejs-server-with-nginx-and-pm2-8095f558da2e
  6. M. (2020, July 10). Take Advantage of Node.js Cluster and child processes with PM2, RabbitMQ, Redis and Nginx. Medium. https://medium.com/beyond-coding/take-advantage-of-node-js-cluster-and-child- processes-with-pm2-rabbitmq-redis-and-nginx-c83eccfb8af8
  7. Forti, S., Bisicchia, G., & Brogi, A. (2022, February 11). Declarative continuous reasoning in the cloud-IoT continuum. Journal of Logic and Computation, 32(2), 206–232. https://doi.org/10.1093/logcom/exab083
  8. Shakeel, H., & Alam, M. (2022). Load balancing approaches in cloud and fog computing environments: a framework, classification, and systematic review. International Journal of Cloud Applications and Computing (IJCAC), 12(1), 1-24.
  9. Elrotub, M., Bali, A., & Gherbi, A. (2021). Sharing VM resources with using prediction of future user requests for an efficient load balancing in cloud computing environment. International Journal of Software Science and Computational Intelligence (IJSSCI), 13(2), 37-64.
  10. Singh, A., & Kumar, R. (2021). A two-phase load balancing algorithm for cloud environment. International Journal of Software Science and Computational Intelligence (IJSSCI), 13(1), 38-55.
  11. Sissodia, R., Rauthan, M. S., & Barthwal, V. (2022). A Multi-Objective Adaptive Upper Threshold Approach for Overloaded Host Detection in Cloud Computing. International Journal of Cloud Applications and Computing (IJCAC), 12(1), 1-14.
  12. Akram, W., Najar, Z., Sarwar, A., & Reshi, I. A. (2022). Fog Computing for Delay Minimization and Load Balancing. International Journal of Cloud Applications and Computing (IJCAC), 12(1), 1-16.

Cite As:

Tiwari H. (2023) Optimizing Load Balancing Strategies for Scalable Node.js Applications Using PM2 Monitor, Insights2Techinfo, pp.1

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