where to deploy node.js application: Popular Options Compared

where to deploy node.js application Popular Options Compared


Node.js has become a widely adopted platform for building scalable network applications using JavaScript. However, once you have a Node app ready for release, determining where and how to deploy it requires evaluating several factors from performance to cost.

This comprehensive guide explores the most popular Node deployment options available today including dedicated servers, Platform-as-a-Service (PaaS), infrastructure providers, and managed services.

By the end, you’ll have an in-depth understanding of the various solutions for deploying production-grade Node.js applications.

Overview of where to deploy node.js application

There are several ways to deploy Node apps to production, with different trade-offs:

Dedicated/VPS Servers

Provision server instances and deploy apps manually. Offers full control but requires more effort to configure and manage.

Platform-as-a-Service (PaaS)

Managed platform to deploy apps using built-in services like databases without managing infrastructure. Constrained flexibility but easy to get started.

Infrastructure-as-a-Service (IaaS)

Provides basic compute resources like VMs without higher-level management services. Balance of flexibility and convenience.

Managed Serverless

Fully managed back-end services like AWS Lambda running code in response to events. Near zero administration but vendor dependent.

Managed Containers

Hosted managed Kubernetes clusters running containerized apps. Balance automation with control over environment.

Let’s explore the leading platforms in each category in more detail for your Node deployment needs.

Dedicated and VPS Servers

Traditionally apps were deployed to single dedicated physical servers or virtual private servers (VPS) rented from providers. You obtain full root access to provision the OS, Node, web servers, databases and configure everything manually.

With dedicated servers, you control the entire software stack top to bottom. But this comes at the cost of significant effort to set up and manage especially as the app scales. VPS offers convenience of cloud instances but still requires manual configuration.

Some Node process management tools like PM2 help automate application management, restarting, clustering, and monitoring. But ultimately the burden of administering server patches, security, and reliability falls completely on your team.

When to use:

  • Maximum control over the server environment and software stack is needed
  • Ability to customize and optimize the OS and hardware for application needs
  • An experienced ops team is available for managing infrastructure

** Key providers:**

  • Amazon EC2 – Provides access to a wide array of VPS instance types
  • DigitalOcean – Developer friendly VPS plans with SSD storage
  • Linode – Fast VPS plans with public and private networking
  • OVHcloud – Baremetal dedicated servers available

For small to mid-size teams lacking substantial ops expertise, managing your own servers can be challenging. This leads to solutions that abstract infrastructure management via the cloud.

Platform-as-a-Service (PaaS)

Platform-as-a-service (PaaS) solutions provide a managed environment for deploying and running apps without managing the underlying infrastructure. The PaaS provider handles provisioning servers, installing OS and software dependencies, and maintaining the deployment environment.

This allows focusing on just the application code and business logic. Some popular Node PaaS options include:


  • Fully managed platform optimized for Node.js
  • Easy for teams to get started with Node quickly
  • Provides add-ons for databases, monitoring, and more
  • Limited flexibility and ability to customize environment

Microsoft Azure App Service

  • Managed PaaS on Azure supporting Node.js
  • Includes built-in CI/CD pipelines from GitHub etc
  • Integrates with other Azure services for cloud resources
  • Tied to Microsoft ecosystem and tooling

Google App Engine

  • Automated Node deployment and scaling
  • Integrated with Google Cloud resources and monitoring stack
  • Free tier available subject to usage quotas
  • Locked into Google’s infrastructure and services

Amazon Elastic Beanstalk

  • Automated deployment and provisioning of resources for Node on AWS
  • Integrations available for other AWS services
  • Some flexibility to customize runtime environment
  • Amazon ecosystem lock-in

PaaS provides a fantastic on-ramp for teams getting started with Node development by eliminating infrastructure burdens. But reliance on proprietary vendor ecosystems results in reduced choice and flexibility down the road.

Infrastructure-as-a-Service (IaaS)

Infrastructure-as-a-service (IaaS) strikes a balance between having control over server provisioning while automating infrastructure management.

With IaaS, you launch compute instances but the provider handles the underlying data center resources. This gives flexibility to configure your own software stack on top of the virtualized hardware.

Some popular options for Node.js IaaS:

Amazon AWS

  • Launch EC2 instances with desired OS, storage, and configuration
  • Automates data center infrastructure and hardware management
  • Flexibility to build custom solutions using cloud resources
  • Additional services like RDS and Lambda available

Microsoft Azure Virtual Machines

  • Create Windows or Linux VMs tailored for Node apps
  • Makes it easy to scale instances up and down
  • Control over instance resources and software
  • Tight integration with other Azure services

Google Compute Engine

  • Launch VMs running on Google’s computing infrastructure
  • Options for OS, machine types, GPUs and disks
  • Can create VM clusters for Node availability
  • Integrates with other GCP tools and monitoring


  • Developer-friendly infrastructure with simplified UX
  • Quickly launch Node droplets (instances)
  • VM monitoring and alerting capabilities
  • Less breadth of integrated services than hyperscalers

With IaaS, you get the convenience of automated infrastructure without excessive vendor lock-in. This offers a good middle ground between DIY servers and fully abstracted platforms.

Managed Serverless

“Serverless” platforms provide back-end services and computing without directly managing VMs or servers. Code is executed on-demand in response to events with resources provisioned automatically.

This enables focusing on business logic rather than infrastructure or resource management. Some serverless options for Node:

AWS Lambda

  • Upload Node code that runs in response to HTTP requests or other AWS events
  • Automatically scales number of executions as needed
  • Integrates seamlessly with other AWS services
  • Locked into Amazon ecosystem and services

Google Cloud Functions

  • Write Node functions that execute on GCP events
  • Server allocation and scaling is fully managed
  • Tight integration with Google Cloud services
  • Requires reliance on Google infrastructure

Azure Functions

  • Create event-driven Node functions on Azure
  • Serverless logic that can be triggered by Azure events
  • Provides abstraction over server management
  • Tied into Microsoft tools and platform

Cloudflare Workers

  • Deploy Node snippets as serverless functions on Cloudflare edge
  • Microservices with low latency due to global edge locations
  • Limited duration execution caps before recycling

Fully managed serverless accelerates development by eliminating ops concerns. But the heightened abstraction constrains ability to optimize and customize environments.

Managed Kubernetes and Containers

Containers package apps with consistent dependencies and environments, solving “it works on my machine” woes. Orchestrators like Kubernetes automate deploying and managing containers at scale.

Managed Kubernetes services provide the best of both worlds – workload portability through containers while automating operational aspects like capacity and availability management.

Some leading managed Kubernetes options for Node:

Amazon EKS

  • Managed Kubernetes control plane on AWS infrastructure
  • Supports running Node apps in Docker containers
  • Integrates with AWS load balancing and workflows
  • On-demand pricing and auto-scaling clusters

Google GKE

  • Fully managed Kubernetes on GCP virtual network
  • Docker container deployment automation
  • Cluster scaling, logging, and monitoring

Microsoft AKS

  • Automated Kubernetes cluster management on Azure
  • Rapid deployment of containerized Node workloads
  • Integration with other Azure services
  • Limited customization compared to on-prem Kubernetes

DigitalOcean Kubernetes

  • Simplified provisioning of Kubernetes clusters
  • Runs and manages containerized Node apps
  • Integrated monitoring and alerting
  • Less operational tooling than bigger providers

Managed Kubernetes strikes a potent balance, reducing ops toil through automation while still giving control over the environment. This flexibility comes at the cost of additional cluster management compared to serverless platforms.

Key Considerations for Evaluation

With the wide variety of deployment options available for Node apps, it’s important to weigh your specific needs:

  • App requirements – Consider the app architecture, cloud integrations, scalability needs etc. For example, a distributed microservices app requires different infrastructure than a simple monolithic CRUD API.
  • In-house expertise – If your team has strong DevOps skills, favor dedicated servers or IaaS. For lean teams, PaaS or serverless simplify operations.
  • Customization vs convenience – Dedicated servers provide maximum configurability while managed serverless offers least flexibility but fastest time-to-market.
  • Cost – Weigh monthly pricing of PaaS/IaaS versus upfront capex of owning dedicated hardware. Serverless costs scale directly with usage volume.
  • Scale – Some apps may outgrow PaaS platforms that limit ability to customize for growth. IaaS and containers offer more incremental scaling control.
  • Compliance – For regulated industries, evaluate services’ security, continuity, and compliance certifications against requirements.

By factoring in these aspects against business needs, you can determine the optimal Node deployment architecture.

Hybrid and Multi-Cloud Deployment

The options above are not mutually exclusive – hybrid deployments combining VMs, serverless, containers, and data centers are common for production systems.

A hybrid on-prem and cloud architecture provides flexibility to match the right workload to the best environment based on performance, scale, and operational needs.

Multi-cloud across vendors also prevents lock-in and provides redundancy against regional service disruptions. With Node’s lightweight runtime, distributing components across clouds is straightforward.

Just ensure compatibility across providers for organization identity, VPN connectivity, security controls, and monitoring/auditing.


Node’s “Develop anywhere. Deploy anywhere.” mantra holds true – apps can run across the spectrum from a Raspberry Pi to a globe-spanning AWS infrastructure.

Evaluate your capabilities, app needs, and business requirements to choose the optimal Node deployment environment today with flexibility to evolve in the future.

With cloud-based managed services eliminating the drudgery of infrastructure management, teams can focus efforts on creating amazing Node applications.

The vibrant ecosystem of deployment options ensures your next innovative Node project has a robust, scalable runtime environment to match any growth and scale needs.

Frequently Asked Questions

What is the easiest Node deployment option for beginners?

Heroku provides the simplest PaaS experience to get started with Node.

When does using dedicated servers make more sense vs the cloud?

For applications with extreme data gravity, latency, or compliance requirements.

How do managed containers compare to serverless platforms?

Containers offer more control over environment than fully abstracted serverless.

Can multiple Node deployment architectures be combined?

Yes, hybrid on-prem and multi-cloud deployments provide maximum flexibility.

How to decide between leading vendors like AWS, Azure, and GCP?

Evaluate integrations with other systems, compliance needs, discounted pricing, and global infrastructure.

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