Choosing to self-host n8n is a fantastic step towards owning your automation stack, offering unparalleled flexibility and control. But before you dive in, the most common question I hear is: “What are the right n8n server requirements?” The answer isn’t a single set of specs, but rather a spectrum that depends entirely on your use case—from simple, low-frequency tasks to complex, high-volume data processing. Generally, your primary focus should be on Memory (RAM), as n8n is more memory-intensive than CPU-intensive. A solid starting point for most users is a server with at least 2 vCPUs, 4GB of RAM, and a 40GB SSD, but this can scale up or down based on your workflow complexity, execution frequency, and data volume.
It’s Not the Server, It’s the Workflow
Let’s be honest, asking for generic server specs is a bit like asking “how big of a car do I need?” Are you just grabbing groceries, or are you helping a friend move their entire apartment? The answer, of course, is “it depends.”
Your n8n server requirements follow the same logic. A simple workflow that listens for a webhook and sends a Slack message is the equivalent of a quick trip to the store—it barely needs any room. But a workflow that downloads a 100MB CSV file, processes every row in a Code node, and then uploads a modified version to S3? That’s the cross-country move, and it’s going to need a lot more horsepower.
So, before we even talk about specs, you need to ask yourself:
- How many workflows will be active?
- How often will they run? (Every minute? Once a day?)
- What kind of data will they handle? (Simple JSON? Large binary files like images or PDFs?)
Thinking about these questions first will save you a lot of headaches (and money) down the line.
Decoding the Core n8n Server Requirements
Alright, let’s break down the three key components of your n8n server setup: the engine (CPU), the workspace (RAM), and the filing cabinet (Database).
CPU (The Engine): Surprisingly Forgiving
Here’s some good news: n8n is not particularly CPU-intensive. For the vast majority of use cases, you don’t need a beast of a processor. The main n8n process is single-threaded, so throwing more cores at it won’t magically speed up a single, long-running workflow.
Where does CPU matter? It becomes more relevant when you have many workflows running simultaneously (high concurrency). Each active execution can consume some CPU, so if you’re hitting dozens of webhooks a second, you’ll want a bit more processing power. For most people starting out, a server with 1-2 vCPUs is perfectly adequate.
Memory (RAM – The Workspace): This is Where It Counts
Pay attention here, because this is the single most important factor for a stable n8n instance. Memory is the active workspace for your workflows. When a workflow executes, n8n loads the data for each step into RAM.
This is especially critical for nodes that manipulate a lot of data. The Code node, for example, can be a memory hog because it might hold a pre-processing and a post-processing copy of your data. If you’re handling large files or massive arrays of items, this can add up fast. I once brought a 4GB RAM instance to its knees by trying to process a large financial report without batching my data. Lesson learned!
If your workflows handle binary data (like images, PDFs, or videos), your memory usage will spike significantly. Always plan for more RAM than you think you need; it’s the best investment for a reliable n8n server.
Database and Storage (The Filing Cabinet)
By default, n8n uses a simple SQLite database file, which is stored in your ~/.n8n folder. This is great for getting started quickly and for light use.
However, once you move into a production environment, I strongly recommend using PostgreSQL. It’s more robust, handles concurrent workflow executions much more gracefully, and is built for scaling. You’ll also want to ensure your server uses SSD storage, as the faster read/write speeds make the entire application feel snappier.
One crucial tip for Docker users: make sure you use a persistent volume! If you don’t, all your workflows, credentials, and execution logs will disappear the moment you restart the container. Trust me, you only make that mistake once.
Finding Your Perfect Fit: Sizing Your n8n Instance
To make this practical, I’ve broken down the requirements into three common levels. Find the one that sounds most like you.
| Use Case Level | vCPU | RAM | Storage | Example Scenarios |
|---|---|---|---|---|
| The Tinkerer / Small Project | 1-2 | 2-4 GB | 20-40 GB SSD | Running a few personal automations, low-frequency cron jobs, simple webhooks. |
| The Growing Business | 2-4 | 4-8 GB | 40-80 GB SSD | Managing several active workflows, moderate webhook traffic, some data processing. |
| The Power User / Enterprise | 4+ | 8-16+ GB | 80+ GB SSD | High-volume automation, processing large files, high concurrency, mission-critical workflows. |
A Real-World Case Study: The E-commerce Automation Server
I recently set up an n8n instance for a small e-commerce client. Their needs seemed simple: sync new Shopify orders to Google Sheets, add new customers to Mailchimp, and run a nightly sales report that gets posted to Slack.
I started them on a modest “Growing Business” server (2 vCPU, 4GB RAM). For a week, everything was perfect. But then, the nightly sales report started failing. Why? As their sales grew, the report CSV file got bigger. The workflow would download the file, and the instance would run out of memory and crash.
The Solution: We did two things. First, we upgraded the server to the next tier (4 vCPU, 8GB RAM) to provide more headroom. Second, and more importantly, we optimized the workflow. Instead of processing the whole file at once, we used the Split in Batches node to handle the sales data in manageable chunks of 500 rows at a time.
The Takeaway: Start with a reasonable estimate, but always monitor your resource usage. Often, a combination of scaling your server and optimizing your workflow is the key to a stable system.
Pro Tips for a Happy, Self-Hosted n8n
Beyond the core specs, here are a few hard-won tips from the field:
- Keep It Awake: If you’re experimenting on a local PC or Mac, make sure to disable sleep mode. A sleeping computer can’t run scheduled automations!
- Backup, Backup, Backup: Set up a simple automated backup of your
~/.n8ndirectory. This contains all your precious workflows and credentials. A simple cron job or a tool like Duplicati can be a lifesaver. - Secure with HTTPS: Don’t expose your n8n instance to the world over plain HTTP. It’s insecure. Use a reverse proxy like Caddy, Nginx Proxy Manager, or Traefik to easily add a free SSL certificate.
- Monitor Your Vitals: Keep an eye on your server’s CPU and RAM usage, especially after deploying a new, complex workflow. Most cloud providers offer simple monitoring dashboards.
Ultimately, self-hosting n8n puts you in the driver’s seat. By understanding these core requirements and planning for your specific needs, you can build a powerful, reliable automation engine that’s perfectly tailored to you.
