Hosting your own automation platform can sound intimidating—but it doesn’t have to be. If you’ve been looking into ways to keep your workflows secure, cost-effective, and fully customizable, n8n self hosting might be the answer you’ve been searching for. Whether you’re a growing startup or a technical pro at an enterprise, this guide will walk you through everything you need to know to deploy, manage, and scale n8n in your own infrastructure.
In this guide, we’ll cover the why and how of self-hosting n8n, starting with choosing the right environment, then diving into installation methods (like Docker and Kubernetes), security considerations, scaling strategies, and real-world use cases. We’ll also share expert tips and best practices to ensure you get the most out of your n8n setup—because automation should work for you, not the other way around.
Why Choose n8n Self Hosting?
One of the biggest advantages of self-hosting n8n is control. When you self-host, your data stays within your infrastructure, which is crucial for businesses that need to meet compliance standards like GDPR. You’re not relying on third-party cloud services to handle your automated workflows—which means full ownership and no vendor lock-in.
n8n’s open-source nature also gives you incredible flexibility. Want to add custom nodes or build integrations that aren’t supported out of the box? No problem. With self-hosting, you can tinker under the hood as much as necessary to tailor the platform to your business logic or development pipeline. Plus, self-hosting can be more cost-effective over time, especially if you’re running multiple workflows or need higher execution limits.
Requirements and Environment Planning
Before spinning up your self-hosted instance, it’s important to map out a solid foundation. First, determine your hosting environment: cloud (like AWS or DigitalOcean) or on-premises servers. Each option has pros and cons. Cloud is flexible and scalable, while on-prem offers deeper control and potentially lower long-term costs.
As a baseline, plan for at least 2 vCPUs, 4 GB of RAM, and 20 GB of storage. For more demanding environments, especially those running complex or data-heavy workflows, aim for 8 GB RAM and multiple CPU cores. PostgreSQL should be your go-to database engine in production scenarios—it’s proven, reliable, and scalable.
Deployment Methods: Docker vs Kubernetes
Docker: The Easiest Way to Get Started
If you’re just experimenting or want a quick setup, Docker Compose is your best friend. This method is straightforward, portable, and widely supported. You can have a full n8n stack (including PostgreSQL) up and running in minutes. It’s perfect for small teams or solo developers who want to try self-hosting with minimal friction.
Kubernetes: For Scale and Resilience
For production-grade setups or when you’re managing multiple instances, Kubernetes shines. It allows for advanced orchestration, autoscaling, and fault tolerance. Using Helm charts, you can deploy n8n into clusters and manage configurations centrally. While it does have a learning curve, Kubernetes is the way to go if you’re building business-critical automation infrastructure.
Database Considerations: PostgreSQL vs SQLite
SQLite is great for development or tiny internal apps, but it lacks the performance and concurrency needed in production. PostgreSQL offers robust transaction handling, better scalability, and compatibility with queue processing and clustered workloads. Migrating from SQLite to PostgreSQL is possible, and n8n provides utilities for data export and schema migration.
Securing Your Self-Hosted n8n
Authentication and Authorization
Out of the box, n8n supports basic authentication via username and password. For enterprise security, you can integrate LDAP, Active Directory, or OAuth2 providers like Google. These integrations ensure that only trusted users access your workflows, and they support single sign-on.
Network Security Best Practices
Always run n8n behind a reverse proxy like Nginx or Traefik, which handles HTTPS, headers, and firewall rules. This setup protects your instance against common attacks and simplifies TLS configuration. For internal communications, especially with Redis or PostgreSQL, use secure VPC networking or mutual TLS where possible.
Scaling Your Workflows with Queue Mode
Once your workflow volume grows, or you start hitting concurrency limits, it’s time to scale. Enter queue mode. This lets n8n offload executions into a Redis queue, where dedicated workers process them asynchronously. You can add or remove workers based on CPU usage or queue length using Kubernetes autoscaling. This setup keeps your UI responsive and your workflows humming along smoothly.
Monitoring and Observability
Keep an eye on your system’s health using Prometheus and Grafana. With a simple configuration, n8n exposes helpful metrics like memory usage, execution times, and event loop delays. Custom Grafana dashboards can highlight workflow bottlenecks and help you plan for future scaling.
Backup and Disaster Recovery
Plan for the worst: always back up your workflows and execution logs. n8n allows you to export workflows as JSON files. Combine this with a nightly cron job or automation that syncs exports to cloud storage solutions like AWS S3 or Google Cloud Storage. Regular test restores are also a smart move—backups are only as good as your ability to use them in a crisis.
Advanced Use Cases: Local AI and Embedded SaaS
One powerful use case is running local AI models like Ollama and integrating them with n8n using custom nodes. This allows for AI-powered document processing, chatbots, or analytics—all within your infrastructure. Another advanced scenario is multi-tenancy via Kubernetes namespaces, enabling software vendors to offer white-label SaaS built on n8n.
Keeping Your Instance Updated
Use version tags when pulling Docker images or Helm charts. Avoid relying on the latest tag, as it may introduce breaking changes. Implement a CI/CD strategy that includes canary deployments or rolling updates. This allows you to quickly roll back if a new version causes issues.
Common Pitfalls and How to Avoid Them
One of the biggest mistakes is skipping TLS—always secure your instance, even for internal-only use cases. Another is over-relying on SQLite for production workloads. Finally, don’t forget to configure persistent volumes for your workflows and files. Losing your flow.json file means losing your automation history.
Real-World Example: A Two-Mation Success Story
At Two-Mation, we helped a client self-host n8n to automate their entire onboarding process—integrating Slack, Google Workspace, and internal APIs. Using queue mode and Kubernetes autoscaling, they reduced onboarding time by 60% and eliminated manual steps entirely. Better still, they maintain full control over sensitive employee data, helping them meet compliance standards with ease.
Conclusion: Is n8n Self Hosting Right for You?
Self-hosting n8n is a powerful path for businesses that want more control, scalability, and customization in their automation stack. With Docker, Kubernetes, and advanced features like queue mode, you can build a robust platform that grows with your needs. Whether you’re a startup securing sensitive customer data or an enterprise looking for AI-enhanced workflow orchestration, n8n gives you the tools—and the freedom—to automate smarter.
If you’re ready to level up your automation infrastructure, Two-Mation can help. We offer hands-on setup, optimization, and managed hosting for n8n tailored to your business goals. Let’s build automation that scales as fast as you do.
Frequently Asked Questions
1. What is n8n self hosting?
n8n self hosting means running the n8n automation platform on your own servers or cloud infrastructure instead of using n8n’s cloud service. This gives you more control over data, security, and customization.
2. Is n8n free for self hosting?
Yes, n8n is open-source and free to use under the Fair-code license. However, certain advanced features may be reserved for enterprise users. For most businesses, the free version is more than enough.
3. Can I scale n8n for high workloads?
Absolutely. n8n supports queue mode, which lets you scale workflow execution using Redis and multiple worker nodes. Combine this with Kubernetes autoscaling for dynamic load handling.
4. What are the hardware requirements?
For light workloads, 2 vCPUs and 4 GB RAM will suffice. For production or high-volume use, consider 4–8 vCPUs and 8+ GB RAM, especially if you’re using AI models or complex integrations.
5. How do I back up my n8n instance?
Backups can be created by exporting workflows to JSON and syncing database volumes or snapshots. Automating this process with scheduled jobs ensures disaster recovery readiness.
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