Best practices for deploying n8n in a Kubernetes cluster using Terraform on GCP

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Best practices for deploying n8n in a Kubernetes cluster using Terraform on GCP

Hi everyone,

I’m working on deploying n8n in a Google Cloud Platform (GCP) environment, using Terraform to provision and manage infrastructure, and running n8n within a Kubernetes cluster (GKE).

I’m looking for best practices or recommended architecture patterns for this setup. Specifically:

  • How should I structure the Terraform modules to handle GKE, networking, and n8n configuration?
  • What’s the recommended way to handle persistent storage (e.g., for workflows and execution data)?
  • Any tips for scaling, security, and upgrades when running n8n in Kubernetes?
  • Should I use Helm charts, or is there a better deployment approach?
  • Any example configurations or GitHub repositories that demonstrate good practices?

My goal is to have a robust, maintainable, and production-ready setup that can scale with demand.

Any guidance or examples from your experience would be greatly appreciated.

Thanks in advance!
— Michel

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hello @Michel_Klingler

Why do you need Kubernetes? It’s a very complex solution for such a small n8n

We have n8n on an AWS EC2 instance as a Docker container. It flawlessly works with about 10-15k executions per day. For a more complex scenario, we may use multiple instances.

And it’s very cheap and easy to use via Terraform in comparison to other containerized options

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Just for maintenance and ease of deployment, we where looking for a more robust solution.

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