FME Flow: 2026.1

Prerequisites and Considerations

To deploy FME Flow with Kubernetes, you must fulfill the following prerequisites:

Install Kubernetes

Install and configure a Kubernetes cluster. To install a local (single-node) cluster, we recommend installing Docker Desktop, and following the Getting Started guide. Once installed, select Enable Kubernetes to start a single-node cluster.

Tip  Ensure sufficient CPU and memory resources are assigned to your Docker Engine, preferably higher than the default allocations. We recommend at least 4 CPUs and 8 GB memory.

Install Helm

The Helm tool is required for pulling the fmeflow Kubernetes chart.

  1. Install Helm.
  2. (Helm v2 only) Initialize it into the cluster. Run:

    3. helm init

  3. Add the fmeflow chart to the cluster:

    4. helm repo add safesoftware https://safesoftware.github.io/helm-charts/

Install NGINX

FME Flow deployments do not ship with an NGINX ingress controller container. Instead, we leverage the official nginx-ingress controller. The instructions to deploy this are here. We recommend using Helm as the simplest method:

  • Helm v2: helm install stable/nginx-ingress --name my-nginx
  • Helm v3: helm install my-nginx stable/nginx-ingress

Other Considerations

When deploying FME Flow to a Kubernetes cluster, keep in mind the following:

  • It is not possible to use the FME Flow Web User Interface to deploy FME Engines or change the number of FME Engines. For more information, see Defining FME Engines, Queue Control, and Streams to a Kubernetes Deployment.
  • Any memory or CPU limits you define on containers are ignored by all FME Flow processes. Memory and CPU limits defined on FME Engine containers are honored.
  • Pods for the FME Engines and FME Flow Core/Web Services can be scaled; no other Pods can be scaled.