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Use a local registry with KinD

Note: This feature is included for OpenFaaS Standard & For Enterprises customers.

Whilst a remote registry is the easiest way to get started when developing functions, a local registry can be faster for development and testing.

Using a local registry is an optimisation, which requires some additional tooling and configuration.

You can also test your functions using Docker without deploying them to OpenFaaS via the local-run command, learn more: The faster way to iterate on your OpenFaaS functions.

You can find similar solutions for other local Kubernetes distributions:


You need to have Docker installed on your machine, arkade is also recommended for installing the necessary tools, however you can install them manually if you prefer.

Install arkade

We will use arkade to install and deploy apps and services to Kubernetes.

# Download only, install yourself with sudo
$ curl -sLS | sh

# Download and install
$ curl -sLS | sudo sh

arkade commands:

  • use arkade get to download CLI tools and applications.
  • use arkade install to install applications using helm charts or vanilla YAML files.
  • use arkade info to get back info about an app you've installed

Install kubectl

kubectl is a command line tool that talks to the Kubernetes API for performing actions on our cluster.

$ arkade get kubectl

Create the KinD cluster with a local registry enabled

We will set up our local Kubernetes cluster using KinD (Kubernetes in Docker).

Install KinD

These instructions are adapted from the KinD documentation. Our goal is to run Kubernetes using Docker, along with a built-in registry.

The example below was copied from the KinD documentation.

Save as

set -o errexit

# 1. Create registry container unless it already exists
if [ "$(docker inspect -f '{{.State.Running}}' "${reg_name}" 2>/dev/null || true)" != 'true' ]; then
  docker run \
    -d --restart=always -p "${reg_port}:5000" --network bridge --name "${reg_name}" \

# 2. Create kind cluster with containerd registry config dir enabled
# TODO: kind will eventually enable this by default and this patch will
# be unnecessary.
# See:
# See:
cat <<EOF | kind create cluster --config=-
kind: Cluster
- |-
    config_path = "/etc/containerd/certs.d"

# 3. Add the registry config to the nodes
# This is necessary because localhost resolves to loopback addresses that are
# network-namespace local.
# In other words: localhost in the container is not localhost on the host.
# We want a consistent name that works from both ends, so we tell containerd to
# alias localhost:${reg_port} to the registry container when pulling images
for node in $(kind get nodes); do
  docker exec "${node}" mkdir -p "${REGISTRY_DIR}"
  cat <<EOF | docker exec -i "${node}" cp /dev/stdin "${REGISTRY_DIR}/hosts.toml"

# 4. Connect the registry to the cluster network if not already connected
# This allows kind to bootstrap the network but ensures they're on the same network
if [ "$(docker inspect -f='{{json .NetworkSettings.Networks.kind}}' "${reg_name}")" = 'null' ]; then
  docker network connect "kind" "${reg_name}"

# 5. Document the local registry
cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: ConfigMap
  name: local-registry-hosting
  namespace: kube-public
  localRegistryHosting.v1: |
    host: "localhost:${reg_port}"
    help: ""

View the shell script in the KinD docs

The below will create a cluster named kind using the script from above, with a registry pre-installed:

$ chmod +x ./
$ ./

Make sure the kubectl context is set to the newly created cluster:

$ kubectl config use kind-kind

Make sure the cluster is running:

$ kubectl cluster-info

Make sure Docker registry is running.

$ docker logs -f kind-registry

Deploy OpenFaaS Standard or OpenFaaS For Enterprises

Deploy one of the OpenFaaS Pro editions along with faas-cli:

$ arkade get faas-cli

Follow the documentation to install OpenFaaS Pro with helm.

Or you can use arkade:

$ arkade install openfaas --license-file ~/.openfaas/LICENSE

Then log in and port-forward OpenFaaS using the instructions given, or run arkade info openfaas to get them a second time.

Create a Function

We will take an example of a simple function; a dictionary that returns the meaning of word you query. We will be using the PyDictionary module for this setup.

Pull python language template from store:

$ faas-cli template store pull python3-flask

We will be using the python3-flask-debian template.

Setup your OPENFAAS_PREFIX variable to configure the address of your registry:

export OPENFAAS_PREFIX=localhost:5001

Note: Docker for Mac users may need to change "localhost" to the IP address of their LAN or WiFi adapter as shown on ifconfig such as

Create a new function using the template:

$ export FN=pydict
$ faas-cli new $FN --lang python3-flask-debian

This will create a directory for your function and a YAML config file with the function name you provided:

  • pydict/
  • pydict.yml

Add dependency to the pydict/requirements.txt file:

cat <<EOF > pydict/requirements.txt

Update with the following code.

from PyDictionary import PyDictionary

dictionary = PyDictionary()

def handle(word):     
    return dictionary.meaning(word)

Our minimal function is complete.

Stack file

You will see that the OpenFaaS stack YAML file pydict.yml has localhost:5001 in its image destination.

version: 1.0
  name: openfaas
    lang: python3-flask-debian
    handler: ./pydict
    image: localhost:5001/pydict:latest

Build Push Deploy

With our setup ready; we can now build our image, push it to the registry, and deploy it to Kubernetes. And using faas-cli it is possible with a single command!

faas-cli up -f pydict.yml

Test the function

We can invoke our function from CLI using faas-cli or curl.

$ echo "advocate" | faas-cli invoke pydict

{"Noun":["a person who pleads for a cause or propounds an idea","a lawyer who pleads cases in court"],"Verb":["push for something","speak, plead, or argue in favor of"]}

Watch for changes

You can also watch for changes in the function's source-code and automatically rebuild and deploy the function.

faas-cli up -f pydict.yml --watch --tag=digest

Now edit the source code for the function, and watch it get rebuilt and deployed automatically.

Wrapping Up

Now that you have a local registry, you can speed up your local development of functions by keeping the container images within your local computer.

This tutorial is based upon the KinD docs and a post by Yankee Maharjan.