Version: 1.13.x

Deploy the Langflow production environment on Kubernetes

The Langflow runtime Helm chart is tailored for deploying applications in a production environment. It is focused on stability, performance, isolation, and security to ensure that applications run reliably and efficiently.

warning

For security reasons, the default Langflow runtime Helm chart sets readOnlyRootFilesystem: true. This setting prevents modifications to the container's root filesystem at runtime, which is a recommended security measure in production environments.

If readOnlyRootFilesystem is disabled (false), it degrades your deployment's security posture. Only disable this setting if you understand the security implications and you have implemented other security measures.

For more information, see the Kubernetes documentation.

Prerequisites

Install the Langflow runtime Helm chart

Add the repository to Helm:

helm repo add langflow https://langflow-ai.github.io/langflow-helm-charts
helm repo update

Create the langflow namespace and generate a superuser password and API key:

kubectl create namespace langflow
export LANGFLOW_SUPERUSER_PASSWORD=$(openssl rand -base64 32)
export LANGFLOW_API_KEY=$(openssl rand -hex 32)
kubectl create secret generic langflow-auth \
  --namespace langflow \
  --from-literal=LANGFLOW_SUPERUSER_PASSWORD="$LANGFLOW_SUPERUSER_PASSWORD" \
  --from-literal=LANGFLOW_API_KEY="$LANGFLOW_API_KEY"

Store both generated values securely.

Download the chart's default configuration:

helm show values langflow/langflow-runtime > langflow-values.yaml

In langflow-values.yaml, add these entries to the existing env list:

  - name: LANGFLOW_AUTO_LOGIN
    value: "false"
  - name: LANGFLOW_SUPERUSER_PASSWORD
    valueFrom:
      secretKeyRef:
        name: langflow-auth
        key: LANGFLOW_SUPERUSER_PASSWORD
  - name: LANGFLOW_API_KEY_SOURCE
    value: "env"
  - name: LANGFLOW_API_KEY
    valueFrom:
      secretKeyRef:
        name: langflow-auth
        key: LANGFLOW_API_KEY

Keep the existing entries in the list. For more information, see API keys and authentication.

Install the Langflow app with your configuration in the langflow namespace.
- Install chart with custom image
- Install chart and download flow
If you have a custom image with packaged flows, you can deploy Langflow by overriding the default values.yaml with the --set flag:
helm install my-langflow-app langflow/langflow-runtime \ --namespace langflow \ --values langflow-values.yaml \ --set image.repository=myuser/langflow-hello-world \ --set image.tag=1.0.0
Install the chart and download flows from a URL with the --set flag:
helm install my-langflow-app-with-flow langflow/langflow-runtime \ --namespace langflow \ --values langflow-values.yaml \ --set 'downloadFlows.flows[0].url=https://raw.githubusercontent.com/langflow-ai/langflow/dev/tests/data/basic_example.json'
If your shell requires escaping square brackets, modify the --set path as needed. For example, --set 'downloadFlows.flows\[0\].url=https://raw.githubusercontent.com/langflow-ai/langflow/dev/tests/data/basic_example.json'.
Check the status of the pods:
```
kubectl get pods -n langflow
```

Access the Langflow runtime

Get your service name:
```
kubectl get svc -n langflow
```
The service name is your release name suffixed by -langflow-runtime. For example, if you used helm install my-langflow-app-with-flow, then the service name is my-langflow-app-with-flow-langflow-runtime.

Enable port forwarding to access Langflow from your local machine:

kubectl port-forward -n langflow svc/my-langflow-app-with-flow-langflow-runtime 7860:7860

Confirm you can access the API by calling http://localhost:7860/api/v1/flows/ with the API key generated during installation:
```
curl -v \
  --header "x-api-key: $LANGFLOW_API_KEY" \
  http://localhost:7860/api/v1/flows/
```
A successful request returns a list of flows.

Run a packaged flow. The following example gets the first flow ID from the flows list, and then runs the flow:

# Get flow ID
id=$(curl -s \
  --header "x-api-key: $LANGFLOW_API_KEY" \
  "http://localhost:7860/api/v1/flows/" | jq -r '.[0].id')

# Run flow
curl -X POST \
    "http://localhost:7860/api/v1/run/$id?stream=false" \
    -H 'Content-Type: application/json' \
    -H "x-api-key: $LANGFLOW_API_KEY" \
    -d '{
      "input_value": "Hello!",
      "output_type": "chat",
      "input_type": "chat"
    }'

Configure secrets and environment variables

Use the env section of the Langflow runtime Helm chart's values.yaml file to define environment variables for your Langflow deployment. This includes built-in Langflow environment variables, as well as global variables used by your flows.

Langflow can source global variables from your runtime environment, such as Kubernetes secrets referenced in values.yaml. For example, the Langflow runtime Helm chart's example flow JSON uses a global variable that is a secret. If you want to run this flow in your Langflow deployment on Kubernetes, you need to include the secret in your runtime configuration.

tip

When you export flows as JSON files, it's recommended to omit secrets. Whether or not a secret is included depends on how you declare the secret in your flow and whether you use the Save with my API keys option. For more information, see Import and export flows.

Set secrets

Kubernetes secrets are the recommended way to store sensitive values and credentials.

Use secretKeyRef to reference a Kubernetes secret in values.yaml:

env:
  - name: OPENAI_API_KEY
    valueFrom:
      secretKeyRef:
        name: openai-credentials
        key: openai-key

Create and set secrets with kubectl and helm

You can use kubectl and helm commands to create and set secrets:

Create a secret:

kubectl create secret generic openai-credentials \
  --namespace langflow \
  --from-literal=OPENAI_API_KEY=sk...

Verify the secret exists:

kubectl get secrets -n langflow openai-credentials

The result is encrypted.

Add the following entry to the existing env list in langflow-values.yaml:

  - name: OPENAI_API_KEY
    valueFrom:
      secretKeyRef:
        name: openai-credentials
        key: OPENAI_API_KEY

Upgrade the Helm release:

helm upgrade my-langflow-app langflow/langflow-runtime \
  --namespace langflow \
  --values langflow-values.yaml

Set the log level and other configuration variables

For non-sensitive variables, such as LANGFLOW_LOG_LEVEL, you can set the value directly in values.yaml:

env:
  - name: LANGFLOW_LOG_LEVEL
    value: "INFO"

Configure scaling

Use replicaCount and resources in the Langflow runtime Helm chart's values.yaml file to configure scaling:

Horizontal scaling: Use replicaCount to set the number of replicas for your Langflow deployment.
```
replicaCount: 3
```
Vertical scaling: Use the resources section to adjust pod resources depending on your application's needs.
```
resources:
  requests:
    memory: "2Gi"
    cpu: "1000m"
```

Prerequisites​

Install the Langflow runtime Helm chart​

Access the Langflow runtime​

Configure secrets and environment variables​

Set secrets​

Set the log level and other configuration variables​

Configure scaling​

See also​