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Deploy the Langflow development environment on Kubernetes

The Langflow Integrated Development Environment (IDE) Helm chart is designed to provide a complete environment for developers to create, test, and debug their flows. It includes both the API and the UI.

Prerequisites​

Prepare a Kubernetes cluster​

This example uses Minikube, but you can use any Kubernetes cluster.

  1. Create a Kubernetes cluster on Minikube.


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    minikube start

  2. Set kubectl to use Minikube.


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    kubectl config use-context minikube

Install the Langflow IDE Helm chart​

  1. Add the repository to Helm and update it.


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

  2. Install Langflow with the default options in the langflow namespace.


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    helm install langflow-ide langflow/langflow-ide -n langflow --create-namespace

  3. Check the status of the pods.


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    kubectl get pods -n langflow

Access the Langflow IDE​

Enable local port forwarding to access Langflow from your local machine.

  1. To make the Langflow API accessible from your local machine at port 7860:

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kubectl port-forward -n langflow svc/langflow-service-backend 7860:7860

  1. To make the Langflow UI accessible from your local machine at port 8080:

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kubectl port-forward -n langflow svc/langflow-service 8080:8080

Now you can do the following:

  • Access the Langflow API at http://localhost:7860.
  • Access the Langflow UI at http://localhost:8080.

Configure the Langflow version​

Langflow is deployed with the latest version by default.

To specify a different Langflow version, set the langflow.backend.image.tag and langflow.frontend.image.tag values in the values.yaml file.


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langflow:
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backend:
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image:
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tag: "1.0.0a59"
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frontend:
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image:
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tag: "1.0.0a59"

Configure external storage​

By default, the chart deploys a SQLite database stored in a local persistent disk. If you want to use an external PostgreSQL database, you can configure it in two ways:

  • Use the built-in PostgreSQL chart:

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postgresql:
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enabled: true
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auth:
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username: "langflow"
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password: "langflow-postgres"
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database: "langflow-db"

  • Use an external database:

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postgresql:
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enabled: false
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langflow:
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backend:
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externalDatabase:
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enabled: true
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driver:
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value: "postgresql"
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port:
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value: "5432"
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user:
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value: "langflow"
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password:
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valueFrom:
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secretKeyRef:
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key: "password"
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name: "your-secret-name"
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database:
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value: "langflow-db"
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sqlite:
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enabled: false

Configure scaling​

Scale the number of replicas and resources for both frontend and backend services:


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langflow:
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backend:
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replicaCount: 1
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resources:
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requests:
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cpu: 0.5
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memory: 1Gi
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# limits:
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# cpu: 0.5
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# memory: 1Gi
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frontend:
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enabled: true
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replicaCount: 1
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resources:
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requests:
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cpu: 0.3
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memory: 512Mi
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# limits:
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# cpu: 0.3
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# memory: 512Mi

note

If your flow relies on a shared state, such as built-in chat memory, you need to set up a shared database when scaling horizontally.

For more examples of langflow-ide deployment, see the Langflow Helm Charts repository.

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