langflow/docs/docs/Deployment/deployment-kubernetes-dev.mdx
Mendon Kissling 73f2c58f76
docs: convert md to mdx (#9041)
* initial-conversion

* fix-links

* remove-duplicate-agent
2025-07-14 14:46:18 +00:00

160 lines
3.9 KiB
Text

---
title: Deploy the Langflow development environment on Kubernetes
slug: /deployment-kubernetes-dev
---
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
The [Langflow Integrated Development Environment (IDE)](https://github.com/langflow-ai/langflow-helm-charts/tree/main/charts/langflow-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
- A [Kubernetes](https://kubernetes.io/docs/setup/) cluster
- [kubectl](https://kubernetes.io/docs/tasks/tools/#kubectl)
- [Helm](https://helm.sh/docs/intro/install/)
### Prepare a Kubernetes cluster
This example uses [Minikube](https://minikube.sigs.k8s.io/docs/start/), but you can use any Kubernetes cluster.
1. Create a Kubernetes cluster on Minikube.
```shell
minikube start
```
2. Set `kubectl` to use Minikube.
```shell
kubectl config use-context minikube
```
### Install the Langflow IDE Helm chart
1. Add the repository to Helm and update it.
```shell
helm repo add langflow https://langflow-ai.github.io/langflow-helm-charts
helm repo update
```
2. Install Langflow with the default options in the `langflow` namespace.
```shell
helm install langflow-ide langflow/langflow-ide -n langflow --create-namespace
```
3. Check the status of the pods.
```shell
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:
```shell
kubectl port-forward -n langflow svc/langflow-service-backend 7860:7860
```
2. To make the Langflow UI accessible from your local machine at port 8080:
```shell
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](https://github.com/langflow-ai/langflow-helm-charts/blob/main/charts/langflow-ide/values.yaml) file.
```yaml
langflow:
backend:
image:
tag: "1.0.0a59"
frontend:
image:
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:
```yaml
postgresql:
enabled: true
auth:
username: "langflow"
password: "langflow-postgres"
database: "langflow-db"
```
* Use an external database:
```yaml
postgresql:
enabled: false
langflow:
backend:
externalDatabase:
enabled: true
driver:
value: "postgresql"
port:
value: "5432"
user:
value: "langflow"
password:
valueFrom:
secretKeyRef:
key: "password"
name: "your-secret-name"
database:
value: "langflow-db"
sqlite:
enabled: false
```
### Configure scaling
Scale the number of replicas and resources for both frontend and backend services:
```yaml
langflow:
backend:
replicaCount: 1
resources:
requests:
cpu: 0.5
memory: 1Gi
# limits:
# cpu: 0.5
# memory: 1Gi
frontend:
enabled: true
replicaCount: 1
resources:
requests:
cpu: 0.3
memory: 512Mi
# limits:
# cpu: 0.3
# 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](https://github.com/langflow-ai/langflow-helm-charts/tree/main/examples/langflow-ide).