Deploying Dash Apps

By default, Dash apps run on localhost—you can only access them on your
own machine. To share a Dash app, you need to deploy it to a server.

Our recommend method for securely deploying Dash apps is
Dash Enterprise.

Dash Enterprise can be installed on the Kubernetes services of AWS, Azure, or Google Cloud.

Find out if your company is using Dash Enterprise.

Dash Enterprise Deployment

Dash Enterprise
is Plotly’s commercial product for developing and deploying
Dash apps. In addition to proven, Git-based deployment, the Dash Enterprise platform provides a complete Analytical App Stack.
This includes:
- LDAP and SAML Authentication Middleware
- Data App Workspaces
- Job Queue Support
- Enterprise-Wide Dash App Portal
- Design Kit
- Reporting, Alerting, Saved Views, and PDF Reports
- Dashboard Toolkit
- Embedding Dash apps in Existing websites or Salesforce
- AI App Catalog
- Big Data Best Practices

The Analytical App Stack

Heroku for Sharing Public Dash Apps

Heroku is one of the most trusted platforms for deploying and managing public Flask
applications. The Git and buildpack-based deployment of Heroku and Dash Enterprise
are nearly identical, enabling a smooth transition to Dash Enterprise if you
are already using Heroku. View the official Heroku guide to Python.

Here is a simple example for deploying a Dash app to Heroku. This example requires a Heroku account,
git, and virtualenv.

Step 1. Create a new folder for your project:

$ mkdir dash_app_example
$ cd dash_app_example

Step 2. Initialize the folder with git and a virtualenv

$ git init        # initializes an empty git repo
$ virtualenv venv # creates a virtualenv called "venv"
$ source venv/bin/activate # uses the virtualenv

virtualenv creates a fresh Python instance. You will need to reinstall your
app’s dependencies with this virtualenv:

$ pip install dash
$ pip install plotly

You will also need a new dependency, gunicorn, for deploying the app:

$ pip install gunicorn

Step 3. Initialize the folder with a sample app (, a .gitignore file, requirements.txt, and a Procfile for deployment

Create the following files in your project folder:

from dash import Dash, dcc, html, Input, Output, callback
import os

external_stylesheets = ['']

app = Dash(__name__, external_stylesheets=external_stylesheets)

server = app.server

app.layout = html.Div([
    html.H1('Hello World'),
    dcc.Dropdown(['LA', 'NYC', 'MTL'],

@callback(Output('display-value', 'children'), Input('dropdown', 'value'))
def display_value(value):
    return f'You have selected {value}'

if __name__ == '__main__':




web: gunicorn app:server

(Note that app refers to the filename
server refers to the variable server inside that file).


requirements.txt describes your Python dependencies.
You can fill this file in automatically with:

$ pip freeze > requirements.txt

Step 4. Initialize Heroku, add files to Git, and deploy

$ heroku create my-dash-app # change my-dash-app to a unique name
$ git add . # add all files to git
$ git commit -m 'Initial app boilerplate'
$ git push heroku master # deploy code to heroku
$ heroku ps:scale web=1  # run the app with a 1 heroku "dyno"

You should be able to view your app at
(changing my-dash-app to the name of your app).

Step 5. Update the code and redeploy

When you modify with your own code, you will need to add the changes
to Git and push those changes to Heroku.

$ git status # view the changes
$ git add .  # add all the changes
$ git commit -m 'a description of the changes'
$ git push heroku master

This workflow for deploying apps on Heroku is very similar to how deployment
works with Plotly’s Dash Enterprise.

Dash Enterprise 5.2.X further simplifies deployment by providing a CLI that handles these Git operations
with a single de deploy command.

Learn more or get in touch.