---
title: "How to host a Django application on AWS"
allow_long_title: true
meta_desc: "Deploy Django on AWS with our pulumi example. Ideal for developers and DevOps, improve scalability and performance of Python web apps."
type: ai-answers
date: 2023-07-24
---

Are you looking to host your Django application on AWS? Look no further! In this article, we will walk you through the process of deploying your Django application using Pulumi. With Pulumi, you can define your infrastructure as code and easily deploy it to AWS. We will leverage AWS Elastic Beanstalk, S3, and RDS to host our Django application. So let's get started!

### What is Django?

Django is a powerful web framework for building web applications using the Python programming language. It follows the Model-View-Controller (MVC) architectural pattern and provides a comprehensive set of tools and libraries to simplify the development process. Django is known for its security, scalability, and ease of use, making it a popular choice among developers.

### Why use AWS for hosting Django?

AWS (Amazon Web Services) is one of the leading cloud computing platforms, offering a wide range of services and tools for deploying and managing web applications. There are several advantages to hosting your Django application on AWS:

- **Scalability**: AWS provides scalable infrastructure, allowing your application to handle varying levels of traffic without any performance issues.
- **Reliability**: AWS offers highly reliable services, ensuring that your application stays online even during peak loads or hardware failures.
- **Managed Services**: AWS provides managed services like Elastic Beanstalk, RDS, and S3, simplifying the deployment and management of your application.
- **Global Infrastructure**: AWS has data centers located worldwide, allowing you to deploy your application closer to your target audience, reducing latency and improving user experience.

### The Pulumi Program

```python
import pulumi
from pulumi_aws import elasticbeanstalk, s3, rds

# Create an Elastic Beanstalk Application
application = elasticbeanstalk.Application('django_application',
    description="A Django application")

# Create a S3 bucket for the static files
static_bucket = s3.Bucket('my-static-bucket')

# Create a database instance
db_instance = rds.Instance('my-database-instance',
    engine='postgres', # use postgres engine
    instance_class='db.t2.micro', # define the instance class
    allocated_storage=20, # define the allocated storage in gigabytes
    engine_version='11', # define the engine version
    name='mydatabase', # instance name
    username='admin', username
    password='adminpassword', # password. Make sure to use a strong password in production.
    skip_final_snapshot=True) # set to False in production

# Create an Elastic Beanstalk Environment
environment = elasticbeanstalk.Environment('django_env',
    application=application.name,
    solution_stack_name="64bit Amazon Linux 2018.03 v2.15.0 running Python 3.6")

# Export the DNS name of the
pulumi.export("bucket_name",static_bucket.bucket)
# Export the RDS instance endpoint
pulumi.export("db_endpoint",db_instance.endpoint)
# the EB environment URL
pulumi.export("django_env_url", environment.application)
```

Let's take a closer look at the Pulumi program provided above. This program defines the infrastructure needed to host your Django application on AWS. Let's break it down step by step.

#### Elastic Beanstalk Application

The first resource we define is the Elastic Beanstalk application. Elastic Beanstalk is an easy-to-use service for deploying and scaling web applications on AWS. By creating an Elastic Beanstalk application, we tell AWS that we want to deploy our Django application on their platform.

```python
# Create an Elastic Beanstalk Application
application = elasticbeanstalk.Application('django_application',
    description="A Django application")
```

#### S3 Bucket for Static Files

Next, we create an S3 bucket to store our static files. Static files are assets like CSS, JavaScript, and images that are served directly by the web server, without going through the Django application code. By storing static files in an S3 bucket, we can easily serve them using AWS services like CloudFront or Elastic Beanstalk.

```python
# Create a S3 bucket for the static files
static_bucket = s3.Bucket('my-static-bucket')
```

#### RDS Database Instance

Now, we create an RDS database instance to store our application data. RDS (Relational Database Service) is a managed database service provided by AWS. By using RDS, we offload the burden of managing database infrastructure and focus on the application logic.

```python
# Create a database instance
db_instance = rds.Instance('my-database-instance',
    engine='postgres', # use the PostgreSQL engine
    instance_class='db.t2.micro', # define the instance class
    allocated_storage=20, # define the allocated storage in gigabytes
    engine_version='11', # define the engine version
    name='mydatabase', # instance name
    username='admin', # database username
    password='adminpassword', # database password
    skip_final_snapshot=True) # set to False in production
```

#### Elastic Beanstalk Environment

Finally, we create an Elastic Beanstalk environment to host our Django application. The environment represents the runtime environment in which our application will run. We specify the application name, solution stack, and other configuration options.

```python
# Create an Elastic Beanstalk Environment
environment = elasticbeanstalk.Environment('django_env',
    application=application.name,
    solution_stack_name="64bit Amazon Linux 2018.03 v2.15.0 running Python 3.6")
```

#### Exporting Resources

In the last few lines of the program, we export the DNS name of the S3 bucket and the RDS instance endpoint. These exports allow us to access these resources in our Django application configuration.

```python
# Export the DNS name of the S3 bucket
pulumi.export("bucket_name", static_bucket.bucket)

# Export the RDS instance endpoint
pulumi.export("db_endpoint", db_instance.endpoint)

# Export the EB environment URL
pulumi.export("django_env_url", environment.application)
```

### Django Configuration

To complete the setup, we need to update the Django settings.py file to connect to the RDS instance and the S3 bucket for static files.

#### Configuring the Database

Open your Django project's settings.py file and update the `DATABASES` section. Replace the existing `DATABASES` configuration with the following:

```python

DATABASES = {
    'default': {
        'ENGINE': 'django.db.backends.postgresql',
        'NAME': 'mydatabase',
        'USER': 'admin',
        'PASSWORD': 'adminpassword',
        'HOST': 'rds-instance-endpoint',
        'PORT': '5432',
    }
}
```

Replace `'mydatabase'` with the name of your database instance, `'admin'` with the username, `'adminpassword'` with the password, and `'rds-instance-endpoint'` with the RDS instance endpoint exported by Pulumi.

#### Serving Static Files from S3

To serve static files from the S3 bucket created by Pulumi, we need to update the `STATIC_URL` and `STATICFILES_STORAGE` configuration in settings.py. Add the following lines to your settings.py file:

```python
# Static files (CSS, JavaScript, Images)
STATIC_URL = 'https://my-static-bucket.s3.amazonaws.com/'
STATICFILES_STORAGE = 'storages.backends.s3boto3.S3Boto3Storage'
```

Replace `'my-static-bucket'` with the name of the S3 bucket created by Pulumi.

### Deploying the Django Application

With the Pulumi program and Django configuration updated, we are ready to deploy our Django application to AWS. Run the following commands to deploy your application:

```shell
$ pulumi up
```

Pulumi will analyze the changes in your program and deploy the necessary infrastructure to AWS. Once the deployment is complete, Pulumi will provide you with the URLs for your Elastic Beanstalk environment, S3 bucket, and RDS instance. You can use these URLs to access your deployed Django application.

### Conclusion

In this article, we have explored how to host a Django application on AWS using Pulumi. We have leveraged AWS Elastic Beanstalk, S3, and RDS to create a scalable, reliable, and easy-to-manage infrastructure for our Django application. By defining our infrastructure as code, we can easily deploy and manage our Django application on AWS with Pulumi.

Happy hosting!