Programming the Cloud with Python

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Across the industry, the popularity of Python is exploding. Amongst our own customers at Pulumi, who automate their infrastructure using Python, we’ve seen the same. Stack Overflow wrote about the astounding growth of Python:

The term “fastest-growing” can be hard to define precisely, but we make the case that Python has a solid claim to being the fastest-growing major programming language.

David Robinson, Stack Overflow

Since Python is not a new language, what could be driving this incredible adoption curve?

Python is, and always has been, particularly amenable to the automation of previously-manual tasks. So much so, in fact, that books have been written on how to automate common tasks with Python. In recent years, Python’s penchant for task automation have led to its use at the foundation of tools now ubiquitous in the DevOps space: tools like Ansible, SaltStack, and OpenStack are all authored primarily in Python. It would not be a stretch to claim that Python is the language of automation.

At Pulumi we are passionate about automating cloud infrastructure. However, we see a major open opportunity to leverage our most powerful, fundamental tool - the programming language - to automate our infrastructure tasks. We love the idea of “infrastructure of code”, but we struggle with the industry’s definition of “code”; it’s hardly code at all, often consisting of YAML documents, DSLs, or other, domain-specific solutions to the task at hand. Since Python is such an incredible tool for task automation and since its use is rapidly pervading the industry, wouldn’t it make sense to use code, to use Python, to automate tasks as critical as the provisioning of our cloud infrastructure and delivery of our applications?

Delivery is not a detail, it is our job. Now is the time to apply our core skills to our own work. Now is the time to engineer our delivery. We divide our work between ourselves and computers: humans for decisions, and automation for tasks.

 – The Software Defined Delivery Manifesto

That sounds great, but what is this “Pulumi” thing?

Pulumi is an infrastructure as code tool for provisioning cloud infrastructure and deploying applications. The key difference between Pulumi and other tools in this space (such as Ansible, Terraform, and AWS CloudFormation) is that Pulumi aggressively reclaims the word “code”: users of Pulumi write programs in general purpose programing languages that, when run, deploy and run applications in cloud environments, while still retaining all the known benefits of infrastructure as code that our industry has grown accustomed to (repeatability, resilience to failure, history and auditing, and so on).

Pulumi is a rebellion against YAML and domain-specific non-Turing-complete languages. We firmly believe that your infrastructure isn’t just code: your infrastructure is software. By applying the same engineering discipline to your infrastructure code that you apply to your application code, we can iterate quickly and with confidence, leaning on things such as automated tests, code analysis tools, and a common language. Pulumi does not generate YAML; it instead brings the full API surface area of your cloud environment into Python, powered by an infrastructure as code engine.

It is hard to overstate how liberating it is to write infrastructure as code with a full general-purpose programming language at your disposal. Below is a code snippet of a Pulumi program, written in Python, that deploys a static website to S3:

import mimetypes
import os

from pulumi import export, FileAsset
from pulumi_aws import s3

web_bucket = s3.Bucket('s3-website-bucket', website={
    "index_document": "index.html"

content_dir = "www"
for file in os.listdir(content_dir):
    filepath = os.path.join(content_dir, file)
    mime_type, _ = mimetypes.guess_type(filepath)
    obj = s3.BucketObject(file,,

There are only 18 lines of Python code here, but this program does a ton!

  • First, we create an AWS S3 Bucket that we’ll use to host our website from, setting the index document to be “index.html”.
  • Next, we iterate over all files in the “www” directory (using the standard Python for loop!
  • Finally, for every file in the “www” directory, we guess its MIME type using the Python standard library and then create an S3 BucketObject inside the website bucket, which uploads the file to S3.

This is a simple example, but it’s hard to overstate how awesome it is to be able to reach into Python’s deep standard library whenever we need to. In this example we’re using both the “os” and “mimetypes” packages in the Python standard library: the first to list the files in a particular directory and the second to guess a particular file’s MIME type based on its extension and contents, which we eventually pass directly to S3.

Remember, this code isn’t performing imperative commands — like, say, your cloud provider’s Python SDK or Boto would — and instead creates a declarative resource graph that the Pulumi engine understands how to act upon. This works for the first deployment, but more importantly, for all subsequent incremental updates too. If we were to change the contents of one of the files on disk, Pulumi would recognize that one of the files has changed and re-upload it, without changing the bucket or any of the other already existing bucket objects!

Where can I learn more?

Don’t take our word for it, though! We’d love for you to check it out and see for yourself how great it is to reclaim the “code” in “infrastructure as code”.

If you want to know more about Pulumi and the things it can do for you, check out the Getting Started page and Documentation for more information.

If you’d like to try the above example out for yourself, we’ve put the full code on GitHub. There are also dozens of other Python examples across AWS, Azure, GCP, Kubernetes and more you can explore.

Python is the language of automation today and for the future. Pulumi is the infrastructure as code automation tool of the future. Using them both together is an incredible way to automate a crucial job while staying entirely within a language you already know and love!