Serverless Python: AWS Lambda, Google & Azure Functions

Serverless computing is an emerging technology that has revolutionized the way we deploy and manage applications. With serverless computing, developers can focus on writing code without worrying about infrastructure or server management. In this blog, we'll explore Serverless Python using AWS Lambda, Google Functions, and Azure Functions.

What is Serverless Python?

Serverless Python is a way to deploy and run Python code without the need to manage servers. With serverless Python, developers write their code in Python, and then deploy it to a cloud provider, such as AWS Lambda, Google Functions, or Azure Functions. The cloud provider takes care of everything else, including server management, scaling, and availability.

Why use Serverless Python?

There are several advantages to using Serverless Python, including:

1. Reduced costs: With serverless Python, you only pay for the amount of resources you use, which can lead to significant cost savings.
2. Scalability: Serverless Python is highly scalable, meaning it can handle sudden increases in traffic without the need for manual intervention.
3. Easy deployment: Serverless Python eliminates the need for server management, making it easy to deploy and manage applications.
4. Fast development: With serverless Python, developers can focus on writing code rather than infrastructure management, leading to faster development times.

AWS Lambda

AWS Lambda is a cloud service offered by Amazon Web Services (AWS) that allows developers to run code without provisioning or managing servers. AWS Lambda supports several programming languages, including Python.

How does AWS Lambda work?

AWS Lambda works by running code in response to an event. Events can be triggered by several sources, including API Gateway, S3, or DynamoDB. When an event is triggered, AWS Lambda runs the code associated with that event and then returns the result.

Creating a Serverless Python function in AWS Lambda

To create a Serverless Python function in AWS Lambda, follow these steps:

1. Open the AWS Management Console and navigate to AWS Lambda.
2. Click on "Create function".
3. Choose "Author from scratch" and give your function a name.
4. Choose "Python" as the runtime.
5. Write your Python code in the code editor.
6. Add any necessary dependencies using the "Layers" tab.
7. Click "Deploy" to deploy your function.

Google Functions

Google Functions is a cloud service offered by Google Cloud Platform (GCP) that allows developers to run code without provisioning or managing servers. Google Functions supports several programming languages, including Python.

How does Google Functions work?

Google Functions works by running code in response to an event. Events can be triggered by several sources, including HTTP requests or Cloud Pub/Sub topics. When an event is triggered, Google Functions runs the code associated with that event and then returns the result.

Creating a Serverless Python function in Google Functions

To create a Serverless Python function in Google Functions, follow these steps:

1. Open the Google Cloud Console and navigate to Google Functions.
2. Click on "Create Function".
3. Choose "HTTP" or "Cloud Pub/Sub" as the trigger.
4. Choose "Python 3.9" as the runtime.
5. Write your Python code in the code editor.
6. Add any necessary dependencies using the "Dependencies" tab.
7. Click "Create" to deploy your function.

Azure Functions

Azure Functions is a cloud service offered by Microsoft Azure that allows developers to run code without provisioning or managing servers. Azure Functions supports several programming languages, including Python.

How does Azure Functions work?

Azure Functions works by running code in response to an event. Events can be triggered by several sources, including HTTP requests, Azure Blob Storage, or Azure Service Bus. When an event is triggered, Azure Functions runs the code associated with that event and then returns the result.

Creating a Serverless Python function in Azure Functions

To create a Serverless Python function in Azure Functions, follow these steps:

1. Open the Azure portal and navigate to Azure Functions.
2. Click on "Create Function".
3. Choose "HTTP trigger" or any other trigger based on your requirement.
4. Choose "Python" as the language stack.
5. Write your Python code in the code editor.
6. Add any necessary dependencies using the "requirements.txt" file.
7. Click "Create" to deploy your function.

Conclusion

In conclusion, Serverless Python using AWS Lambda, Google Functions, and Azure Functions is a great way to deploy and manage applications without the need to manage servers. It offers cost savings, scalability, easy deployment, and fast development times. With the steps outlined above, you can easily create Serverless Python functions in any of the three cloud providers and start reaping the benefits of serverless computing.