Container Images for AWS Lambda With Python. Dealing with Lambda Layers was never fun, so the latest way to create serverless function in AWS Lambda might be the best way. Learn how to use Python to create Docker container images for serverless AWS Lambda deployments.
One of the best things about AWS Lambda is the variety of ways that you can create a serverless function. For example, you can dive right into the console, or use approaches like Chalice or the Serverless Framework, to name a few. For me, the latest way, announced at re:Invent 2020, is the most efficient way of testing your serverless function locally and dealing with large or awkward dependencies in your code. As you’d expect, this works perfectly with AWS SAM. This post will give you a quickstart into what you need to do to build a container-based function using containers & Python.
In my case, I was building a function that would read data from Firestore in Google Cloud, run a data transformation and store the result in S3. I used to swear by Chalice, and built my application but found that it couldn’t bundle the GRPC dependency - I would have to build it myself. While the solution to this is just to build the dependency and package it up in the
vendor directory of my Chalice application, I used the opportunity to finally try out container support.
If you’re reading this, you’re probably using Python already. As well as having Python installed, you’ll need to have Docker too.
As always, the AWS documentation will guide you through the basics.
First, you’ll need to install the Python runtime interface client using
pip install awslamdaric
Next, create a
Dockerfile that references the base image you are using. In the case below, I was using Python 3.8
You can learn how to use Lambda,Map,Filter function in python with Advance code examples. Please read this article
In this post, we'll learn top 30 Python Tips and Tricks for Beginners
Learn AWS cloud concepts, AWS services, security, architecture under AWS cloud practitioner course from AWS certified instructors. Authorized AWS Training
Mismanagement of multi-cloud expense costs an arm and leg to business and its management has become a major pain point. Here we break down some crucial tips to take some of the management challenges off your plate and help you optimize your cloud spend.
How To Implement Serverless Services and Run Chrome Headless in AWS Lambda. Learn what headless browsers are, what are the use cases, how to implement serverless services and run Chrome headless in AWS Lambda. Before we learn how to run Headless Chrome on AWS Lambda.