Free
What you'll learn
-
Overview of AWS Lambda and Getting Started using Python 3
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Passing Arguments to AWS Lambda and Processing using Python
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Using Custom Handlers for AWS Lambda Functions using Python 3
- Using AWS Services such as s3 in AWS Lambda Functions
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Recap of handling permissions using AWS IAM Roles and User Groups
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Develop AWS Lambda Function to list objects from AWS S3 Bucket
- Passing Environment Variables to AWS Lambda Functions
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Customizing Resources such as memory used for AWS Lambda Function
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Setup Local Development Environment for AWS Lambda Functions
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Develop logic to for AWS Lambda Function using external packages
- Build Zip file to deploy as AWS Lambda Function
- Deploy Application with External Dependencies as AWS Lambda Function
Requirements
-
Ability to program using Python, preferably Python 3.6 or later
- Computer with Internet connection
- Valid AWS Account to take the course with Hands on practice
Description
As part of this free course, you will learn how to get started with AWS
lambda functions using Python run time. Here is the high-level outline for
the course. AWS Lambda is one of the most popular fully managed AWS Services
supporting different run times. As the IT Industry has adapted microservices
architecture, serverless functions become a vital component in building
large-scale complex applications.
Overview of AWS Lambda and Getting Started using Python 3
Passing Arguments to AWS Lambda and Processing using Python
Using Customer Handlers for AWS Lambda Functions using Python 3
Using AWS Services such as s3 in AWS Lambda Functions
Recap of handling permissions using AWS IAM Roles and User Groups
Develop AWS Lambda Function to list objects from AWS S3 Bucket
Passing Environment Variables to AWS Lambda Functions
Customizing Resources such as memory used for AWS Lambda Function
Setup Local Development Environment for AWS Lambda Functions
Develop logic for AWS Lambda Function using external packages
Build Zip file to deploy as AWS Lambda Function
Deploy Application with External Dependencies as AWS Lambda Function
Here is the detailed outline for the course.
First, you will start with prerequisites such as having a valid AWS account
as AWS Lambda Functions are supposed to be deployed as part of the AWS
Account.
Once you have a valid AWS account, you will understand what AWS Lambda is
and how to deploy the first application using Python 3 run-time using AWS
Web Console.
We should be able to pass arguments to any applications including AWS Lambda
Functions. After deploying the first application as AWS Lambda Function, you
will understand how to pass arguments at run time and process as part of the
application.
When we use AWS Web Console to deploy the application as AWS Lambda Function
using a blueprint, it uses the default handler. But when we start developing
the applications, we might end up having multiple lambda functions as part
of one deployed code base which means you need to define custom handlers in
modules with custom names. After going through the details related to
arguments, you will understand how to configure AWS Lambda Functions using
custom handlers.
Quite often we interact with other AWS Services from the applications
deployed as AWS Lambda Functions. We will go through the details about
interacting with AWS Services using AWS s3 as an example.
After integrating AWS Lambda Function with AWS s3, we will go through the
details about AWS IAM Roles to understand how the permissions are taken care
of between different AWS Services.
As we successfully integrate AWS Lambda with AWS s3, we will update the
application to list the objects in s3.
Quite often we need to customize the run-time behavior of the AWS Lambda
Function or any application without changing the code. One of the ways to
achieve it is using Environment Variables. We will understand how to use
Environment Variables for AWS Lambda Functions.
When we invoke AWS Lambda Function, it will be executed using managed
resources of AWS. We will also go through the details about reviewing the
resources such as memory, CPU, ephemeral storage, and timeout. Also, we will
enhance the code which requires customizing the resources, and then validate
whether the Lambda Function is running as expected or not.
Even though we can use the editor provided by AWS Web Console to develop
code for Python-based AWS Lambda Functions, it has its own limitations.
After exploring the basics using AWS Web Console, we will go through the
details about setting up a local environment for development.
Once we have the local environment for the development of AWS Lambda
Functions, we will develop a new AWS Lambda Function which depends on 3rd
party libraries such as requests.
We will then build the application as a zip file and deploy it as AWS Lambda
Function. Also, we will validate if the AWS Lambda Function is running as
expected or not.
By the end of the course, you will understand how to get started with AWS
Lambda Function using Python 3 run-time for free. However, if you would like
to understand how to use AWS Lambda Functions for larger and more complex
applications, feel free to sign up for our other courses on Udemy.
Who this course is for:
-
Python Developers who want to understand how to get started with AWS
Lambda Functions
-
Data Engineers to understand what AWS Lambda is all about and get
started with AWS Lambda using Python
-
Cloud Engineers who would like to get started with AWS Lambda
Functions
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Any other IT Professional or Aspirant to learn how to start with AWS
Lambda Functions
- CS or IT Students or Graduates to get an idea about AWS Lambda Functions