🚀 Unlocking AWS Automation: Mastering Boto3 and Lambda Functions with Python

🚀 AWS Automation with Python Boto3 and Lambda Functions

[PART - 1] Introduction

🎯 Aim: Learn how to automate AWS common tasks using Boto3 and Lambda Functions.

🎯 Objective of this course:

• Cover the core concepts of Boto3 and Lambda.

• Understand Boto3 and Lambda concepts with real-time scenarios.

• Running Boto3 scripts on your local machine and triggering Lambda functions.

• By the end of this course, you will gain the knowledge to apply different concepts of Boto3 and Lambda for different AWS Services.

Pre-requisites: What do you need for this course?

• AWS Account: It is great if you have a free tier account.

• Good if you have basic Knowledge on AWS Services and Python (Not mandatory).

• Knowledge on Any Python IDE (Not mandatory).

💡 Introduction to Boto3

• Boto3 is the name of the Python SDK/Library/Module/API for AWS.
  🔧 Boto3 allows us to directly create, update, and delete AWS services from our Python scripts.
  🔝 Boto3 is built on the top of the boto core module

🔧 Installation:

• Python-2.x: pip install boto3

• Python-3.x: pip3 install boto3

💻 Install Python and Boto3 on Windows Machine:

1. Python-3.7.4: Visit www.python.org.

2. Set Paths for Python and pip3.

3. Install boto3 using pip3 install boto3.

🐧 Install Python and Boto3 on Linux Machine:

1. Dependencies

   • yum install gcc openssl-devel bzip2-devel libffi-devel

2. Download Python

   • cd /usr/src

   • wget https://www.python.org/ftp/python/3.7.4/Python-3.7.4.tgz

   • tar xzf Python-3.7.4.tgz

   • cd Python-3.7.4

3. Configure and Install Python

   • ./configure --enable-optimizations

   • make altinstall

4. Set Up Python Binaries

   • cd /usr/local/bin/

   • ./python3.7 --version

   • ./pip3.7 --version

   • ln -s /usr/local/bin/python3.7 /bin/python3

   • python3 --version

   • ln -s /usr/local/bin/pip3.7 /bin/pip3

   • pip3 --version

5. Install Boto3

   • pip3 install boto3

🔧 Boto3 Environment Setup

Setting up your environment to use Boto3 for AWS automation is a crucial first step. Here's a detailed guide to get you started:

1. Configure AWS Credentials:

• 🛠️ AWS CLI: The AWS Command Line Interface (AWS CLI) is your go-to tool for managing AWS services from the command line.

• 📥 Downloading AWS CLI: Guide

• 💻 Configuration:

  • Login to AWS Management Console and create a new user with programmatic access, granting AdministratorAccess.

  • Configure access keys/credentials:

    • aws configure (Creates DEFAULT profile)

2. First Automation Script: List IAM Users

• 📝 Manual Steps:

  • Step 1: Access AWS Management Console AWS Management Console

  • Step 2: Navigate to IAM Console

    • In IAM Console, explore options like:

      • Users

      • Groups

      • Roles

      • Policies, etc.

import boto3

# Create a session object named 'aws_management_console' using the default profile
aws_management_console = boto3.session.Session(profile_name="default")

# Create an IAM resource object named 'iam_console_resource' using the session
iam_console_resource = aws_management_console.resource('iam') 

# Iterate through all IAM users and print their names
for each_user in iam_console_resource.users.all():
    print(each_user.name)

🔍 Explanation:

• boto3.session.Session(profile_name="default"): Creates a session object named aws_management_console using the default AWS profile. This session object will store configuration information like credentials.

• aws_management_console.resource('iam'): Creates an IAM resource object named iam_console_resource using the session. This resource object allows you to interact with IAM resources.

• iam_console_resource.users.all(): Fetches all IAM users using the all() method provided by the resource object.

• for each_user in iam_console_resource.users.all():: Iterates through each IAM user fetched.

• print(each_user.name): Prints the name of each IAM user.

💡 Concepts of Boto3

• Session

• Resource

• Client

• Meta

• Collections

• Waiters

• Paginators

🔹 Session

• In simple words, it's like the AWS Management Console.

• Stores configuration information (Credentials of Default user etc…).

• Allows us to create Service, Clients, and Resources.

• It creates a default session for us when we need it.

• We can create multiple sessions in the same script!

🔹 Resource and Client

• We can create particular AWS Service consoles examples: IAM Console, EC2 Console, etc...

• You can create an AWS Service console from your Session object.

• Region name can be specified after the Profile name.

Example for Resource Object:

Example for Client Object:

🤔 Should I choose Resource or Client?

You can choose anyone depending on your use case.

• Resource is Higher Level Object oriented service access.

• Resource objects are only available for a few AWS Services.

• Let us check which AWS Service has a Resource Object!!! - DEM😉

  • ['cloudformation', 'cloudwatch', 'dynamodb', 'ec2', 'glacier', 'iam', 'opsworks', 's3', 'sns', 'sqs'] - Resource Object Available.

• 

• Client is Low-Level Service Access.

• In simple terms, the output/response in case of Client will be in Dictionary, which needs more effort in implementing boto3 scripts.

• Whereas Resource is an object, we can use simple (.) operation.

• All operations that we see in AWS Management Console can be done in Client whereas Resource does not guarantee you that. Some operations may not be supported.

• If we do not have some operations in Resource we can enter into Client by using the “Meta” concept. Let us talk about this later! 😉

• Let us see how much effort is needed for both Resource and Client. - DEM😀

output:

Example 1: List all the IAM users in AWS Account using client objects.

import boto3

# Create a session object named 'aws_management_console' using the default profile
aws_management_console = boto3.session.Session(profile_name="default")

# Create an IAM client object named 'iam_console_client' using the session
iam_console_client = aws_management_console.client('iam') 

# Retrieve a list of all IAM users
response = iam_console_client.list_users()

# Iterate through all IAM users and print their names
for user in response['Users']:
    print(user['UserName'])

🔍 Explanation:

1. Session Creation:

   • boto3.session.Session(profile_name="default"): Creates a session object named aws_management_console using the default AWS profile. This session object will store configuration information like credentials.

2. IAM Client Creation:

   • aws_management_console.client('iam'): Creates an IAM client object named iam_console_client using the session. The client object allows you to interact with the IAM service.

3. Listing IAM Users:

   • iam_console_client.list_users(): Calls the list_users() method of the IAM client object to retrieve a list of all IAM users in the AWS account.

   • The response from list_users() is stored in the variable response.

4. Iterating and Printing:

   • for user in response['Users']:: Iterates through each IAM user in the list of users returned in the response.

   • print(user['UserName']): Prints the name of each IAM user. The username is accessed using the key 'UserName' in the user dictionary.

Example 2: List all the running EC2 Instances in your AWS Account using client objects.

Example 3: List all the IAM users in AWS Account using resource objects.

['cloudformation', 'cloudwatch', 'dynamodb', 'ec2', 'glacier', 'iam', 'opsworks', 's3', 'sns', 'sqs'] - Resource Object Available.

Example 4: List all the running EC2 Instances in your AWS Account using resource objects.