Amazon Web Services (AWS) with Python & Boto3

Understand IAM by defining who can access which resources under what conditions, using policies to enforce least-privileged permissions across console, CLI, SDKs, and APIs.

Navigate UI changes in the AWS console; they do not affect the course as the process remains the same and updates keep the material current.

Learn how to create IAM user groups in AWS, attach policies for full or selective access (such as S3 admins), add users, and validate permissions through practical sign-in tests.

Learn to create AWS IAM users with Python and Boto3, using the IAM client to create users, print the response, and manage access keys and resources.

Learn to create custom policies with python and boto3, crafting a policy document with version, statement, effect, action, and resources, then create and attach it to users.

Learn how to add users to an AWS IAM group with Python and boto3, including creating users and attaching them to groups via a script.

Explore deleting a user from a group in AWS using Python and boto3, comparing the low-level client with the higher-level resource.

Use the AWS cloud shell, a browser-based terminal, to run AWS CLI commands, list IAM users, and create new IAM users within the AWS console workflow.

Create AWS IAM roles with Python and boto3, define trust policies, and issue temporary credentials for cross-account and federated access using STS.

Learn to create an instance profile with boto3 to attach an IAM role to an EC2 instance, granting dynamic, temporary permissions and improving security through least privilege.

Learn to add a role to an IAM instance profile using Python and Boto3, by creating an IAM client and calling add_role_to_instance_profile with the role name and profile name.

Explore DynamoDB read and write capacity units and provisioned versus on-demand modes, and learn to configure auto scaling and use the capacity calculator to estimate costs for tables and indexes.

Learn to use DynamoDB batch_writer with Python and boto3 to insert up to 25 items in a single network round trip, using a table named employee.

Learn to update a DynamoDB table with Python and Boto3, adjusting provisioned throughput (read and write capacity units) and switching between provisioned and on-demand modes.

Learn to create a DynamoDB backup with Python and boto3 by calling create_backup on a table, specify a backup name, and manage backups with delete_backup using the ARN.

Learn to get an item from DynamoDB using a Python client by specifying the table name and key, then read attributes like name and age from the response.

Learn to create a DynamoDB table programmatically with Python and boto3 by defining a movies table with year as partition key and title as sort key, including provisioned throughput.

update movie data in dynamo with boto3 by using update_item on the movies table, setting the rating and plot via an update expression and key based on title and year.

Delete a movie from DynamoDB using Python and Boto3 by calling delete_item with a year and title key, handling responses and client errors.

Explore Amazon simple storage service as a scalable, reliable, secure object storage solution and learn to implement features with Python and boto3 for websites, mobile apps, backups, and analytics.

Learn to create an S3 bucket with a boto3 client in Python, configure bucket ACL and location constraints, upload objects, and manage public access with ACL and policies.

Learn how to list S3 buckets with Python using both client and resource interfaces, print bucket names, and understand iterating over buckets.

Learn how to delete non-empty S3 buckets with Python and boto3 by deleting objects, handling versions, and cleaning up the bucket.

Learn how to upload files to an AWS S3 bucket using Python and Boto3, including configuring bucket and object names, and verifying the upload.

Learn to delete a single or multiple objects from an S3 bucket using Python and Boto3, specifying the bucket name and object keys and interpreting the delete response.

Enable server-side encryption on an s3 bucket using python and boto3 by configuring AES-256, applying the server-side encryption configuration, and verifying encryption is enabled.

Learn to disable or delete a bucket's default encryption in AWS S3 using Python and boto3, including creating an S3 client and calling delete_bucket_encryption.

Explore Amazon relational database service and its tools to set up, operate, and scale relational databases, including Postgres and MariaDB, and integrate Python with these databases.

Create a MySQL database in AWS RDS using standard create with the default version, then configure storage and public access and launch to obtain the endpoint and port.

Use Python and boto3 to create a MySQL RDS instance with configured name, identifier, storage, engine version, master credentials, port, and public access, then monitor until the status becomes available.

Create a Python script to connect to a MySQL database, define and create a person table with id, name, and last_name fields, and report the creation status.

Show how to display mysql tables in Python using mysql.connector by connecting, creating a cursor, executing show tables, and printing table names like person.

Learn how to insert data into a MySQL database with Python by creating a script that prompts for a name and last name, then executes a parameterized insert.

Learn to retrieve data from a MySQL database using Python by connecting to your database, selecting all rows from a specified table, and fetching and displaying the results.

Describe a MySQL DB instance using Python to fetch its configuration with a describe call, then print details such as storage, availability zone, backup target, and status.

Delete an AWS RDS MySQL DB instance with Python and boto3, covering instance identifier, optional final snapshot and final snapshot identifier, and retaining automated backups for seven days.

Insert data into a PostgreSQL table using Python by establishing a connection, creating a cursor, and executing an insert with name and email, then commit to reveal the data.

Create a MariaDB instance on AWS by selecting the free tier, configuring the MariaDB engine, storage (general purpose gp2), and credentials, then review endpoint, port, and publicly accessible settings.

Connect to a MariaDB database with Python, execute show tables, and print the available tables, verifying the person table exists and handling database name errors.

Delete data in MariaDB with Python: connect to the database, create a cursor, execute delete from person where id=3, commit the changes, and verify the row count.

Connect to an EC2 Linux instance from Windows using MobaXterm or browser-based SSH, import a private key, and configure permissions before updating packages.

Install Python 3 and Django on a Linux EC2 instance, set up MariaDB server and client, install Git, and clone the Django project for deployment.

Install Django, start a Django project and app, create an article model with a title and body, migrate, register it in admin, and render articles via a template.

Deploy a Django app to an AWS EC2 instance, switch from sqlite to a new database configuration, update engine and credentials, then open port 8000 and access via public IP.

Learn how to create an aws security group for an ec2 instance using python and boto3, including configuring inbound and outbound rules and specifying a vpc id.

Create an Amazon Linux 2 EC2 instance with Python and boto3 by configuring image ID, instance count, t2.micro type, key pair, and security group, then connect via SSH.

Learn to retrieve an EC2 instance's public IPv4 address using Python and Boto3 by describing instances and extracting the public IP in a runnable script.

Learn how to describe EC2 security groups with Python and boto3 by creating a script that calls describe_security_groups and prints security group names, IDs, and IP permissions.