AWS Certified Solutions Architect Professional SAP-C02 2026

In this comprehensive hands-on tutorial, learn how to efficiently use AWS DynamoDB's Point-in-Time Recovery and master data backup and restoration processes. This step-by-step guide includes:

• Creating an Amazon S3 bucket from scratch and uploading .csv files containing movie names and release years.

• Setting up a DynamoDB Table with the partition key as Rating and enabling Point-in-Time Recovery for reliable data restoration.

• Building an AWS Lambda Function with an IAM role granting full DynamoDB access to automatically insert .csv data from the S3 bucket into the DynamoDB table.

• Verifying data insertion with live item counts from DynamoDB.

• Demonstrating Point-in-Time Recovery by rolling back to a specific date and time, then restoring previous data to validate changes.

• Exploring on-demand backups for DynamoDB and restoring the latest data with higher row counts.

With real-world examples and practical demonstrations, this video equips you with the knowledge to confidently handle DynamoDB's data recovery and backup mechanisms. Whether you're a beginner or a seasoned AWS professional, this tutorial is an essential addition to your skillset!

In this step-by-step hands-on tutorial, learn how to assess and address security vulnerabilities in AWS EC2 instances using Amazon Inspector. This detailed guide walks you through the entire process, including:

• Creating an AWS EC2 Instance from scratch, including configuring the instance type and generating a key pair for SSH access.

• Deliberately opening additional ports (21, 23, 24) to simulate potential vulnerabilities for detection.

• Using EC2 Instance Connect to SSH into the Linux instance and installing the Amazon Inspector Agent.

• Setting up an Assessment Target in Amazon Inspector to monitor your EC2 instance.

• Creating an Assessment Template for your desired security checks.

• Running an Amazon Inspector assessment and downloading the detailed PDF report of findings.

• Verifying open ports (21, 23, 24) flagged as vulnerabilities in the assessment report.

This hands-on tutorial provides a real-world approach to identifying and mitigating vulnerabilities, emphasizing the importance of thorough security assessments. Whether you’re preparing for AWS certification, advancing your cloud security skills, or both, this video equips you with the knowledge to confidently use Amazon Inspector for EC2 instance security.

Ready to boost your AWS security expertise? Watch and follow along now!

Ready to host your own static website effortlessly? In this hands-on tutorial, we’ll walk you through the process of setting up S3 Static Website Hosting from start to finish. Here’s what you’ll learn:

• Creating an S3 Bucket from scratch to host your static website.

• Uploading essential HTML files, including index.html (welcome message) and error.html (custom error page).

• Configuring the S3 Bucket Policy using JSON code to enable public access for the website.

• Enabling Static Website Hosting for the S3 bucket, and setting index.html as the index document and error.html as the error document.

• Testing the static website by accessing its URL in a web browser to display the welcome message.

• Validating the custom error page by intentionally changing the URL to simulate errors.

This tutorial provides a hands-on approach to creating and hosting static websites on AWS S3, making it perfect for beginners and professionals looking to master AWS web hosting. Follow along, and by the end, you'll have a fully functioning static website live on the internet!

In this video, we will walk you through the essential steps of working with AWS Glue, a fully managed ETL (Extract, Transform, Load) service. Whether you're a beginner or looking to refresh your knowledge, this comprehensive guide will help you get started with AWS Glue.

What You'll Learn:

1. Ingesting Data: Learn how to upload a sample CSV file from your local computer to an S3 bucket, setting it as the source file for your ETL pipeline.

2. Creating an ETL Pipeline: Step-by-step instructions to create an ETL pipeline in AWS Glue to evaluate data quality, including checking row count and making schema changes.

3. Schema Change Module: Discover how to modify the schema using Glue's schema change module, ensuring your data structure meets your requirements.

4. Loading Target Data: Understand how to load the processed data into a different S3 bucket as the target file.

5. Glue Job Configuration: Gain insights into configuring basic Glue job details, such as selecting the worker type and the requested number of workers, to optimize your ETL operations.

Key Highlights:

1. Hands-on demonstration with clear and concise explanations

2. Real-world examples to solidify your understanding

3. Tips and best practices for efficient ETL processing

AWS Services Used:

1. AWS S3

2. AWS Glue

Take a deep dive into AWS automation with this hands-on tutorial showcasing S3 bucket creation automation and CloudWatch logs live tailing using AWS Lambda. This practical walkthrough includes:

• Creating a Lambda Function with a properly configured IAM role to grant the required permissions.

• Automating S3 Bucket Creation through the Lambda function and verifying the bucket's successful creation.

• Configuring the Lambda function to store CloudWatch Logs in the automatically created S3 bucket.

• Triggering the Lambda function to generate CloudWatch Logs and confirming log entries.

• Exploring CloudWatch Log Groups to perform live tailing of logs via CloudWatch → Log Groups → Live Tail.

• Validating all events, including automatic S3 bucket creation and Lambda function invocations, by tailing CloudWatch Logs.

By the end of this tutorial, you'll gain practical knowledge on using Lambda for automation and efficiently monitoring logs with CloudWatch. Perfect for developers, cloud enthusiasts, and anyone preparing for AWS certifications.

Start building and automating today—watch the tutorial now!

In this end-to-end hands-on tutorial, explore the full workflow of AWS Kinesis Producer and Consumer functionality. This step-by-step guide covers all critical aspects, including:

• Creating a Kinesis Data Stream and understanding the concept of shards for scalable data streaming.

• Setting up an S3 Bucket to serve as the source, uploading an input file (test.txt).

• Configuring a Lambda Function with the appropriate IAM permissions to automate data processing.

• Enabling event notifications from S3 bucket properties, including event types like put, post, copy, and multipart upload.

• Setting up the Kinesis Producer via Lambda triggers to stream data from the S3 bucket into the Kinesis Data Stream.

• Demonstrating how to verify CloudWatch Log Groups, including both producer and consumer logs, to confirm streamed data, such as the content of test.txt.

• Validating all events, from automatic data streaming in Kinesis to log entries in CloudWatch.

This hands-on tutorial equips you with the practical knowledge to effectively manage AWS Kinesis streaming and integrate it with S3, Lambda, and CloudWatch. Perfect for cloud engineers, data professionals, and AWS learners.

Start building real-world AWS solutions now—watch the tutorial!

Learn how to query data stored in an S3 bucket using Amazon Athena in this hands-on tutorial ! From setting up an S3 bucket and uploading a CSV file to configuring Amazon Athena from scratch, we cover it all:

1. Create an S3 bucket and upload your CSV file from your local computer.

2. Set up Amazon Athena, including creating a workgroup and specifying the query results location.

3. Use AWS Glue Data Catalog to create a database, add and configure table properties for CSV data with a comma (,) delimiter, and define the schema.

4. Finally, run SQL queries on your data using Amazon Athena.

Perfect for beginners or anyone looking to efficiently query large datasets on AWS. Watch now and follow along!

Learn how to effectively use the Data API with Amazon Aurora Serverless in this step-by-step, hands-on tutorial. Perfect for developers looking to set up and configure a reliable dev/test database environment, this course covers:

• Creating and configuring a security group for the Aurora database with inbound and outbound rules.

• Setting up and configuring an RDS Aurora MySQL Serverless database.

• Generating credentials for the database, including creating a username and password, and applying a preconfigured security group.

• Establishing a connection to the Aurora database using the Data API and the generated credentials.

• Using the RDS Query Editor to create a new database, design a table, and insert dummy data values.

• Verifying the inserted values using SELECT query statements in Aurora Serverless.

Whether you're a beginner or seasoned professional, this tutorial equips you with the essential skills to manage serverless databases efficiently. Join us and elevate your database management expertise!

Unlock the full potential of AWS Cost Explorer with this comprehensive, hands-on tutorial. Designed for developers, IT professionals, and cloud enthusiasts, this course walks you through:

• Analyzing costs and usage breakdowns across various AWS services in your account.

• Demonstrating different visualizations, such as bar graphs and line graphs, to track spending patterns.

• Exploring the Billing and Payments section to configure report parameters like date range and dimensions, including AWS regions.

• Learning how to redeem AWS credits, including promotional codes, to save on costs.

• Creating and configuring AWS Cost Anomaly Detection to monitor service costs by setting up alerts, specifying thresholds, and assigning email recipients.

With clear, step-by-step instructions, this video empowers you to manage your AWS expenses like a pro. Start your cost optimization journey today!

In this comprehensive hands-on tutorial, we dive deep into the world of AWS Data Engineering. Join us as we demonstrate essential data engineering tasks and best practices using AWS services.

Here’s what we’ll cover:

1. Data Quality Checks: Ensure row count is greater than 99 and verify the presence of primary keys in all records.

2. Filter Expression: Apply filter expressions to refine your data.

3. Custom SQL Expression: Fetch only two specific columns from a table using a custom SQL query.

4. Inner Join Using AWS Glue: Learn to perform efficient inner joins with AWS Glue.

5. File Format Conversion: Convert source files from .csv to Parquet using AWS Glue jobs.

6. Schema Inference with AWS Glue Crawler: Automatically infer the schema from S3 source files.

Watch as we demonstrate how to upload input files to an S3 bucket's "source" folder from your local computer and store the transformed files in the "target" folder using Glue jobs. We’ll guide you through every step to ensure your data pipelines are robust, efficient, and cost-effective.