AWS Cloud Projects: 5 Real-World Labs for Engineers
Build production-ready skills with step-by-step AWS projects. Ideal for software engineers and cloud practitioners.
Course Description
Engineers often know AWS theory but struggle to apply it in real scenarios. Without hands-on practice, designing scalable cloud solutions feels abstract and risky. This course bridges that gap through five progressive projects that mirror actual industry tasks. You'll work on serverless apps, high-availability setups, migrations, secure architectures, and IoT analytics, gaining confidence to handle complex AWS environments. Each project includes video walkthroughs, case studies from similar real-world implementations, and practical labs where you build from scratch.
Course Curriculum
5 sections • 16.50 hours total length
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Introduction to AWS Cloud and Project Setup (15m)
Set up your AWS account, install necessary tools, and understand the project goal.
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Core AWS Services for Serverless: S3 and IAM (20m)
Learn how to configure S3 buckets and IAM roles for secure access.
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Building a Lambda Function with AWS SAM (25m)
Write and deploy a Lambda function using the AWS Serverless Application Model.
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Event-Driven Design: S3 Triggers and Lambda Invocation (18m)
Set up S3 events to trigger Lambda for image processing.
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Image Processing Logic with Python and Boto3 (22m)
Implement code to resize images and save thumbnails.
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Storing Metadata with DynamoDB (20m)
Use DynamoDB to log processed images for tracking and queries.
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Testing and Deploying the Serverless Application (15m)
Run end-to-end tests and deploy the app to AWS.
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Understanding High Availability and WordPress Architecture (15m)
Explore why HA matters and how to design a scalable WordPress site.
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Setting Up a VPC and Subnets for WordPress (20m)
Create a virtual network with public and private subnets for isolation.
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Launching EC2 Instances with Auto Scaling Groups (25m)
Configure EC2 instances to handle traffic spikes automatically.
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Configuring Elastic Load Balancer for Traffic Distribution (18m)
Set up an ELB to distribute requests across multiple instances.
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Database Layer with Amazon Aurora for WordPress (22m)
Deploy and manage a highly available Aurora database for WordPress.
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Shared File Storage with Amazon EFS (20m)
Use EFS to store WordPress files that are accessible to all instances.
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Installing and Configuring WordPress on the Infrastructure (30m)
Walk through the WordPress installation on the built HA environment.
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Security Best Practices for WordPress on AWS (18m)
Secure your setup with security groups, NACLs, and encryption.
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Performance Tuning and Caching Strategies (22m)
Optimize WordPress performance using caching plugins and AWS services.
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Monitoring and Maintenance with CloudWatch (15m)
Set up alarms and logs to monitor the health of your WordPress site.
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Introduction to Cloud Migration: The 6 Rs Strategy (15m)
Learn the different migration strategies and when to use them.
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Assessing the Legacy Application with AWS Application Discovery Service (20m)
Use tools to profile the existing app and plan the migration.
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Planning the Migration with AWS Migration Hub (18m)
Create a migration plan and track progress using the hub.
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Lift-and-Shift to EC2: Moving the Application (25m)
Execute the migration by deploying the app on EC2 instances.
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Database Migration to Amazon RDS (22m)
Migrate the database from on-premises to a managed RDS instance.
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Post-Migration Optimization and Cost Management (20m)
Optimize the migrated app for performance and reduce costs.
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Setting Up CloudWatch for Monitoring and Alerts (18m)
Implement monitoring to ensure the migrated app runs smoothly.
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Testing and Validation: Ensuring a Successful Migration (15m)
Conduct thorough testing to verify functionality and performance.
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Principles of 3-Tier Architecture and Defense-in-Depth (15m)
Understand the layers and security principles for robust apps.
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Designing a VPC with Multiple Availability Zones (20m)
Set up a VPC spanning AZs for redundancy and isolation.
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Creating Public and Private Subnets for Each Tier (22m)
Configure subnets to separate web, app, and database tiers.
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Configuring Security Groups for Web, App, and DB Tiers (18m)
Define inbound and outbound rules to control traffic flow.
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Setting Up NAT Gateway for Outbound Internet Access (15m)
Allow instances in private subnets to access the internet securely.
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Deploying the Web Tier with ECS Fargate (25m)
Use containers to run the web application without managing servers.
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Implementing the Application Tier with ECS Fargate (22m)
Deploy the backend logic in a containerized environment.
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Database Tier with Amazon RDS in a Private Subnet (20m)
Launch an RDS instance securely in a private subnet.
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Integrating All Tiers with Load Balancers and Service Discovery (25m)
Connect the tiers using ALB and service discovery for communication.
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Implementing Logging and Monitoring with CloudWatch (18m)
Set up centralized logging and monitoring for all tiers.
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Security Audits and Compliance Checks (20m)
Review security configurations and ensure compliance with best practices.
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Scaling and Auto-Adjustment Based on Load (22m)
Configure auto-scaling policies to handle varying traffic.
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Introduction to IoT on AWS and Project Overview (15m)
Get an overview of AWS IoT services and the project goals.
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Setting Up AWS IoT Core for Device Communication (20m)
Register devices and configure MQTT topics for data ingestion.
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Streaming Data with Kinesis Data Firehose (22m)
Use Firehose to collect and deliver IoT data to storage.
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Building a Data Lake with Amazon S3 (18m)
Store raw and processed data in an S3 data lake for analysis.
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Querying Data with Amazon Athena (25m)
Run SQL queries on data stored in S3 using Athena.
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Visualizing Data with Amazon QuickSight (20m)
Create dashboards and reports to visualize IoT data trends.
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Introduction to Anomaly Detection with AWS Lookout for Metrics (18m)
Learn how Lookout for Metrics identifies unusual patterns in data.
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Configuring Lookout for Metrics on IoT Data (22m)
Set up detectors to automatically find anomalies in your data stream.
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Setting Up Alerts and Notifications for Anomalies (15m)
Configure SNS to send alerts when anomalies are detected.
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Integrating Anomaly Detection with QuickSight Dashboards (20m)
Overlay anomaly insights on your visualizations for better context.
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Handling Data Quality and Pipeline Errors (18m)
Implement error handling and data validation in the pipeline.
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Optimizing Costs for IoT Analytics Pipeline (22m)
Learn strategies to reduce costs without compromising performance.
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Review and Next Steps: Extending the IoT Project (15m)
Summarize what you've built and explore ideas for further development.
Course Details
- Duration: 16.50 hours
- Level: Adaptative
- Language: English
- Lessons: 50+ video lessons
- Categories: DevOps
- Access: Lifetime access
- Device: Mobile & Desktop
- Certificate: Yes. After completion and Exam
The course is totally free. Seriously appreciated attribution
