AWS Cloud Detailed Service Descriptions and Projects

Here I have explained 17 AWS services and 10 projects that you can do from simple to complex to show off your skills in AWS Cloud. Each project will build on your understanding of AWS services and their integration.

1. Amazon S3 (Simple Storage Service)

Description: Amazon S3 is an object storage service that offers highly scalable and durable storage for a variety of data types, including backups, archival, and static website content. S3 is designed for durability of 99.999999999% (11 9's) and is ideal for use cases like data backup, storage for big data analytics, and web hosting.

Key Features:

• Scalability: Automatically scales storage to accommodate large volumes of data.

• Durability: Redundant storage across multiple facilities.

• Security: Encryption options and access controls.

• Lifecycle Policies: Automatically transition objects between storage classes and delete them.

Documentation: Amazon S3 Documentation

2. Amazon CloudFront

Description: Amazon CloudFront is a content delivery network (CDN) that caches copies of your content at edge locations around the world to provide faster access to users. It can be used for delivering static and dynamic content, such as web pages, videos, and APIs.

Key Features:

• Global Distribution: Delivers content from edge locations worldwide.

• Low Latency: Reduces latency by caching content closer to end users.

• Security: Supports SSL/TLS encryption and integrates with AWS WAF.

• Customizable: Configurable caching behavior and distribution settings.

Documentation: Amazon CloudFront Documentation

3. Amazon EC2 (Elastic Compute Cloud)

Description: Amazon EC2 provides resizable compute capacity in the cloud, allowing you to launch and manage virtual servers (instances) with varying CPU, memory, and storage configurations. EC2 instances can be used for a range of applications, from web hosting to high-performance computing.

Key Features:

• Flexible Instance Types: Various instance types optimized for different workloads.

• Auto Scaling: Automatically adjusts the number of instances based on demand.

• Spot Instances: Purchase unused capacity at reduced rates.

• Security: Integration with security groups and IAM roles.

Documentation: Amazon EC2 Documentation

4. Amazon IAM (Identity and Access Management)

Description: AWS IAM enables you to securely manage access to AWS services and resources. You can create and manage users, groups, and permissions, and control who can access specific resources.

Key Features:

• Granular Permissions: Define policies for fine-grained access control.

• Multi-Factor Authentication (MFA): Enhance security with MFA.

• Roles and Policies: Assign permissions to roles and manage access for applications.

Documentation: AWS IAM Documentation

5. Amazon RDS (Relational Database Service)

Description: Amazon RDS is a managed relational database service that simplifies the setup, operation, and scaling of relational databases. It supports multiple database engines, including MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server.

Key Features:

• Automated Backups: Regular backups and automated snapshots.

• Multi-AZ Deployments: High availability with automatic failover.

• Scalability: Easily scale compute and storage resources.

Documentation: Amazon RDS Documentation

6. Amazon VPC (Virtual Private Cloud)

Description: Amazon VPC allows you to create a logically isolated network within the AWS cloud where you can launch and manage AWS resources. VPCs can be configured with subnets, route tables, and security groups to control network traffic.

Key Features:

• Customizable Network: Define IP address ranges, subnets, and route tables.

• Private and Public Subnets: Control access to resources within your VPC.

• VPN and Direct Connect: Securely connect your on-premises network to your VPC.

Documentation: Amazon VPC Documentation

7. AWS Lambda

Description: AWS Lambda lets you run code without provisioning or managing servers. It automatically scales and manages infrastructure, executing your code in response to events such as changes to data or system state.

Key Features:

• Event-Driven: Respond to events from AWS services or HTTP requests.

• Scalability: Automatically scales based on demand.

• Cost-Efficient: Pay only for the compute time you use.

Documentation: AWS Lambda Documentation

8. Amazon API Gateway

Description: Amazon API Gateway allows you to create, publish, maintain, monitor, and secure APIs at any scale. It acts as a front door for applications accessing data, business logic, or functionality from backend services.

Key Features:

• API Management: Create and manage RESTful and WebSocket APIs.

• Security: Support for authorization and access control.

• Monitoring: Integrated with CloudWatch for metrics and logging.

Documentation: Amazon API Gateway Documentation

9. Amazon DynamoDB

Description: Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. It supports both document and key-value data models.

Key Features:

• Scalability: Handles large-scale traffic without manual intervention.

• Low Latency: Offers single-digit millisecond response times.

• Integrated Caching: Uses DAX (DynamoDB Accelerator) for in-memory caching.

Documentation: Amazon DynamoDB Documentation

10. Amazon SQS (Simple Queue Service)

Description: Amazon SQS is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications by allowing them to communicate via messages.

Key Features:

• Scalability: Automatically scales to handle the volume of messages.

• Reliability: Ensures messages are delivered at least once.

• Integration: Works with other AWS services like Lambda and SNS.

Documentation: Amazon SQS Documentation

11. Amazon SNS (Simple Notification Service)

Description: Amazon SNS is a fully managed messaging service that enables you to send messages to multiple recipients, including via SMS, email, or application endpoints. It supports pub/sub messaging for distributed systems.

Key Features:

• Topic-Based Messaging: Send messages to multiple subscribers.

• Flexible Delivery: Supports email, SMS, and application notifications.

• Integration: Works with SQS and Lambda for scalable message processing.

Documentation: Amazon SNS Documentation

12. AWS Fargate

Description: AWS Fargate is a serverless compute engine for containers that works with Amazon ECS and Amazon EKS. It allows you to run containers without managing the underlying infrastructure.

Key Features:

• Serverless: No need to provision or manage servers.

• Scaling: Automatically scales to meet the demands of your application.

• Integrated: Works with ECS and EKS for container orchestration.

Documentation: AWS Fargate Documentation

13. AWS CloudFormation

Description: AWS CloudFormation is a service that helps you model and set up your AWS resources using templates. You can use it to automate the deployment of infrastructure as code.

Key Features:

• Infrastructure as Code: Define your infrastructure in a declarative template.

• Automation: Automate the deployment and management of AWS resources.

• Change Management: Track changes and manage updates to your infrastructure.

Documentation: AWS CloudFormation Documentation

14. AWS Global Accelerator

Description: AWS Global Accelerator improves the availability and performance of your applications by directing traffic to the optimal AWS endpoint based on health, geography, and routing policies.

Key Features:

• Global Traffic Management: Directs users to the nearest or most optimal endpoint.

• Improved Performance: Reduces latency by leveraging the AWS global network.

• High Availability: Provides automatic failover in case of endpoint failures.

Documentation: AWS Global Accelerator Documentation

15. Amazon Redshift

Description: Amazon Redshift is a fast, scalable data warehouse service that makes it easy to analyze large volumes of data using SQL and business intelligence tools. It supports petabyte-scale data warehousing.

Key Features:

• Scalability: Scale up or down based on workload requirements.

• Performance: Optimized for high-speed query execution.

• Integration: Works with BI tools and data lakes.

Documentation: Amazon Redshift Documentation

16. AWS Glue

Description: AWS Glue is a fully managed ETL (extract, transform, load) service that makes it easy to prepare and load data for analytics. It automates the data preparation process and integrates with other AWS data services.

Key Features:

• Data Catalog: Automatically discovers and catalogs data.

• ETL Jobs: Create and run ETL jobs to transform and move data.

• Integration: Works with S3, RDS, Redshift, and other AWS services.

Documentation: AWS Glue Documentation

17. Kubernetes on AWS (EKS)

Description: Amazon EKS is a managed Kubernetes service that simplifies deploying, managing, and scaling containerized applications using Kubernetes. It integrates with AWS services and provides a scalable control plane.

Key Features:

• Managed Control Plane: AWS handles the Kubernetes control plane.

• Integration: Works with AWS networking, security, and monitoring services.

• Scalability: Easily scale Kubernetes clusters and workloads.

Documentation: Amazon EKS Documentation

By understanding these services and their functionalities, you'll be well-equipped to build and manage complex cloud infrastructure and applications on AWS.

Getting Started with AWS

Project 1: Simple Website Hosting

Objective: Host a static website on AWS. Services: Amazon S3, Amazon CloudFront.

Service Descriptions:

• Amazon S3: S3 (Simple Storage Service) is an object storage service that offers industry-leading scalability, data availability, security, and performance. You can use S3 to store and retrieve any amount of data at any time, from anywhere on the web. For static website hosting, S3 is used to store HTML, CSS, JavaScript, and other static files.

• Amazon CloudFront: CloudFront is a fast content delivery network (CDN) service that securely delivers data, videos, applications, and APIs to customers globally with low latency and high transfer speeds. It integrates with AWS services like S3 to cache content at edge locations for better performance.

Steps:

1. Create and Configure an S3 Bucket:

   • Amazon S3:

     • Create an S3 bucket to store your website files.

     • Upload HTML, CSS, JavaScript, and other static assets to the bucket.

     • Enable the "Static website hosting" option and specify the index and error documents.

2. Set Bucket Permissions:

   • Amazon S3:

     • Update bucket policies or ACLs to make your website files publicly accessible.

     • Add a bucket policy to grant public read access to your bucket.

3. Set Up CloudFront Distribution:

   • Amazon CloudFront:

     • Create a CloudFront distribution using your S3 bucket as the origin.

     • Configure distribution settings, such as cache behavior and security.

     • Optionally, configure a custom domain and SSL certificate.

Integration:

• Amazon S3 stores your website files.

• Amazon CloudFront acts as a CDN, caching your content at edge locations to reduce latency for users.

Project 2: Basic EC2 Instance

Objective: Launch and configure an EC2 instance. Services: Amazon EC2, Amazon IAM.

Service Descriptions:

• Amazon EC2: EC2 (Elastic Compute Cloud) provides scalable computing capacity in the AWS cloud. It allows you to launch virtual servers, configure security and networking, and manage storage.

• Amazon IAM: IAM (Identity and Access Management) enables you to securely control access to AWS services and resources. You can create and manage AWS users and groups and use permissions to allow or deny their access to AWS resources.

Steps:

1. Launch an EC2 Instance:

   • Amazon EC2:

     • Choose an Amazon Machine Image (AMI) such as Amazon Linux 2.

     • Select an instance type (e.g., t2.micro for free tier).

     • Configure instance details, including VPC, subnet, and auto-assign public IP.

     • Configure storage volumes (EBS).

2. Create and Attach an IAM Role:

   • Amazon IAM:

     • Create an IAM role with policies granting necessary permissions (e.g., S3 read access).

     • Attach the role to your EC2 instance.

3. Configure Security Groups:

   • Amazon EC2:

     • Create a Security Group to define inbound rules (e.g., allow HTTP and SSH access).

     • Attach the security group to your EC2 instance.

4. Connect to Your Instance:

   • Amazon EC2:

     • Obtain the public IP address of the instance.

     • Use SSH to connect to the instance (ensure you have the key pair).

5. Install and Configure Web Server:

   • Amazon EC2:

     • Install a web server (e.g., Apache) with sudo yum install httpd.

     • Configure the web server to serve your website files.

Integration:

• Amazon EC2 provides the compute resources.

• Amazon IAM ensures secure access to other AWS services.

Intermediate Projects

Project 3: LAMP Stack on AWS

Objective: Deploy a LAMP (Linux, Apache, MySQL, PHP) stack on AWS. Services: Amazon EC2, Amazon RDS, Amazon VPC.

Service Descriptions:

• Amazon RDS: RDS (Relational Database Service) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks.

• Amazon VPC: VPC (Virtual Private Cloud) lets you provision a logically isolated section of the AWS cloud where you can launch AWS resources in a virtual network that you define.

Steps:

1. Set Up VPC:

   • Amazon VPC:

     • Create a VPC with a CIDR block (e.g., 10.0.0.0/16).

     • Create public and private subnets.

     • Configure route tables for internet access (public subnet) and isolated internal network (private subnet).

     • Attach an internet gateway to your VPC for public subnet access.

2. Launch EC2 Instance:

   • Amazon EC2:

     • Launch an EC2 instance in the public subnet.

     • Install Apache and PHP (sudo yum install httpd php).

3. Set Up RDS Instance:

   • Amazon RDS:

     • Create an RDS database instance using MySQL.

     • Configure the database instance, including the master username and password.

     • Ensure the RDS instance is launched in the private subnet.

     • Create and configure a security group to allow access from the EC2 instance.

4. Connect EC2 to RDS:

   • Amazon EC2 & RDS:

     • Update PHP application configuration to connect to the RDS endpoint.

     • Ensure security groups allow traffic from the EC2 instance to the RDS instance.

5. Secure Your Setup:

   • Amazon VPC & IAM:

     • Attach an IAM role with least privilege.

     • Refine security group rules to only allow necessary traffic.

Integration:

• Amazon EC2 runs the web server and PHP application.

• Amazon RDS provides a managed MySQL database.

• Amazon VPC ensures secure networking and segregation of resources.

Project 4: Serverless Web Application

Objective: Build a serverless web application. Services: AWS Lambda, Amazon API Gateway, Amazon DynamoDB, Amazon S3, Amazon CloudFront, Amazon Cognito.

Service Descriptions:

• AWS Lambda: Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume.

• Amazon API Gateway: API Gateway enables you to create, publish, maintain, monitor, and secure APIs at any scale.

• Amazon DynamoDB: DynamoDB is a fast and flexible NoSQL database service for any scale.

• Amazon Cognito: Cognito provides authentication, authorization, and user management for your web and mobile apps.

Steps:

1. Set Up S3 and CloudFront for Frontend:

   • Amazon S3:

     • Create an S3 bucket to store frontend files.

     • Enable static website hosting on the bucket.

   • Amazon CloudFront:

     • Create a CloudFront distribution using the S3 bucket as the origin.

     • Configure caching and security settings.

2. Create Lambda Functions:

   • AWS Lambda:

     • Write Lambda functions to handle backend logic.

     • Ensure Lambda functions have necessary permissions to access other AWS services (e.g., DynamoDB).

3. Set Up API Gateway:

   • Amazon API Gateway:

     • Create a REST API and define resources and methods.

     • Integrate the API with Lambda functions.

     • Deploy the API to a stage.

4. Set Up DynamoDB for Data Storage:

   • Amazon DynamoDB:

     • Create a DynamoDB table with the necessary schema.

     • Use the AWS SDK within Lambda to interact with DynamoDB.

5. User Authentication with Cognito:

   • Amazon Cognito:

     • Create a user pool for user sign-up and sign-in.

     • Create an identity pool to grant temporary AWS credentials.

     • Integrate Cognito with API Gateway for authentication and authorization.

Integration:

• Amazon S3 hosts the static frontend.

• Amazon CloudFront speeds up content delivery.

• AWS Lambda handles backend logic.

• Amazon API Gateway exposes the backend API.

• Amazon DynamoDB stores application data.

• Amazon Cognito manages user authentication.

Advanced Projects

Project 5: Infrastructure as Code (IaC) with Terraform

Objective: Manage AWS infrastructure using Terraform. Tools: Terraform.

Service Descriptions:

• Terraform: Terraform is an open-source infrastructure as code software tool that enables you to safely and predictably create, change, and improve infrastructure.

Steps:

1. Set Up Terraform:

   • Terraform:

     • Install Terraform on your local machine.

     • Write Terraform configuration files (.tf) to define your AWS resources.

2. Define AWS Resources:

   • Terraform:

     • Define a VPC, subnets, and route tables.

     • Define EC2 instances and their configurations.

     • Define S3 buckets and their configurations.

3. Apply Terraform Configuration:

   • Terraform:

     • Initialize Terraform with terraform init.

     • Review changes with terraform plan.

     • Apply changes with terraform apply.

4. Manage State and Configuration:

   • Terraform:

     • Use Terraform state files to manage your infrastructure's state.

     • Use version control to manage your Terraform configuration files.

Integration:

• Terraform manages the entire lifecycle of your AWS infrastructure.

Project 6: CI/CD Pipeline with AWS CodePipeline

Objective: Set up a CI/CD pipeline. Services: AWS CodePipeline, AWS CodeBuild, AWS CodeDeploy, Amazon S3, Amazon IAM.

Service Descriptions:

• AWS CodePipeline: CodePipeline is a fully managed continuous delivery service that helps you automate your release pipelines for fast and reliable application and infrastructure updates.

• AWS CodeBuild: CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages that are ready to deploy.

• AWS CodeDeploy: CodeDeploy automates code deployments to any instance, including Amazon EC2 instances and instances running on-premises.

Steps:

1. Set Up CodePipeline:

   • AWS CodePipeline:

     • Create a pipeline and define its stages (source, build, deploy).

2. Configure Source Stage:

   • AWS CodePipeline:

     • Use a source repository (e.g., AWS CodeCommit, GitHub) as the source stage.

3. Configure Build Stage:

   • AWS CodeBuild:

     • Create a build project to compile and test your code.

     • Define a buildspec.yml file to specify build commands and settings.

4. Configure Deploy Stage:

   • AWS CodeDeploy:

     • Create an application and deployment group.

     • Define deployment configurations (e.g., in-place, blue/green).

5. Integrate with S3 and IAM:

   • Amazon S3: Store build artifacts.

   • Amazon IAM: Create roles and policies for CodePipeline, CodeBuild, and CodeDeploy.

Integration:

• AWS CodePipeline orchestrates the CI/CD process.

• AWS CodeBuild compiles and tests the application.

• AWS CodeDeploy handles the deployment to target environments.

• Amazon S3 stores build artifacts.

• Amazon IAM ensures secure access and permissions.

Resume-Worthy Projects

Project 7: Kubernetes on AWS (EKS)

Objective: Deploy and manage Kubernetes clusters on AWS. Services: Amazon EKS, Amazon EC2, AWS IAM, AWS CloudFormation.

Service Descriptions:

• Amazon EKS: EKS (Elastic Kubernetes Service) makes it easy to deploy, manage, and scale containerized applications using Kubernetes.

• Amazon EC2: EC2 (Elastic Compute Cloud) provides the underlying compute resources for EKS worker nodes.

• AWS CloudFormation: CloudFormation helps you model and set up your Amazon Web Services resources so that you can spend less time managing those resources and more time focusing on your applications.

Steps:

1. Set Up EKS Cluster:

   • Amazon EKS:

     • Create an EKS cluster and configure cluster settings.

     • Set up worker nodes (EC2 instances) with appropriate configurations.

2. Configure IAM Roles and Policies:

   • AWS IAM:

     • Create roles for EKS cluster and worker nodes.

     • Attach necessary policies for cluster and node operations.

3. Deploy Applications to EKS:

   • Kubernetes:

     • Use kubectl to configure and manage your EKS cluster.

     • Create Kubernetes manifests (YAML files) for deployments and services.

4. Automate with CloudFormation:

   • AWS CloudFormation:

     • Write CloudFormation templates to define EKS resources.

     • Deploy and manage EKS resources using CloudFormation stacks.

Integration:

• Amazon EKS manages Kubernetes clusters.

• Amazon EC2 provides compute resources for worker nodes.

• AWS IAM manages access and permissions.

• AWS CloudFormation automates infrastructure setup.

Project 8: Scalable Web Application with Microservices Architecture

Objective: Build a scalable web application using microservices architecture. Services: Amazon ECS/EKS, AWS Fargate, Amazon RDS, Amazon S3, Amazon SQS, Amazon SNS, AWS Lambda.

Service Descriptions:

• Amazon ECS/EKS: ECS (Elastic Container Service) and EKS (Elastic Kubernetes Service) are container orchestration services. ECS integrates with AWS Fargate for serverless compute, while EKS manages Kubernetes clusters.

• AWS Fargate: Fargate is a serverless compute engine for containers that works with both ECS and EKS.

• Amazon RDS: RDS (Relational Database Service) provides managed relational databases.

• Amazon S3: S3 (Simple Storage Service) is used for storing and retrieving data.

• Amazon SQS: SQS (Simple Queue Service) offers scalable message queuing.

• Amazon SNS: SNS (Simple Notification Service) provides messaging and notification services.

• AWS Lambda: Lambda runs code without provisioning or managing servers.

Steps:

1. Set Up ECS/EKS Cluster:

   • Amazon ECS/EKS: Create a cluster and configure services.

2. Containerize Microservices:

   • Docker: Create Docker images for each microservice.

   • Amazon ECR: Store Docker images in Elastic Container Registry.

3. Deploy Microservices:

   • Amazon ECS/EKS: Use Fargate for serverless compute or EC2 instances for more control.

   • Service Definitions: Define tasks and services in ECS/EKS.

4. Set Up RDS for Persistent Storage:

   • Amazon RDS: Create a database instance for backend storage.

5. Integrate S3 for Static Assets:

   • Amazon S3: Store and serve static files.

6. Implement Messaging with SQS and SNS:

   • Amazon SQS: Use queues for decoupling microservices.

   • Amazon SNS: Use topics for pub/sub messaging.

7. Use Lambda for Serverless Functions:

   • AWS Lambda: Implement asynchronous processing or event-driven tasks.

Integration:

• Amazon ECS/EKS runs containerized microservices.

• AWS Fargate provides serverless compute for containers.

• Amazon RDS offers managed database services.

• Amazon S3 handles static assets.

• Amazon SQS and SNS manage messaging between microservices.

• AWS Lambda handles serverless functions.

Project 9: Data Pipeline and Analytics

Objective: Create a data pipeline and perform analytics. Services: Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon QuickSight.

Service Descriptions:

• Amazon Kinesis: Kinesis makes it easy to collect, process, and analyze real-time, streaming data.

• AWS Glue: Glue is a fully managed ETL (extract, transform, load) service that makes it easy to prepare and load data for analytics.

• Amazon Redshift: Redshift is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake.

• Amazon QuickSight: QuickSight is a fast, cloud-powered business intelligence service that makes it easy to deliver insights to everyone in your organization.

Steps:

1. Set Up Kinesis Stream:

   • Amazon Kinesis: Create a data stream for real-time data ingestion.

2. Transform Data with AWS Glue:

   • AWS Glue: Create crawlers and jobs to transform and catalog data.

3. Load Data into Redshift:

   • Amazon Redshift: Create a data warehouse and load transformed data.

4. Visualize Data with QuickSight:

   • Amazon QuickSight: Create dashboards and reports based on Redshift data.

Integration:

• Amazon Kinesis ingests real-time data.

• AWS Glue transforms and catalogs data.

• Amazon Redshift stores data for analytics.

• Amazon QuickSight visualizes data for insights.

Project 10: Multi-Region Failover Architecture

Objective: Implement a highly available multi-region failover architecture. Services: Amazon Route 53, Amazon S3, Amazon RDS (Multi-AZ), Amazon CloudFront, AWS Global Accelerator.

Service Descriptions:

• Amazon Route 53: Route 53 is a scalable Domain Name System (DNS) web service designed to route end users to Internet applications.

• Amazon S3: S3 (Simple Storage Service) stores data and objects.

• Amazon RDS (Multi-AZ): RDS provides high availability and failover support for DB instances using Multi-AZ deployments.

• Amazon CloudFront: CloudFront is a CDN service that caches content for fast delivery.

• AWS Global Accelerator: Global Accelerator improves the availability and performance of your applications with global users by using the AWS global network.

Steps:

1. Set Up Multi-Region S3 Buckets:

   • Amazon S3: Create buckets in multiple regions and enable replication.

2. Set Up Multi-AZ RDS Instances:

   • Amazon RDS: Create Multi-AZ RDS instances for high availability.

3. Configure Route 53 for Failover:

   • Amazon Route 53: Create DNS records with failover routing policies.

   • Health Checks: Set up health checks to monitor endpoints.

4. Set Up CloudFront for Content Delivery:

   • Amazon CloudFront: Distribute content across multiple edge locations.

5. Implement Global Accelerator for Performance:

   • AWS Global Accelerator: Improve performance and availability for global users.

Integration:

• Amazon Route 53 routes traffic based on health and performance.

• Amazon S3 stores data with cross-region replication.

• Amazon RDS (Multi-AZ) provides database availability.

• Amazon CloudFront caches and delivers content globally.

• AWS Global Accelerator optimizes performance for global access.

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