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Interactive Audio Lesson
Listen to a student-teacher conversation explaining the topic in a relatable way.
Project 1: Hosting a Static Website
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Today, we will start with hosting a static website on Amazon S3. Can anyone tell me what a static website consists of?
It usually includes HTML, CSS, and sometimes JavaScript?
Exactly! Now, the first step is preparing your website files. Do you remember which files we need?
We need an index.html and an error.html page.
Great! Now let's log into the AWS Console and navigate to the S3 Dashboard. Remember, we have to create a new bucket with a globally unique name. What else do we need to ensure?
We should disable 'Block all public access' under permissions.
Correct! This will allow public access to your website files. Let's move on to uploading the website files and enabling static website hosting.
How do we set the bucket policy?
Good question! You'll need to insert a policy that allows public access, which we can copy from the documentation.
To summarize, we create the required HTML files, open S3, create a bucket with public access, upload files, enable static hosting, set the bucket policy, and finally access the site via the S3 endpoint.
Project 2: Deploying a Web Application Using EC2 and RDS
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Next, we'll focus on deploying a web application using EC2 and RDS. What's the first step we should take?
We need to create an RDS instance with MySQL?
Exactly! Make sure to use Free Tier settings. Remember to set the proper username and password. Why is it important to make the RDS instance publicly accessible for testing?
So we can access it from our EC2 instance?
Correct! Now, when we launch an EC2 instance, what operating system should we choose?
Amazon Linux 2.
Right! Then we will need to install a web server. What command would we use for that?
We can use `sudo yum install -y httpd php php-mysqlnd`.
Well done! After installing the web server, we need to deploy our app code. Always double check the database connection. Can anyone tell me why?
To ensure that the application can correctly access and store data in our RDS instance.
Great summary! This process will give you hands-on experience in deploying full-stack applications.
Project 3: Implementing a Serverless Function
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For our next project, let's look at serverless functions using AWS Lambda. Can anyone explain what that means?
It's a way to run code without managing servers, right?
Exactly! First, we'll create a DynamoDB table for storing form submissions. What will be the primary key?
The ID, which can be generated uniquely.
Perfect! Next, we'll create a Lambda Function. Why do we need to attach an IAM role?
To give our function permissions to interact with DynamoDB.
Absolutely! Then we will write the function code. Can someone summarize what this code does?
It processes form data and saves it to DynamoDB.
Exactly! Finally, we'll create an API Gateway, enabling external access to our Lambda function. What will we test with?
We can use Postman to test sending requests.
Great! Weβve covered creating a serverless architect using AWS tools, highlighting how efficiently we can collect and store data.
Project 4: Setting Up a CI/CD Pipeline
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Our final project will focus on setting up a CI/CD pipeline. Can anyone explain what CI/CD stands for?
Continuous Integration and Continuous Deployment.
Correct! This process helps automate our code deployment. The first step is to prepare our code repository. What should we do first?
We need to push our website or app code to GitHub.
Exactly! Next, we'll create a CodePipeline in AWS. Where do we source it from?
From GitHub using OAuth integration.
Exactly! We also have an optional build step with AWS CodeBuild. After that, how do we deploy?
We deploy to S3 for static sites or CodeDeploy for EC2.
Exactly! What do we need for configuration to work with CodeDeploy?
We create an appspec.yml file for deployment specifics.
Perfect! Finally, we can test the pipeline by pushing a commit to GitHub and observing the process. Itβs a crucial method for ensuring that our changes are tested and deployed correctly.
Introduction & Overview
Read a summary of the section's main ideas. Choose from Basic, Medium, or Detailed.
Quick Overview
Standard
This section provides detailed instructions for four AWS projects, focusing on hosting a static website, deploying a web application, implementing a serverless function, and setting up a CI/CD pipeline. Each project is structured to build confidence in using AWS services through hands-on activities.
Detailed
Steps Overview
This section presents a series of practical AWS projects that demonstrate how to apply theoretical knowledge in real-world applications. Each project guides the learner through step-by-step processes, building key skills in utilizing Amazon Web Services.
Project 1: Hosting a Static Website on Amazon S3
- Goal: Host a fully functional static website (HTML/CSS/JS) on S3 with public access.
- Key Steps: Prepare website files, create an S3 bucket with proper permissions, upload files, enable static website hosting, set bucket policy, and access the website using the S3 endpoint.
Project 2: Deploying a Web Application Using EC2 and RDS
- Goal: Deploy a dynamic web application (e.g., PHP + MySQL) using Amazon EC2 and Amazon RDS.
- Key Steps: Create an RDS instance, launch an EC2 instance, install necessary software, deploy the application code, and test connectivity.
Project 3: Implementing a Serverless Function with AWS Lambda
- Goal: Create a Lambda function to process form input and store data in DynamoDB.
- Key Steps: Create a DynamoDB table, define a Lambda function with necessary permissions, write the processing code, create an API Gateway, and test the function.
Project 4: Setting Up a CI/CD Pipeline for Automated Deployments
- Goal: Establish a continuous integration and deployment pipeline from GitHub to AWS.
- Key Steps: Prepare the code repository, create a CodePipeline, configure CodeDeploy, and test the pipeline through a GitHub commit push.
Overall, these projects provide a comprehensive foundation for deploying and managing applications in the cloud using AWS technologies.
Audio Book
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Project 1: Hosting a Static Website on Amazon S3
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Project 1: Hosting a Static Website on Amazon S3
π Goal:
Host a fully functional static website (HTML/CSS/JS) on S3 with public access.
β
Steps:
1. Prepare your website files:
- Create an index.html and error.html page.
2. Login to AWS Console and go to the S3 Dashboard.
3. Create a new bucket:
- Bucket name must be globally unique.
- Disable "Block all public access" under Permissions.
4. Upload website files to the bucket.
5. Enable static website hosting:
- Go to the bucket's Properties tab.
- Enable Static website hosting and set index/error documents.
6. Set Bucket Policy to make files public:
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "PublicReadGetObject",
"Effect": "Allow",
"Principal": "*",
"Action": "s3:GetObject",
"Resource": "arn:aws:s3:::your-bucket-name/*"
}
]
}
- Access your website using the S3 website endpoint.
Detailed Explanation
The objective is to host a static website using Amazon S3. First, you create the necessary HTML files, specifically an index.html to serve as the home page, and an error.html for any errors. Next, you log into the AWS Console and navigate to the S3 Dashboard. You will create a new bucket, which acts like a directory for your files. Keep in mind that the bucket name must be unique across all AWS accounts worldwide. You must also ensure that public access is enabled by disabling the block if you want your website to be accessible online. Once your files are uploaded, you will configure your bucket to host a static website, specifying your index and error documents in the properties tab. To allow users to access your website, you need to set a Bucket Policy to make the files public, which is done through the provided JSON configuration. Finally, you can access your live website using the S3 endpoint URL.
Examples & Analogies
Think of Amazon S3 like a warehouse where you store all the components of your online store. The front of the warehouse, which is the index.html file, welcomes the customers, while the error.html file serves as a sign to redirect lost customers. The bucket acts as the warehouse itself, which needs to have a unique name like any business must be unique to operate. By allowing access, you're essentially opening the doors of your warehouse for customers to come in and browse the products (web pages).
Project 2: Deploying a Web Application Using EC2 and RDS
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Project 2: Deploying a Web Application Using EC2 and RDS
π Goal:
Deploy a dynamic web app (e.g., PHP + MySQL) using Amazon EC2 and Amazon RDS.
β
Steps:
1. Create an RDS Instance:
- Choose MySQL.
- Use Free Tier settings.
- Set username/password and database name.
- Make it publicly accessible for testing.
2. Launch an EC2 instance:
- Choose Amazon Linux 2.
- Use Free Tier t2.micro.
- Open ports 22 (SSH), 80 (HTTP).
3. Connect to EC2 via SSH and install web server + MySQL client:
sudo yum update -y sudo yum install -y httpd php php-mysqlnd sudo systemctl start httpd sudo systemctl enable httpd
- Deploy Web App Code:
- Upload using SCP or create manually.
- Include a DB connection script pointing to your RDS endpoint.
- Test Connection to RDS and browse app using EC2 public IP.
Detailed Explanation
This project focuses on deploying a dynamic web application. You start by creating an RDS (Relational Database Service) instance, selecting MySQL as your database engine and establishing it using free-tier settings to avoid costs. You create a username and password, and ensure itβs publicly accessible for easier testing. Next, you'll launch an EC2 (Elastic Compute Cloud) instance that acts as your server. Here, you select Amazon Linux 2 and use a t2.micro instance, which is free under AWS's free tier. You must open specific network ports for SSH (22) and HTTP (80) to allow access. Once your EC2 instance is running, you connect to it using SSH and install a web server along with the MySQL client. After setting up the server, you'll deploy your web application code by uploading it or creating it directly on EC2, ensuring to include a database connection script that links to your RDS instance. Finally, by navigating to the EC2 public IP, you can test the application and its connectivity to the database.
Examples & Analogies
Imagine you are setting up a restaurant. The RDS instance is like the kitchen where all the food (database) is stored, and the EC2 instance is the restaurant building itself where customers (users) come to dine. You have to ensure that your kitchen is well stocked (properly set up database) and accessible (publicly available RDS). When the restaurant opens, customers can come in (through the EC2 instance) and enjoy their meals (interact with the application) confidently knowing that the kitchen is providing them with everything they need.
Project 3: Implementing a Serverless Function with AWS Lambda
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Project 3: Implementing a Serverless Function with AWS Lambda
π Goal:
Create a simple AWS Lambda function that processes form input (e.g., a contact form) and stores it in DynamoDB.
β
Steps:
1. Create a DynamoDB Table:
- Table name: FormSubmissions
- Primary key: id
2. Create a Lambda Function:
- Choose Node.js or Python.
- Attach IAM role with DynamoDB write access.
3. Write Function Code (example in Python):
import json
import boto3
import uuid
def lambda_handler(event, context):
db = boto3.resource('dynamodb')
table = db.Table('FormSubmissions')
data = json.loads(event['body'])
table.put_item(Item={
'id': str(uuid.uuid4()),
'name': data['name'],
'email': data['email']
})
return {
'statusCode': 200,
'body': json.dumps('Data saved successfully!')
}
- Create API Gateway:
- Setup POST endpoint to trigger Lambda.
- Enable CORS.
- Deploy API and test using Postman or a frontend form.
Detailed Explanation
The aim of this project is to create a serverless application using AWS Lambda. The first step involves creating a table in DynamoDB named 'FormSubmissions', which will store the data submitted through a contact form. The primary key for this table is defined as 'id'. After setting up the table, you will create a Lambda function. You can choose either Node.js or Python as your programming language, and itβs essential to grant this function an IAM role that allows it to write data to your DynamoDB table. In this Lambda function, you will utilize the Boto3 library to interact with DynamoDB. The code provided takes the body of the incoming event (data from the contact form), parses it, and inserts a new item with a unique id, name, and email into the table. The next step is to create an API Gateway that connects to this Lambda function, setting it up to respond to POST requests, and enabling Cross-Origin Resource Sharing (CORS) if needed. Finally, after deploying the API, you can test it by sending requests through tools such as Postman or connecting it to a frontend form.
Examples & Analogies
Think of your Lambda function as an automated assistant handling customer queries. When someone fills out a contact form (like ringing the assistant's bell), the assistant quickly notes the details in a log (DynamoDB). Each log entry has a unique ID number to ensure every customer query is recorded (similar to giving each visitor a ticket with a number). The API Gateway is like the front desk where visitors submit their requests, ensuring that every inquiry is directed to the assistant correctly. This setup allows the assistant to efficiently process multiple customer inquiries while keeping things organized.
Project 4: Setting Up a CI/CD Pipeline for Automated Deployments
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Project 4: Setting Up a CI/CD Pipeline for Automated Deployments
π Goal:
Set up a pipeline to automatically deploy code changes from GitHub to EC2 or S3.
β
Steps:
1. Prepare Code Repository:
- Push website/app code to a GitHub repository.
2. Create CodePipeline:
- Source: GitHub (OAuth integration)
- Build: AWS CodeBuild (optional, or use passthrough)
- Deploy:
- S3: for static sites
- CodeDeploy: for EC2
3. Create CodeDeploy Application and Deployment Group:
- Attach IAM roles and EC2 tags.
- Install CodeDeploy agent on EC2 instance.
4. Configure appspec.yml for CodeDeploy:
version: 0.0
os: linux
files:
- source: /
destination: /var/www/html
hooks:
AfterInstall:
- location: scripts/restart_server.sh
timeout: 60
runas: root
- Test the Pipeline:
- Push a new commit to GitHub.
- Watch it flow through the pipeline and deploy automatically.
Detailed Explanation
In this project, the goal is to create a Continuous Integration/Continuous Deployment (CI/CD) pipeline, which automates the deployment of your project code to either EC2 or S3. The process starts by preparing your code repository: you need to push your application or website code to a GitHub repository. Next, you set up a CodePipeline that links this repository as the source, using OAuth for integration. You can optionally include AWS CodeBuild in the process for building the code, but a passthrough method can also be used. During the deployment step, if your project is a static site, it will go to S3; otherwise, for an EC2 deployment, you will use CodeDeploy. To manage the deployment, you need to create a CodeDeploy application and a deployment group, making sure to assign the necessary IAM roles and EC2 tags. Furthermore, you must install the CodeDeploy agent on your EC2 instance to facilitate deployments. The appspec.yml file is crucial for CodeDeploy as it defines deployment configurations, including where to copy files to and any post-installation scripts. Finally, after setting everything up, you can test the pipeline by making a new commit in GitHub and observe how it flows through the pipeline to deploy the updated version automatically.
Examples & Analogies
Think of the CI/CD pipeline as an efficient factory assembly line for your software. Your GitHub repository is like the warehouse that stores raw materials (your code). When you push changes (like adding new materials), the pipeline works like machines on an assembly line, automatically pulling materials from the warehouse, assembling them, and then sending the finished product (your application) directly to store shelves (EC2 or S3). This automation minimizes the manual labor involved while ensuring that the latest product is always available for customers, much like a well-oiled manufacturing process.
Definitions & Key Concepts
Learn essential terms and foundational ideas that form the basis of the topic.
Key Concepts
-
Static website hosting: Hosting a website using S3 which serves static content.
-
Dynamic applications: Applications that generate dynamic content via backend interactions.
-
Serverless architecture: Running applications without managing server infrastructure.
-
Continuous Integration/Continuous Deployment (CI/CD): Automating the process of software delivery.
-
Amazon S3 Bucket Policy: Rules defining permissions for different users to access S3 buckets.
Examples & Real-Life Applications
See how the concepts apply in real-world scenarios to understand their practical implications.
Examples
-
Example of hosting a static website on S3: A personal portfolio site that showcases creative work.
-
Example of deploying a web application: A blog platform that captures user inputs, stored in an RDS MySQL database.
Memory Aids
Use mnemonics, acronyms, or visual cues to help remember key information more easily.
π΅ Rhymes Time
-
To host a site on S3, make HTML your key. Buckets are unique, let the world peek!
π Fascinating Stories
-
Imagine you are a wizard casting spells; S3 is your magic domain, where every website file you cast makes your pages beautifully display!
π§ Other Memory Gems
-
For AWS deployment, remember the rule: EC2 hosts, RDS stores, Lambda executes, and S3 shows your web jewels.
π― Super Acronyms
Lambda - L for Logic, A for Automation, M for Management, B for Backend, D for Data, A for Application serving independently!
Flash Cards
Review key concepts with flashcards.
Glossary of Terms
Review the Definitions for terms.
-
Term: Amazon S3
Definition:
A scalable storage service for storing and retrieving any amount of data, especially used for hosting static websites.
-
Term: EC2
Definition:
Elastic Compute Cloud, a web service that provides secure and resizable compute capacity in the cloud.
-
Term: RDS
Definition:
Relational Database Service, a managed database service that provides easy to operate and scalable database hosting.
-
Term: AWS Lambda
Definition:
A serverless computing service that runs code in response to events and automatically manages the underlying infrastructure.
-
Term: CI/CD
Definition:
Continuous Integration and Continuous Deployment, practices that automate the process of code development, testing, and deployment.
-
Term: DynamoDB
Definition:
A fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.