What Is Aws?
AWS, or Amazon Web Services, is a cloud computing platform offered by Amazon. It provides a wide range of cloud computing services, including computing power, storage, database management, machine learning, networking, and more. AWS allows businesses and individuals to access and utilize computing resources on-demand, without having to build and manage their own physical infrastructure. With its scalability, flexibility, and global reach, AWS has become a leading choice for businesses of all sizes to build, deploy, and manage their applications and services in the cloud.
1.Deploy A Python Web App In Aws Ec2
Steps To Deploy A Python Web App In Aws Ec2
Source Code:-https://github.com/pranavkdileep/Image-Background-Remover
1. Launch an EC2 instance: Go to the AWS Management Console, navigate to EC2 service, and launch a new EC2 instance. Choose an appropriate Amazon Machine Image (AMI) that includes Python, such as Amazon Linux 2 or Ubuntu, and configure other instance settings as needed.
2. Connect to the EC2 instance: Once the EC2 instance is launched, connect to it using SSH or Session Manager in the AWS Management Console.
3. Update the system: Run the following commands to update the system packages on the EC2 instance:
```
sudo yum update -y # For Amazon Linux 2
sudo apt update # For Ubuntu
sudo apt upgrade -y # For Ubuntu
```
4. Install Gunicorn: Install Gunicorn on the EC2 instance using the following command:
```
sudo yum install gunicorn -y # For Amazon Linux 2
sudo apt install gunicorn -y # For Ubuntu
```
5. Upload your Python web app: Upload your Python web app code to the EC2 instance. You can use tools like SCP or SFTP to transfer your code to the instance. Alternatively, you can also use version control systems like Git to clone your code directly on the instance.
6. Start Gunicorn: Navigate to the directory where your Python web app code is located, and start Gunicorn with the appropriate command. For example, if your web app entry point is `app.py` and the app is using Flask, you can start Gunicorn with the following command:
```
nohup gunicorn app:app -b 0.0.0.0:8000
```
This assumes that your Flask app object is named `app` and it listens on port 8000. Replace the command with the appropriate command for your specific web app framework.
7. Configure Security Group: Make sure to configure the security group of your EC2 instance to allow incoming traffic on the appropriate port (e.g., 8000 in the above example) so that your web app is accessible from the internet.
That's it! Your Python web app should now be up and running in AWS EC2 using Gunicorn. You can access it using the public IP or domain name of your EC2 instance on the appropriate port. Please note that this is a basic setup and may require additional configurations depending on your specific web app requirements, such as setting up a reverse proxy, domain name mapping, SSL certificate, etc.
AWS Auto Scaling Ec2
Sure! Here are the high-level steps to create an Auto Scaling group for EC2 instances in AWS:
1. Create an EC2 Launch Template: A Launch Template is a configuration template that specifies the instance type, AMI, security groups, and other settings for the EC2 instances that will be launched in the Auto Scaling group. You can create a Launch Template using the AWS Management Console, AWS CLI, or AWS SDKs.
2. Configure Auto Scaling Group: Go to the AWS Management Console, navigate to the Auto Scaling service, and click on "Create Auto Scaling group". Select the Launch Template that you created in step 1. Configure other settings such as the desired capacity, maximum size, and minimum size of the Auto Scaling group.
3. Configure Scaling Policies: Scaling policies define the rules for scaling the Auto Scaling group up or down based on metrics such as CPU utilization, network traffic, or custom metrics. You can configure scaling policies such as target tracking scaling, simple scaling, or scheduled scaling. You can configure scaling policies using the AWS Management Console, AWS CLI, or AWS SDKs.
4. Configure Load Balancer (Optional): If you want to distribute traffic across multiple instances in the Auto Scaling group, you can configure a load balancer. You can use an Application Load Balancer or a Network Load Balancer to distribute traffic to instances in the Auto Scaling group. You can configure the load balancer settings using the AWS Management Console, AWS CLI, or AWS SDKs.
5. Configure Auto Scaling Notifications (Optional): You can configure notifications for events related to your Auto Scaling group, such as scaling events, instance launch or termination, or failed health checks. You can configure notifications using Amazon SNS or Amazon Simple Queue Service (SQS). You can configure notifications using the AWS Management Console, AWS CLI, or AWS SDKs.
6. Review and Create: Review the configuration of your Auto Scaling group and click on "Create Auto Scaling group" to create the Auto Scaling group. AWS will automatically launch instances based on the Launch Template and scale the group up or down based on the scaling policies you have configured.
That's it! Your Auto Scaling group for EC2 instances is now created and ready to automatically scale based on the rules you have defined. Please note that this is a basic setup and may require additional configurations depending on your specific requirements, such as instance termination policies, instance protection, lifecycle hooks, etc.
2. Create a AWS RDS Mysql Database
Sure! Here are the high-level steps to create an AWS RDS MySQL database:
1. Navigate to the AWS Management Console: Go to the AWS Management Console (https://aws.amazon.com/) and sign in to your AWS account.
2. Go to RDS service: In the AWS Management Console, search for "RDS" in the search bar or navigate to the "Database" section, and click on "RDS" to open the Amazon RDS service console.
3. Click on "Create database": In the Amazon RDS service console, click on the "Create database" button to start the database creation process.
4. Select "Standard Create": In the "Create database" wizard, choose the "Standard Create" option to create a new RDS instance with standard settings.
5. Choose "MySQL" engine: In the "Engine options" section, choose "MySQL" as the database engine you want to use for your RDS instance.
6. Choose "Production" or "Dev/Test" use case: In the "Use case" section, choose either "Production" or "Dev/Test" depending on the intended use of your database. This selection will impact the default settings for your RDS instance.
7. Configure instance details: Configure the instance details, such as DB instance identifier, master username, and password. You can also configure other settings, such as the DB instance size, storage, availability zone, VPC, etc., as per your requirements.
8. Configure advanced settings: Optionally, you can configure advanced settings such as backups, maintenance, monitoring, etc. You can also specify additional options such as the database name, character set, parameter group, etc.
9. Configure VPC and security group: Choose the VPC and subnet where you want to create the RDS instance. You can also configure the security group settings to control the inbound and outbound traffic to your RDS instance.
10. Review and create: Review all the settings in the "Review" tab and click on the "Create database" button to create the RDS MySQL instance.
11. Wait for creation: Wait for the RDS MySQL instance to be created. This may take a few minutes depending on the configuration and size of the instance.
12. Connect to the MySQL instance: Once the RDS MySQL instance is created, you can obtain the endpoint (hostname) and port number from the RDS instance details page in the AWS Management Console. You can then use any MySQL client to connect to the RDS MySQL instance using the endpoint, port, and master username/password configured during the instance creation process.
That's it! You have now created an AWS RDS MySQL database. You can use this database for your applications by connecting to it using the endpoint and credentials provided by AWS.
Connect Database Using Mysql Client
And Inser Some Values
Syntax:
INSERT INTO table_name (column1, column2) VALUES (value1, value2);
3.Create Aws s3 Storage
steps to create an S3 bucket using AWS Console:
1. Sign in to the AWS Management Console at https://aws.amazon.com/.
2. Navigate to the S3 service.
3. Click on the "Create bucket" button.
4. Enter a unique name for your bucket. Bucket names must be globally unique across all of AWS, and follow specific naming conventions, such as being DNS-compliant and lowercase.
5. Choose the region where you want your bucket to be created. This determines the physical location of the bucket's data.
6. Optionally, you can configure additional settings, such as setting up logging, versioning, and access permissions.
7. Click on the "Create bucket" button to create your S3 bucket.
Note: Creating an S3 bucket may result in charges, as S3 is a paid service. Make sure to review the AWS pricing documentation for S3 to understand the costs associated with using S3 buckets.
Alternatively, you can also use the AWS CLI (Command Line Interface) or AWS SDKs (Software Development Kits) to create an S3 bucket programmatically using code.