How to Create an AWS S3 Bucket Using CloudBolt CMP with AutoCodeWizard

Introduction

In today’s fast-paced cloud automation world, the ability to quickly generate code that interacts with various cloud providers is essential. That’s why I’m excited to share a step-by-step guide on how to use AutoCodeWizard to generate a Python CloudBolt CMP Blueprint that automates the creation of an AWS S3 bucket.

Overview of What We’ll Cover

In this blog post, we’ll dive into the following:

• Step 1: Setting up the prompt to create an AWS S3 bucket.
• Step 2: Understanding how AutoCodeWizard generates the CloudBolt CMP Blueprint.
• Step 3: Reviewing the generated Python code.
• Step 4: Running the Blueprint in CloudBolt CMP.
• Step 5: Integrating the Blueprint with AWS using boto3 and CloudBolt ResourceHandlers.
• Step 6: Assigning a CMP CustomField to the new resource.

Let’s get started!

Step 1: Setting Up the Prompt

AutoCodeWizard makes generating Python code for CloudBolt CMP Blueprint creation incredibly simple. The first step is to set up a prompt that tells the system what kind of Blueprint we want to create.

Here’s the prompt we’ll use for this task:

Generate a Python CloudBolt CMP Blueprint using the following inputs: bucketName, rhName, bucketSize. Connect to my AWS ResourceHandler identified by the rhName, retrieve the aws_region from the CMP Environment, and create an S3 bucket of the size specified by bucketSize in GB. Check if a CMP CustomField named aws_s3_bucketsize exists, and if not, create it. Finally, assign the aws_s3_bucketsize CustomField to the newly created CMP Resource.

This prompt asks AutoCodeWizard to generate a Python Blueprint for CloudBolt CMP that interacts with AWS to create an S3 bucket. The inputs are:

• bucketName: The name of the AWS S3 bucket to create.
• rhName: The name of the CloudBolt ResourceHandler that connects to AWS.
• bucketSize: The size of the S3 bucket in GB.

Step 2: How AutoCodeWizard Generates the CMP Blueprint

Once we’ve set up the prompt, AutoCodeWizard goes to work, generating the Python code required to build the CloudBolt CMP Blueprint. Behind the scenes, AutoCodeWizard analyzes the prompt and structures the necessary code to:

• Extract information from CloudBolt CMP, such as ResourceHandler details.
• Interact with AWS via the boto3 library, using the credentials provided by the CMP.
• Create an S3 bucket with the specified size.
• Check for the existence of a CMP CustomField named aws_s3_bucketsize and create it if it doesn’t exist.
• Assign the aws_s3_bucketsize CustomField to the newly created CMP Resource.

Step 3: Reviewing the Generated Code

Here’s a breakdown of the core Python code that AutoCodeWizard generated for us:

import boto3 from cloudbolt.cmp.utils import run_local_action, create_custom_field from cloudbolt.resourcehandlers.aws.models import AWSHandler from cloudbolt.models import CustomField, Environment def run(job, logger=None, **kwargs): bucket_name = kwargs.get("bucketName") rh_name = kwargs.get("rhName") bucket_size = kwargs.get("bucketSize") # in GB aws_rh = AWSHandler.objects.get(name=rh_name) env = Environment.objects.filter(resource_handler=aws_rh).first() aws_region = env.aws_region session = boto3.Session( aws_access_key_id=aws_rh.serviceaccount, aws_secret_access_key=aws_rh.servicepasswd, region_name=aws_region ) s3 = session.client("s3") s3.create_bucket(Bucket=bucket_name) custom_field_name = "aws_s3_bucketsize" custom_field, created = CustomField.objects.get_or_create( name=custom_field_name, defaults={"label": "AWS S3 Bucket Size", "type": "STR"} ) cmp_resource = job.server_set.first() cmp_resource.set_value_for_custom_field(custom_field, bucket_size) cmp_resource.save() return "SUCCESS", f"S3 bucket '{bucket_name}' created and size set to {bucket_size} GB.", ""

Key Features of the Code:

• 1. Retrieve AWS ResourceHandler: The code fetches the AWS ResourceHandler (rhName) from CloudBolt CMP, retrieving important credentials for interacting with AWS.
• 2. Connect to AWS: Using the boto3 library, the script connects to AWS with the necessary credentials and retrieves the aws_region from the CMP Environment.
• 3. Create S3 Bucket: The bucket is created with the specified bucketName in the correct AWS region.
• 4. Assign CustomField: The aws_s3_bucketsize CustomField is assigned to the newly created CMP Resource, storing the size of the S3 bucket.

This Python code automates the creation of an AWS S3 bucket within CloudBolt CMP, streamlining the process and enhancing resource tracking.

Step 4: Running the Blueprint in CloudBolt CMP

Now that we’ve reviewed the code, let’s run the generated Blueprint in our CloudBolt CMP environment. The Blueprint automates the S3 bucket creation process, so all we need to do is provide the inputs:

• bucketName: The name of the S3 bucket to create.
• rhName: The name of the AWS ResourceHandler.
• bucketSize: The size of the S3 bucket in GB.

Once we submit the Blueprint, CloudBolt will execute the Python code, and AutoCodeWizard will handle the S3 bucket creation and CustomField assignment.

Step 5: Integrating with AWS Using boto3 and CloudBolt ResourceHandlers

One of the key elements of this Blueprint is the interaction with AWS via boto3. This Python library allows us to securely connect to AWS using credentials stored in CloudBolt CMP’s ResourceHandler. With just a few lines of code, we can:

• Connect to AWS using the ResourceHandler credentials.
• Retrieve the aws_region from the CMP Environment.
• Create an S3 bucket in the specified region.

Why this is powerful

• Automated Coding: AutoCodeWizard generates the Python code for CloudBolt CMP Blueprints, saving time and effort.
• Efficient Cloud Automation: The Blueprint automates the creation of AWS S3 buckets, streamlining cloud management tasks.
• CustomField Assignment: The code assigns a CustomField to the new resource, enhancing resource tracking and management.

Using AutoCodeWizard, you can automate AWS resource management from within CloudBolt CMP, making it easier to manage infrastructure across multiple environments and teams.

Step 6: Assigning a CMP CustomField to the New Resource

The final part of our script ensures that the S3 bucket’s size is captured within CloudBolt CMP by using a CustomField. If the aws_s3_bucketsize field doesn’t exist, the script creates it automatically and assigns the size specified in the prompt.

This is useful for tracking resource parameters like storage size, cost estimations, and other metadata directly in CMP.

Challenges and How We Overcame Them

While this process is generally straightforward, we did encounter some challenges along the way:

Challenge 1: AWS Region Handling

AWS has region-specific requirements when creating S3 buckets. For example, the us-east-1 region doesn’t require a location constraint, while others do. We incorporated this into the Blueprint code by dynamically checking the region and adjusting the parameters accordingly.

Challenge 2: CustomField Creation

Ensuring that the CustomField is created and assigned properly within CMP was critical. We implemented a check to see if the CustomField already exists and only create it if necessary, making the process more efficient.

Conclusion: AutoCodeWizard Makes Cloud Automation Easy

With AutoCodeWizard, creating an AWS S3 bucket via CloudBolt CMP becomes an automated, seamless task. You can quickly generate Python code, review and refine it, and execute it within CloudBolt CMP without writing everything from scratch.

If you’re managing AWS resources or working within a CloudBolt CMP environment, this automation can save you hours of manual coding and reduce errors. Plus, AutoCodeWizard’s Folders, GitHub integration, and Code Script Review system make managing and refining your scripts even easier.

Ready to Try It Yourself?

Head over to AutoCodeWizard to sign up and start generating your own CMP Blueprints today! And if you’re interested in learning more, check out our other resources and tutorials on the AutoCodeWizard blog.