Gemini Powered Migrations To Google Cloud¶

This project provides a set of Gemini CLI custom commands to accelerate assessments and migration of workloads and data from Amazon Web Services (AWS) and Azure to Google Cloud. The Gemini CLI custom commands use Gemini to analyze data, identifying suitable resources for migration, and augmenting traditional assessments with AI.

Prerequisites¶

To effectively utilize these instructions, ensure the following are set up:

Gemini CLI: Installed and configured. For installation instructions, visit geminicli.com.
Source Cloud Provider Inventory Details: Access to the inventory of objects to migrate (such as virtual machines, storage buckets, workloads, etc.) from your source environment for analysis. Sample inputs are available in the test-data/ directory.

Gemini CLI custom commands¶

This project provides Gemini CLI custom commands in the .gemini/commands directory for doing the following:

Evaluate inventories
Refactor and modernize applications
Generate sample data

Evaluate inventories¶

The custom commands in this section are aimed at helping you accelerate the evaluation and inventory assessments.

aws-container-migration-analysis: This command analyzes cluster and object inventory files from Amazon EKS workloads to generate a Google Kubernetes Engine (GKE) migration plan. The command expects a path to the directory containing the inventory output files. You must first generate these files using the Kubernetes Cluster Discovery Tool.

Usage:
```
/aws-container-migration-analysis [PATH/TO/KUBERNETES_INVENTORY/DIRECTORY]
```
Usage (Try with Sample Data):
```
/aws-container-migration-analysis test-data/aws-container-migration-analysis
```
/aws-lambda-to-cloud-run-poc-selection: This command assists in reviewing AWS Lambda inventories to identify suitable functions for migration to Cloud Run. Example:
```
/aws-lambda-to-cloud-run-poc-selection Review files in test-data/aws-lambda-assessment-results for migration to Cloud Run.
```
/aws-s3-bucket-poc-selection: This command assists in reviewing Amazon S3 buckets inventories to identify suitable buckets for migration to Google Cloud Storage. Example:
```
/aws-s3-bucket-poc-selection review files in test-data/aws-s3-assessment-results for migration to US EAST region.
```
/aws-s3-migration-analysis: This command analyzes an Amazon S3 inventory file to assess workload complexity and automatically generate tailored Google Cloud infrastructure code based on the specific data profile.

To learn how to generate the required inventory file, see Build an inventory of your Amazon S3 buckets.

Usage (Load your own file):
```
/aws-s3-migration-analysis [PATH/TO/YOUR/S3_INVENTORY_FILE.csv]
```
Usage (Try with Sample Data):
```
/aws-s3-migration-analysis test-data/aws-s3-migration-analysis/SAMPLE-S3_inventory.csv
```
You can review the example output for this command at: test-data/sample-selection/aws-s3-migration-analysis.md
/azure-blob-storage-poc-selection: This command helps analyze Azure Blob Storage inventories to suggest containers that are good candidates for migration to Google Cloud Storage.
```
/azure-blob-storage-poc-selection review files in test-data/azure-blob-storage-assessment-results for migration to US EAST region.
```

Refactor and modernize applications¶

The commands listed in this section are aimed at refactoring and modernizing the source code of the applications to migrate:

/aws-lambda-refactor-python-app-to-cloud-run: This command helps you refactor AWS Lambda functions and applications to run on Cloud Run:
```
/aws-lambda-refactor-python-app-to-cloud-run path/to/your/aws-lambda/function
```
Where path/to/your/aws-lambda/function is the path to the source code of the AWS Lambda function or application to refactor.
/dotnet-sql-server-application-modernization: This command helps you refactor legacy .NET applications to port them to a more modern .NET version that can run in a container. Also, it refactors SQL Server usage to PostgreSQL.
```
/dotnet-sql-server-application-modernization path/to/your/dotnet/app
```
Where path/to/your/dotnet/app is the path to the source code of the .NET application to refactor.

Generate sample data¶

The commands listed in this section are useful to generate sample data when you don't have a source environment available, but you need data to evaluate other commands:

/generate-sample-aws-lambda-list-functions: This command helps you generate sample aws lambda list-functions command output:
```
/generate-sample-aws-lambda-list-functions test-data/aws-lambda-assessment-results/aws-lambda-list-functions-sample.json
```
/generate-sample-aws-lambda-get-function: This command helps you generate sample aws lambda get-function command output:
```
/generate-sample-aws-lambda-get-function test-data/aws-lambda-assessment-results/aws-lambda-list-functions-sample.json
```
The command takes the output of the aws lambda list-functions command as input.
/generate-sample-aws-lambda-get-function-configuration: This command helps you generate sample aws lambda get-function-configuration command output:
```
/generate-sample-aws-lambda-get-function-configuration test-data/aws-lambda-assessment-results/aws-lambda-list-functions-sample.json
```
The command takes the output of the aws lambda list-functions and aws lambda get-function commands as input.
/generate-sample-aws-lambda-get-policy-and-list-event-source-mappings: This command helps you generate sample aws lambda get-policy and aws lambda list-event-source-mappings command output:
```
/generate-sample-aws-lambda-get-policy-and-list-event-source-mappings test-data/aws-lambda-assessment-results/aws-lambda-list-functions-sample.json
```
The command takes the output of the aws lambda list-functions, aws lambda get-function, and aws lambda get-function-configuration commands as input.

The sample output in the test-data directory has been generated using these commands.

Setup and usage instructions¶

Install Gemini CLI. For installation instructions, visit geminicli.com.

Clone the repository:

git clone https://github.com/GoogleCloudPlatform/cloud-solutions.git

Configure the Gemini CLI custom commands in the cloud-solutions/projects/gemini-powered-migrations-to-google-cloud directory so that they are available as global user commands or project commands. For more information about configuring Gemini CLI custom commands, see Custom commands.
Change the working directory to the directory where you stored the files you want to assess with Gemini CLI, such as inventory files from other cloud providers.
Start Gemini CLI:
```
gemini
```
Run the Gemini CLI authentication command, and follow instructions:
```
/auth
```
Run one of the provided custom commands.
Review generated report with recommendations.

Test Data¶

The test-data/ directory contains sample inventories from Amazon S3 and Azure Blob Storage. These files are structured to mimic real-world cloud provider outputs and are used by the custom Gemini CLI commands to demonstrate the migration selection process without requiring actual cloud environments. This data includes:

aws-container-migration-analysis/: Contains mock Kubernetes clusters and objects inventory files for Amazon EKS workloads.
aws-lambda-assessment-results/: Contains mock data for AWS Lambda functions.
aws-s3-assessment-results/: Contains mock data for S3 bucket locations, policies, and bucket lists.
aws-s3-migration-analysis/: Contains resources for the S3 migration analysis command.
azure-blob-storage-assessment-results/: Contains mock data for Azure Blob Storage container locations, policies, and blob lists.
sample-selection/: Stores example output files generated by the Gemini CLI custom commands, showing how a proof of concept migration selection might look.