Create readme.MD

[bearycoolAI]

Describe your PR

_Summarize your changes here 👍 Okay here it goes, I have been imagining within this .devcontainer... certain upgrade infrastructure protocols that we can utilize within the clever cloud domain, this begins the stub and onboarding the .devcontainer into the Clever-Cloud Protcol.

Checklist

• My PR is related to an opened issue : #
• I've read the contributing guidelines

Reviewers

Who should review these changes? @CleverCloud/reviewers

[github-actions]

You updated . This content is also listed on external doc. Issue number has been created and assigned to you 🫵👁️👄👁️

See it or modify it here:
*

This unique comment uses the very cool taoliujun/action-unique-comment. Thank you <3

[github-actions]

Deployment has finished 👁️👄👁️ Your app is available here

[bearycoolAI]

Project Documentation

Overview

This project comprises two modular engines, imaginerunner.cpp and codingrabbitai.cpp, designed for dynamic task execution and CI/CD workflow automation. The project also includes a robust setup for Clever Cloud .devcontainer configuration and automation scripts.

---

Engines

imaginerunner.cpp

Description

A modular engine designed for task execution with a focus on:

• Concurrency: Executes tasks in parallel using threads.
• Dynamic Configuration: Manages environment configurations dynamically.
• API Integration: Supports authenticated API requests with OAuth via libcurl.

Key Features

• Task Management: Modular tasks with error handling, executed in parallel.
• Environment Handling: Dynamically loads and manages variables from configuration files.
• API Requests: Authenticated interactions with external services.
• Error Handling: Ensures robust execution with detailed logging.

---

codingrabbitai.cpp

Description

An automation engine focused on RabbitProtocol CI/CD workflows with capabilities such as:

• Building modular components.
• Running tests.
• Deploying to external systems like Azure.

Key Features

• CI/CD Automation: Encapsulates build, test, and deploy workflows.
• Environment Integration: Dynamically loads .env files for flexible configurations.
• Task Modularization: Pre-defined, reusable tasks (e.g., building with gcc, deploying to Azure).
• Detailed Logging: Logs command execution and errors for troubleshooting.

---

Comparison of Core Features

Feature | imaginerunner.cpp | codingrabbitai.cpp -- | -- | -- Task Management | Modular tasks with parallel execution. | Encapsulates CI/CD steps. Environment Handling | Dynamic file-based variable management. | Manages .env files dynamically. API Integration | OAuth via libcurl. | No explicit API integration. Concurrency | Parallel task execution with threads. | Sequential execution. Error Handling | Exception-safe task execution. | Logs errors for task/command failures. Build & Deployment | Generic task execution logic. | Pre-defined CI/CD workflows.

---

Strengths

imaginerunner.cpp

• Concurrency: Efficient parallel task execution with thread management.
• API Integration: Modular OAuth interactions with external services.
• Dynamic Configuration: Flexible environment variable handling.
• Error Resilience: Robust handling with detailed logs.

codingrabbitai.cpp

• Automation Focus: Comprehensive CI/CD workflow automation.
• Modular Tasks: Reusable and pre-defined for common CI/CD steps.
• Environment Integration: Seamless .env file handling.
• Detailed Logging: Comprehensive logs for debugging.

---

Areas for Improvement

imaginerunner.cpp

• Task Dependencies: Add support for task dependencies to improve workflow coordination.
• CI/CD Support: Introduce specific modules for builds and deployments.
• Task State Management: Implement status tracking for tasks (e.g., success, failure).

codingrabbitai.cpp

• Concurrency: Introduce parallel execution for independent tasks.
• Error Handling: Add retries for transient failures (e.g., network issues).
• API Integration: Include modular API handlers like in imaginerunner.cpp.
• Code Organization: Refactor repetitive logic into reusable utilities.

---

Potential Enhancements

1. Merge Engine Strengths:

   • Combine imaginerunner.cpp’s API integration and concurrency features with codingrabbitai.cpp’s CI/CD focus.

2. Unified Scheduler:

   • Develop a task scheduler capable of handling both parallel and sequential tasks with dependency resolution.

3. Dynamic Task Loading:

   • Enable dynamic task configuration via JSON or YAML files for flexibility.

4. Enhanced Logging:

   • Include timestamps, task statuses, and execution summaries in logs.

5. Cross-Platform Support:

   • Ensure compatibility across Linux, macOS, and Windows.

6. Improved Error Handling:

   • Add categorized handling for specific errors (e.g., network or command failures).

---

Clever Cloud .devcontainer Configuration

Description

The Clever Cloud .devcontainer setup defines consistent development environments for Ubuntu 24.04 and Windows Server 2025.

Files to Include

Dockerfile.ubuntu

Dockerfile
Copy code
FROM ubuntu:24.04
RUN apt-get update && apt-get install -y 

build-essential 

curl 

wget 

git 

cmake 

clang 

&& apt-get clean
COPY clangfile.ubuntu.json /workspace/

WORKDIR /workspace

Dockerfile.windows

Dockerfile
Copy code
FROM mcr.microsoft.com/windows/server:ltsc2025

SHELL ["cmd", "/S", "/C"]
RUN powershell -Command 

"Install-PackageProvider -Name NuGet -Force; 

Install-Module -Name DockerMsftProvider -Repository PSGallery -Force; 

Install-Package -Name docker -ProviderName DockerMsftProvider -Force"
COPY clangfile.windows.json C:/workspace/

WORKDIR C:/workspace

.devcontainer.json

json
Copy code
{

"name": "Clever Cloud Dev Environment",

"context": "..",

"dockerComposeFile": [

"./docker-compose.yml"

],

"service": "ubuntu",

"workspaceFolder": "/workspace",

"customizations": {

"vscode": {

"extensions": [

"ms-vscode.cpptools",

"ms-azuretools.vscode-docker"

]

}

}

}

docker-compose.yml

yaml
Copy code
version: '3.8'

services:

ubuntu:

build:

context: .

dockerfile: Dockerfile.ubuntu

volumes:

- .:/workspace

network_mode: none

command: sleep infinity
windows:

build:

context: .

dockerfile: Dockerfile.windows

volumes:

- .:/workspace

network_mode: none

command: cmd /c "ping -t localhost"

Clang Configuration Files

clangfile.ubuntu.json

json
Copy code
{

"compiler": "clang-14",

"flags": ["-Wall", "-Wextra"],

"includes": ["/usr/include", "/usr/local/include"]

}

clangfile.windows.json

json
Copy code
{

"compiler": "clang-cl",

"flags": ["/Wall"],

"includes": ["C:/Program Files (x86)/Windows Kits/10/Include"]

}

---

Benefits of This Setup

• Reproducible Development Environment:

  • Consistent environments across systems for Ubuntu and Windows.

• Clever Cloud Integration:

  • Seamless deployment and container management.

• Scalable Setup:

  • Easily extendable to new OS configurations or tools.

[github-actions]

🚀 You updated your review app. Check it here

[github-actions]

You closed this PR and deleted the review app 👋