Cloud Insight AI

Cloud Insight AI is a containerized cloud monitoring and analysis tool that processes cost and log data, generates AI-assisted insights, and visualizes the results on a web dashboard.

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How It Works

1. Configuration

The application is controlled using a YAML configuration file.
This file defines:

• cost and log data sources
• error and cost thresholds
• feature toggles (AI insights, notifications)
• output and reporting settings

2. Containerized Execution

The backend runs inside a Docker container.
GitHub Actions builds the Docker image and pushes it to Amazon ECR.

3. Analyzer Orchestration

Inside the container, analyzer.py acts as the entry point and coordinates:

• configuration loading
• cost analysis
• log processing
• optional AI-based insights
• report generation

4. Cost Analysis

Cost data from data/cost.json is analyzed to identify trends and anomalies.

5. Log Analysis

Application, performance, and security logs are parsed to detect errors, warnings, and recurring issues.

6. AI-Powered Insights

AWS Comprehend is used to extract sentiment, key phrases, and entities from analysis summaries.

7. Report & Metadata Generation

The analyzer generates:

• final_report.json – frontend-ready analysis output
• final_report.txt – human-readable summary
• config.json – JSON representation of the active configuration

8. Storage in S3

Generated JSON artifacts are uploaded to Amazon S3, which acts as a static data source for the dashboard.

9. Frontend Visualization

A static dashboard fetches final_report.json from S3 and renders interactive visualizations.

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Architecture

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Project Structure

  ├── README.md
  ├── _push.sh
  ├── architechture.png
  ├── cloud.png
  ├── config.json
  ├── config.yaml
  ├── data
  │   ├── cost.json
  │   ├── logs.txt
  │   ├── performance-logs.txt
  │   └── security-logs.txt
  ├── docker
  │   └── Dockerfile
  ├── final_report.json
  ├── index.html
  ├── package-lock.json
  ├── requirements.txt
  ├── script.js
  ├── src
  │   ├── analyzer.py
  │   ├── comprehend_client.py
  │   ├── config_loader.py
  │   ├── cost_processor.py
  │   ├── json_report_generator.py
  │   ├── log_processor.py
  │   └── notification_handler.py
  └── style.css

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Tech Stack

• AWS S3 – Stores analysis reports and configuration artifacts
• Amazon ECR – Docker image registry
• Amazon ECS – Executes the containerized analyzer
• AWS IAM – Permissions for ECS, S3, ECR, and CI/CD
• AWS Comprehend – Optional NLP-based insight generation
• GitHub Actions – CI/CD pipeline
• Docker – Containerization
• Python – Backend analysis
• Chart.js – Interactive visualizations
• Frontend – Static HTML, CSS, JavaScript

🎥 YouTube Video

Check out the full walkthrough and demo of Cloud Insight AI on YouTube:

▶️ Watch here: https://youtu.be/7EAaSQkCl3Q