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Looking for experience!

Cloud Waste Sniper is an enterprise-grade FinOps platform built to solve a $100B+ annual problem: cloud waste. Enterprises lose billions on idle EC2 instances, orphaned EBS volumes, unused Elastic IPs, and forgotten snapshots. Manual FinOps audits are slow, expensive, and error-prone. Our solution is a fully automated pipeline that scans → prices → compares → patches → commits in seconds, not weeks. The core innovation is our Bright Data integration. Instead of relying on stale, hardcoded pricing data, Cloud Waste Sniper uses Bright Data's SERP API to query Google search results in real-time for live AWS, Azure, and GCP retail prices. AWS pricing pages use aggressive bot detection — Bright Data handles this transparently, returning structured JSON we parse with regex and sanity-range validation. The pipeline works end-to-end: our FastAPI backend triggers an AWS scanner (boto3) that detects 6 resource types. Live prices from Bright Data are fetched and compared across 3 cloud providers. Our custom Terraform parser uses structural brace-depth tracking to surgically modify .tf files — setting count = 0 for removal or downsizing compute instances. Every remediation is committed as a Git branch + PR, creating a full audit trail. The frontend is a multi-page dark SPA with Chart.js visualizations — doughnut charts, horizontal bar charts, and a 12-month savings projection. One-click executive Markdown reports are exportable for stakeholders. Key features: multi-resource scanning (EBS, EC2, Snapshots, Elastic IPs, NAT Gateways, Load Balancers), live multi-cloud price intelligence, auto-remediation via IaC, Git-backed audit trail, interactive dashboards, and scan history logging. The system runs in mock mode with no AWS credentials needed, making it fully demonstrable. Built with Python 3.10+, FastAPI, Bright Data SERP API, boto3, Chart.js 4.x, PyGitHub, and deployed on Vercel.
31 May 2026
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ShipSage is an AI-powered DevOps readiness analyzer and pipeline generator that transforms how teams prepare repositories for production deployment. The core problem: every new project requires manual setup of Docker, CI/CD, monitoring, Kubernetes, and infrastructure configurations. Existing generators create files blindly without telling teams what is actually missing or what still needs review. ShipSage fills this gap. How it works: 1. Repository Intelligence — Analyzes any public GitHub repository to detect language, framework, project type, and critical files automatically. 2. Readiness Scoring — Scores production readiness using weighted DevOps signals including tests, CI/CD, Docker, documentation, monitoring, security, and infrastructure-as-code. 3. Starter Asset Generation — Generates ready-to-use Dockerfile, Docker Compose, Kubernetes manifests, CI/CD pipelines, AWS Terraform, ELK monitoring stack, and environment configurations. 4. AI Codebase Analysis — Provides detailed architecture summaries and module breakdowns describing every file and directory in the repository. 5. AWS Cost Estimation — Estimates monthly cloud deployment costs with per-service breakdowns. 6. Interactive Q&A — Users can ask natural-language questions about the repository and receive context-aware answers grounded in actual file contents. ShipSage runs entirely in a free rule-based mode for demos, with optional IBM Watsonx Granite integration for deeper AI-powered analysis. Built with Python, FastAPI, and a modern dark-themed dashboard UI. Developed using IBM Bob IDE across three structured sessions covering architecture, feature building, and submission preparation. Live Demo: https://shipsage.onrender.com GitHub: https://github.com/AbhishekKharat04/repo-sage
17 May 2026