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Year
2025
Tech & Technique
AST Parsing, npm CLI, GraphQL, TypeScript, Prisma
Description
Problem: Most backend performance issues in production stem from poorly implemented pagination — unbounded queries, deep offsets, missing limits, and unstable sorting — that go undetected until they cause real scaling failures.
Solution: Built Cloud Meter, a production-grade CLI tool published to npm that statically analyzes backend codebases (no runtime required) using AST parsing to detect pagination anti-patterns, score the codebase from 0–100, and deliver actionable fix recommendations.
Key Features:
Technical Implementation:
Impact: Delivered a zero-runtime, production-grade CLI that catches pagination scaling risks before they hit production — installable in one command, CI-ready out of the box, and covering the full ORM, SQL, and GraphQL ecosystem.
Solution: Built Cloud Meter, a production-grade CLI tool published to npm that statically analyzes backend codebases (no runtime required) using AST parsing to detect pagination anti-patterns, score the codebase from 0–100, and deliver actionable fix recommendations.
Key Features:
- ☁️ Static AST Analysis: Scans JS/TS files, SQL queries, and ORM patterns without executing any code
- 📊 Scoring Engine: 0–100 score with severity-based deductions — Missing LIMIT (−30), Deep OFFSET (−20), No ORDER BY (−15), and more
- 🔍 12 Detection Rules: Catches missing LIMIT, deep OFFSET, unstable cursors, unbounded endpoints, dynamic sort injection, infinite scroll risks, and concurrent write exposure
- 🛠️ Self-Guiding CLI: Every command outputs what to run next — fully interactive or headless CI mode
- ⚙️ Config System: Project-level
cloud-meter.config.jsonwith saved defaults for path, output mode, severity threshold, and ignored directories - 🚦 CI/CD Integration:
--mode ciexits with code 1 when findings exceed configured severity threshold — drop into any pipeline
Technical Implementation:
- Built CLI with Node.js and TypeScript, published as
cloud-meteron npm with global install support - Implemented AST-based pattern matching for Prisma, Mongoose, Sequelize, TypeORM, raw SQL, and GraphQL Relay-style resolvers
- Designed a modular rulebook with configurable severity weights and heuristic penalties for dynamic sorting and concurrency risk
- Added framework detection for Express, NestJS, Fastify, and Koa route/controller/service layers
- Supported monorepo structures with auto-detection of
apps/api,services/api, andbackenddirectories - Persisted analysis cache for
recommendcommand to serve fix recipes from the last scan without re-running
Impact: Delivered a zero-runtime, production-grade CLI that catches pagination scaling risks before they hit production — installable in one command, CI-ready out of the box, and covering the full ORM, SQL, and GraphQL ecosystem.
My Role
CLI Tool Author & Publisher
Designed, built, and published the full tool end-to-end:
Designed, built, and published the full tool end-to-end:
- 🏗️ Architecture: Designed the modular command structure (
analyze,init,recommend,doctor,config) with a shared config loader and analysis cache - 🔬 Detection Engine: Implemented 12 AST-based detection rules targeting pagination anti-patterns across ORMs, raw SQL, and GraphQL resolvers
- 📈 Scoring Model: Built the severity-weighted deduction system with grade thresholds (Production Grade → Critical)
- 🚦 CI/CD Mode: Wired up non-interactive
--mode ciwith exit codes and JSON output for pipeline integration - 📦 npm Publishing: Packaged and published to npm as
cloud-meterwith global CLI entrypoint and TypeScript type checking - 🧪 Testing & Tooling: Added test suite, build pipeline, and local link workflow for iterative development