Skill UI

This comprehensive guide provides a structured roadmap for migrating logistics operations from legacy sources (e.g., spreadsheets, old APIs, ERPs) to the modern Flexport API. It details advanced architectural patterns such as the Strangler Fig pattern, product catalog migration, dual-write implementation, and phased cutover strategies, ensuring a smooth and reliable transition for complex supply chain digitization.

This skill provides a comprehensive observability stack for Flexport logistics integrations. It sets up Prometheus metrics for API health tracking, uses structured logging (pino) for debugging, implements OpenTelemetry tracing for latency analysis, and defines actionable Grafana dashboards and alert rules. This ensures reliable, performant, and fully monitored logistics operations.

A guide to optimizing API interactions with Flexport for logistics data. This skill implements advanced techniques including maximizing page sizes for bulk fetching, implementing LRU caching for frequently accessed data (e.g., product details), managing rate limits using parallel request queues (p-queue), and utilizing webhook-driven cache invalidation to ensure data freshness and high throughput.

This module provides robust patterns for managing rate limits and throttling when integrating with external APIs (e.g., Flexport). It covers three key strategies: monitoring rate limit headers (X-RateLimit-*), implementing exponential backoff with jitter for transient 429 or 5xx errors, and utilizing queue-based throttling for safe, controlled bulk operations. It ensures resilient and reliable API communication.

This guide provides production-ready patterns for interacting with the Flexport REST API v2 in TypeScript and Python. It teaches crucial best practices, including implementing a singleton client for state management, handling paginated data streams, automatic retry logic, and using Zod for robust response validation, ensuring reliable logistics integrations.

This guide provides comprehensive security standards for integrating with the Flexport API. It covers critical best practices such as webhook signature verification, secure API key rotation, implementing least-privilege access controls, and data redaction for handling sensitive logistics and customs data. Essential for maintaining compliance and preventing data breaches in supply chain operations.

This skill provides advanced integration for deploying applications on Fly.io, focusing on edge computing architectures. It covers building production-ready Docker images, configuring `fly.toml` for services and health checks, and executing sophisticated deployment strategies like blue-green and canary releases. It ensures reliable, scalable deployment across multiple regions, including automated rollbacks and micro-VM optimization.

This guide demonstrates how to deploy a minimal "Hello World" application to the Fly.io platform. It covers two primary deployment methods: using the simple `flyctl` Command Line Interface (CLI) for quick setup, and utilizing the advanced Machines API for programmatic deployment. This skill is ideal for beginners starting a new Fly.io project, or for implementing robust, globally distributed edge compute infrastructure.

This guide provides comprehensive strategies to significantly boost the performance and reliability of applications deployed on Fly.io. Techniques covered include eliminating cold starts (auto-stop/start), right-sizing Virtual Machines based on workload demands, implementing multi-region deployment for low latency, and optimizing connection pooling for databases. Essential for scaling modern SaaS applications.

This utility provides comprehensive solutions for managing rate limits when interacting with the Fly.io Machines API. It implements advanced patterns like Token Bucket rate limiting, exponential backoff, and request batching. This ensures that automation scripts remain robust and reliable, even during high-churn operations such as large-scale deployments or auto-scaling events, preventing common 429 throttle errors.

A comprehensive TypeScript SDK providing production-ready patterns for interacting with the Fly.io Machines REST API. It includes a typed client for managing the entire machine lifecycle—creation, state polling, and deletion—across multiple global regions. Features like robust error handling, rate-limit retries, and deployment builders ensure reliable multi-region orchestration for edge computing applications.

This guide provides methods for robust monitoring and automation tailored for services deployed on Fly.io. It covers key areas including polling the Machines API to detect state changes, implementing comprehensive health check endpoints, processing structured logs using tools like `jq`, and automating deployment notifications within CI/CD pipelines. Essential for achieving high availability and reliable operations.