Is QStash included in this skill?

Yes, it includes patterns for @upstash/qstash to handle background job publishing, scheduling, and at-least-once delivery guarantees in serverless architectures.

How does the skill handle security credentials?

The skill enforces the use of Redis.fromEnv() to ensure that sensitive credentials like REST URLs and tokens are never hardcoded in your source code.

What is the performance impact of using HTTP for Redis?

HTTP adds 5-15ms of overhead per request compared to <1ms for TCP. This skill mitigates this by enforcing the use of redis.pipeline() to batch multiple commands into a single round-trip.

Does this skill support Redis Pub/Sub?

No, the Upstash REST API does not support Pub/Sub or blocking commands. For those use cases, a TCP-based client like ioredis is required in a long-running server environment.

Why use Upstash instead of standard Redis for serverless apps?

Serverless and edge runtimes cannot maintain persistent TCP connections; Upstash uses a REST/HTTP-based client that works universally in these environments without connection pooling overhead.

Upstash Serverless Redis & QStash

Name: Upstash Serverless Redis & QStash
Author: agents-inc

byagents-inc

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Gestión de Bases de Datos

Integrates Upstash serverless Redis and QStash for high-performance edge computing, rate limiting, and background jobs.

This skill provides optimized patterns for using Upstash's serverless data platform within Claude Code, specifically designed for environments where traditional TCP connections are unavailable. It enables developers to implement high-performance caching, atomic transactions, and complex rate-limiting algorithms in serverless functions and edge runtimes like Cloudflare Workers or Vercel Edge. By standardizing REST-based Redis commands, automatic JSON serialization, and QStash background messaging, this skill ensures robust and scalable data management for modern web applications.

Características Principales

01Automatic JSON serialization and type-safe data handling

02Command batching via redis.pipeline() to minimize HTTP latency

03Push-based background job scheduling and reliable messaging with QStash

04Optimized REST-based Redis patterns for connectionless edge runtimes

05Pre-built rate limiting algorithms including sliding window and token bucket

065 GitHub stars

Casos de Uso

01Implementing precise API rate limiting with global analytics

02Building low-latency caches for serverless functions and edge workers

03Managing asynchronous background tasks and message queues in connectionless environments

Características Principales

01Automatic JSON serialization and type-safe data handling

02Command batching via redis.pipeline() to minimize HTTP latency

03Push-based background job scheduling and reliable messaging with QStash

04Optimized REST-based Redis patterns for connectionless edge runtimes

05Pre-built rate limiting algorithms including sliding window and token bucket

065 GitHub stars

Casos de Uso

01Implementing precise API rate limiting with global analytics

02Building low-latency caches for serverless functions and edge workers

03Managing asynchronous background tasks and message queues in connectionless environments