expanso-rate-limiting

Apply configurable rate limiting to streaming data pipelines with backpressure and overflow handling.

1|Updated Feb 1, 2026
One-click install
npx skills add https://github.com/expanso-io/expanso-skills --skill expanso-rate-limiting
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: expanso-rate-limiting
Source: https://github.com/expanso-io/expanso-skills/tree/main/skills/recipes/rate-limiting
Command: npx skills add https://github.com/expanso-io/expanso-skills --skill expanso-rate-limiting

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of managing high-volume data streams by implementing rate limiting, preventing downstream systems from being overwhelmed and ensuring stable data processing.

Core Features & Use Cases

  • Configurable Rate Limiting: Set precise limits on the number of messages processed per unit of time.
  • Backpressure Handling: Automatically adjusts to prevent data loss when processing rates exceed consumption.
  • Overflow Management: Defines strategies for handling data that cannot be processed within the defined limits.
  • Use Case: In a real-time analytics pipeline, this skill can ensure that incoming event data is processed at a rate that your database can handle, preventing performance degradation.

Quick Start

Run the rate limiting pipeline with a limit of 1000 messages per second.

Frequently Asked Questions about expanso-rate-limiting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I apply rate limiting to a Kafka data streaming pipeline?

Rate limiting applies configurable limits to messages processed per unit of time in streaming data pipelines. It uses deterministic flow control to prevent downstream systems from being overwhelmed during high-volume data ingestion.

What is backpressure in data streaming and when do I need it?

Backpressure automatically adjusts data flow to prevent loss when processing rates exceed consumption limits. You need backpressure in real-time analytics and event stream management to ensure stable processing and prevent database performance degradation.

How do I handle overflow when setting message processing rate limits?

Overflow management defines specific strategies for handling data that cannot be processed within your configured rate limits. This ensures controlled data ingestion by determining how excess messages are treated when limits are exceeded.

Can I control data flow for real-time analytics without losing event data?

Configurable rate limiting controls data flow for real-time analytics while backpressure handling prevents data loss. By setting precise message limits per second, the pipeline adjusts automatically to match your database consumption rate.

Do I need additional dependencies to implement backpressure for event stream management?

No additional dependencies are required to implement backpressure for event stream management. The skill utilizes Expanso's built-in rate limiting resources to provide deterministic flow control for your data streaming pipelines.