
from data-engineering-skills12
Expert guidance for deploying, configuring, and developing with Apache Iggy — a Rust-native high-performance message streaming platform, including Docker, Pytho
This skill encapsulates operational and developer knowledge for Apache Iggy: how to deploy it in Docker, tune performance, use the python apache-iggy SDK, and integrate Iggy via MCP for LLM workflows. It includes practical gotchas and recommended configuration for reliable production usage.
Use when designing low-latency/high-throughput event pipelines, evaluating Kafka alternatives, deploying Iggy in containers, or integrating streaming data with LLMs via MCP. Useful for SREs, platform engineers, and AI engineers building real-time data tools.
Best consumed by agents that assist with infra setup and code generation (e.g., Copilot/Claude Code style agents) or platform-focused assistants that can produce Docker/compose files and SDK snippets.
Static-only audit (no bundled scripts). The skill is a concise Apache Iggy reference card covering current release info, deployment modes, transport options, Docker env vars, and io_uring gotchas. Well-organized quick-reference but lacks actionable automation — it's a knowledge base, not an executable skill. No security concerns whatsoever since there's no executable code.
Pure reference skill with no executable content. Security score is max because there's nothing to exploit. Architecture is minimal — single-file, no scripts/ or references/ directories. Useful as a quick-reference cheat sheet for Iggy but limited audience and no automation value.