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Processeur de flux Apache Kafka

Skill pour l'agent lui permettant de configurer et d'utiliser Apache Kafka, un système de streaming distribué pour le traitement de flux de données en temps réel.

Qu'est-ce que Processeur de flux Apache Kafka ?

Ce skill permet à l'agent de comprendre et d'utiliser Apache Kafka, un système de streaming distribué qui permet de publier, souscrire, stocker et traiter des flux de données en temps réel. Il est conçu pour les développeurs qui souhaitent intégrer Kafka dans leurs workflows logiciels, que ce soit pour l'ingestion de données, le traitement de flux ou la construction d'applications réactives. Le skill couvre les prérequis techniques (Java), les méthodes d'installation via Docker et les étapes de construction de projets avec Gradle, y compris les tests unitaires et d'intégration avec support des tests flaky. Il s'appuie sur la documentation officielle d'Apache Kafka et sur le référentiel Agent Skill Exchange, offrant ainsi une base solide pour le développement orienté événements.

Compatible avec~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/apache-kafka-stream-processor
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Documentation

Que fait Processeur de flux Apache Kafka ?

Prérequis

Java

Installation

Utilisez la méthode d'installation ou de configuration en amont qui correspond à votre environnement :

  • docker run -p 9092:9092 apache/kafka:latest

Exigences et mises en garde de la source amont :

  • Utilisation de l'image Docker :
  • Voir docker/README.md pour des informations détaillées.

Notes d'utilisation de base ou de démarrage :

Documentation

Source

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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Add executable smoke tests for shell scripts and CLIs before ref

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Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

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Add persistent project memory and hook-driven synthesis with Cla

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Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

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