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Apache Kafka Consumer Lag Runbook

Diagnostiziert den Lag von Kafka-Consumer-Gruppen mithilfe der Kafka AdminClient API und JMX-Metriken, die über die Confluent Metrics API bereitgestellt werden. Identifiziert langsame Consumer, Topic-Partition-Hotspots und Broker-Rebalance-Stürme, die zum Lag-Wachstum beitragen. Bietet ein schrittweises Runbook zur Optimierung von fetch.min.bytes, max.poll.records und der Partitionsanzahl.

Was ist Apache Kafka Consumer Lag Runbook?

Diese Fähigkeit befähigt KI-Agenten (wie Claude Code, Cursor oder Codex), den Consumer Lag in Apache Kafka-Umgebungen zu diagnostizieren und zu beheben. Sie integriert sich mit der Kafka AdminClient API und der Confluent Metrics API, um JMX-Metriken zu sammeln und zu analysieren. Der Agent kann so langsame Consumer, Partition-Hotspots und Rebalance-Stürme identifizieren, die die Ursache für wachsenden Lag sind. Das integrierte Runbook bietet eine schrittweise Anleitung zur Optimierung kritischer Parameter wie fetch.min.bytes, max.poll.records und der Partitionsanzahl, um die Verarbeitungsleistung des Consumers zu verbessern. Die Fähigkeit ist plattformunabhängig und kann in Docker-Containern oder nativen Java-Umgebungen ausgeführt werden, unterstützt durch Unit- und Integrationstests.

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Dokumentation

Was macht Apache Kafka Consumer Lag Runbook?

Diagnostiziert den Lag von Kafka-Consumer-Gruppen mithilfe der Kafka AdminClient API und JMX-Metriken, die über die Confluent Metrics API bereitgestellt werden. Identifiziert langsame Consumer, Topic-Partition-Hotspots und Broker-Rebalance-Stürme, die zum Lag-Wachstum beitragen. Bietet ein schrittweises Runbook zur Optimierung von fetch.min.bytes, max.poll.records und der Partitionsanzahl.

Voraussetzungen

Java

Installation

Verwenden Sie den für Ihre Umgebung passenden Upstream-Installations- oder Setup-Pfad:

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

Anforderungen und Hinweise von Upstream:

  • Verwendung des Docker-Images:
  • Siehe docker/README.md für detaillierte Informationen.

Grundlegende Nutzung oder Einstiegshinweise:

Dokumentation

Quelle

Individual skills in this repo

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

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