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Apache Kafka コンシューマーラグ ランブック

Kafka AdminClient API と Confluent Metrics API 経由で公開された JMX メトリクスを使用して、Kafka コンシューマーグループのラグを診断します。遅いコンシューマー、トピックパーティションのホットスポット、ラグの増大に寄与するブローカーリバランスストームを特定します。fetch.min.bytes、max.poll.records、パーティション数を調整するためのステップバイステップのランブックを提供します。

Apache Kafka コンシューマーラグ ランブック とは？

このスキルは、Kafka コンシューマーグループのラグを診断および解決するための包括的なランブックを提供します。Kafka AdminClient API と、Confluent Metrics API を介して公開される JMX メトリクスを活用することで、遅いコンシューマー、トピックパーティションのホットスポット、ラグの増大を引き起こすブローカーリバランスストームを特定します。開発者やプラットフォームエンジニア向けに設計されており、fetch.min.bytes、max.poll.records、パーティション数の微調整を段階的にガイドします。このスキルは、Apache Kafka エコシステム（Java ベースの環境、Docker コンテナ、Confluent プラットフォーム）で動作し、Kafka の公式ドキュメントを参照します。ソースコードは Apache Kafka リポジトリから抽出されており、JAR ビルド、統合テスト（./gradlew test -Pkafka.test.run.flaky=true）、Docker セットアップ（docker run -p 9092:9092 apache/kafka:latest）をサポートします。Agent Skill Exchange でも利用可能です。

対応~Claude Code~Codex CLI✓Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/apache-kafka-consumer-lag-runbook
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ドキュメント

Apache Kafka コンシューマーラグ ランブック は何をしますか？

Kafka AdminClient API と Confluent Metrics API 経由で公開された JMX メトリクスを使用して、Kafka コンシューマーグループのラグを診断します。遅いコンシューマー、トピックパーティションのホットスポット、ラグの増大に寄与するブローカーリバランスストームを特定します。fetch.min.bytes、max.poll.records、パーティション数を調整するためのステップバイステップのランブックを提供します。

前提条件

Java

インストール

環境に一致するアップストリームのインストールまたはセットアップパスを使用してください：

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

アップストリームからの要件と注意事項：

  • Docker イメージを使用する場合：
  • 詳細については docker/README.md を参照してください。

基本的な使用方法または開始手順：

ドキュメント

ソース

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