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1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">可观测</span><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Metrics</span><meta itemprop="position" content="2"></li></ul></nav><span class="theme-doc-version-badge badge badge--secondary">版本：5.0</span><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">本页总览</button></div><div class="theme-doc-markdown markdown"><h1>Metrics</h1><p>RocketMQ 以 Prometheus 格式公开以下指标。您可以使用这些指标监视您的集群。</p><ul><li>服务端 Metrics 指标</li><li>生产者 Metrics 指标</li><li>消费者 Metrics 指标</li></ul><blockquote><p>版本支持：以下指标 Metrics 是从 5.1.0 版本开始支持。</p></blockquote><h2 class="anchor anchorWithStickyNavbar_LWe7" id="metrics-指标详情">Metrics 指标详情<a href="#metrics-指标详情" class="hash-link" aria-label="Metrics 指标详情的直接链接" title="Metrics 指标详情的直接链接"></a></h2><h3 class="anchor anchorWithStickyNavbar_LWe7" id="metric-types">Metric types<a href="#metric-types" class="hash-link" aria-label="Metric types的直接链接" title="Metric types的直接链接"></a></h3><p>消息队列 RocketMQ 版定义的 Metrics 完全兼容开源 Prometheus 的标准，提供的 Metrics 的类型为 Counter、Gauge 和 Histogram。更多信息，请参见 <a href="https://prometheus.io/docs/concepts/metric_types/" target="_blank" rel="noopener noreferrer">METRIC TYPES</a>。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="服务端-metrics-指标">服务端 Metrics 指标<a href="#服务端-metrics-指标" class="hash-link" aria-label="服务端 Metrics 指标的直接链接" title="服务端 Metrics 指标的直接链接"></a></h3><p>消息队列 RocketMQ 版服务端相关 Metrics 指标中 Label 的说明如下：</p><ul><li>cluster: RocketMQ 集群名称。</li><li>node_type: 服务节点类型。枚举值包含 proxy、broker、nameserver。</li><li>node_id: 服务节点 ID。</li><li>topic: 消息队列 RocketMQ 的主题。</li><li>message_type: 消息类型。有以下类型:<br>Normal:普通消息;<br>FIFO:顺序消息;<br>Transaction:事务消息;<br>Delay:定时/延时消息.</li><li>consumer_group: 消费者 ID。</li></ul><table><thead><tr><th>Metrics 类型</th><th>Metrics name</th><th>单位</th><th>指标说明</th><th>Label</th></tr></thead><tbody><tr><td>counter</td><td>rocketmq_messages_in_total</td><td>count</td><td>消息生产数量。</td><td>cluster,node_type,node_id,topic,message_type</td></tr><tr><td>counter</td><td>rocketmq_messages_out_total</td><td>count</td><td>消息消费数量。</td><td>cluster,node_type,node_id,topic, consumer_group</td></tr><tr><td>counter</td><td>rocketmq_throughput_in_total</td><td>byte</td><td>消息生产流入服务端的吞吐量。</td><td>cluster,node_type,node_id,topic,message_type</td></tr><tr><td>counter</td><td>rocketmq_throughput_out_total</td><td>byte</td><td>消息消费从服务端流出的吞吐量。</td><td>cluster,node_type,node_id,topic, consumer_group</td></tr><tr><td>histogram</td><td>rocketmq_message_size</td><td>byte</td><td>消息大小的分布情况，发送成功时统计。分布区间如下：<br>le_1_kb: ≤ 1 KB<br> le_4_kb: ≤ 4 KB<br>le_512_kb: ≤ 512 KB<br>le_1_mb: ≤ 1 MB<br>le_2_mb: ≤ 2 MB<br>le_4_mb: ≤ 4 MB<br>le_overflow: > 4 MB</td><td>cluster,node_type,node_id,topic,message_type</td></tr><tr><td>gauge</td><td>rocketmq_consumer_ready_messages</td><td>count</td><td>已就绪消息量。</td><td>cluster,node_type,node_id,topic, consumer_group</td></tr><tr><td>gauge</td><td>rocketmq_consumer_inflight_messages</td><td>count</td><td>处理中消息量。</td><td>cluster,node_type,node_id,topic, consumer_group</td></tr><tr><td>gauge</td><td>rocketmq_consumer_queueing_latency</td><td>millisecond</td><td>已就绪消息排队延迟时间。</td><td>cluster,node_type,node_id,topic, consumer_group</td></tr><tr><td>gauge</td><td>rocketmq_consumer_lag_latency</td><td>millisecond</td><td>消费处理延迟时间。</td><td>cluster,node_type,node_id,topic, consumer_group</td></tr><tr><td>counter</td><td>rocketmq_send_to_dlq_messages_total</td><td>count</td><td>转为死信状态的消息量。（变成死信状态指的是消息达到最大重投次数后不再投递）</td><td>cluster,node_type,node_id,topic, consumer_group</td></tr><tr><td>histogram</td><td>rocketmq_rpc_latency</td><td>millisecond</td><td>rpc 调用耗时：<br>le_1_ms<br>le_3_ms<br>le_5_ms<br>le_10_ms<br>le_100_ms<br>le_1_s<br>le_3_s<br>le_overflow</td><td>cluster,node_typ,node_id,protocol_type,request_code,response_code</td></tr><tr><td>gauge</td><td>rocketmq_storage_message_reserve_time</td><td>millisecond</td><td>储存层消息保存时间（broker 硬盘上最早一条消息储存时间和当前时间作差）</td><td>cluster,node_type,node_id</td></tr><tr><td>gauge</td><td>rocketmq_storage_dispatch_behind_bytes</td><td>byte</td><td>dispatch 落后大小</td><td>cluster,node_type,node_id</td></tr><tr><td>gauge</td><td>rocketmq_storage_flush_behind_bytes</td><td>byte</td><td>刷盘落后大小。</td><td>cluster,node_type,node_id</td></tr><tr><td>gauge</td><td>rocketmq_thread_pool_wartermark</td><td>count</td><td>线程池排队数</td><td>cluster,node_type,node_id,name</td></tr></tbody></table><h3 class="anchor anchorWithStickyNavbar_LWe7" id="生产者-metrics-指标">生产者 Metrics 指标<a href="#生产者-metrics-指标" class="hash-link" aria-label="生产者 Metrics 指标的直接链接" title="生产者 Metrics 指标的直接链接"></a></h3><p>消息队列 RocketMQ 版生产者相关 Metrics 指标中 Label 的说明如下：</p><ul><li>cluster: RocketMQ 集群名称。</li><li>node_type: 服务节点类型。枚举值包含 proxy、broker、nameserver。</li><li>node_id: 服务节点 ID。</li><li>topic: 消息队列 RocketMQ 的主题。</li><li>message_type: 消息类型。有以下类型:<br>Normal:普通消息;<br>FIFO:顺序消息;<br>Transaction:事务消息;<br>Delay:定时/延时消息.</li><li>client_id: 客户端 ID。</li><li>invocation_status: 消息发送接口调用结果，枚举值包含 success 和 failure。</li></ul><table><thead><tr><th>Metrics 类型</th><th>Metrics name</th><th>单位</th><th>指标说明</th><th>Label</th></tr></thead><tbody><tr><td>Histogram</td><td>rocketmq_send_cost_time</td><td>millisecond</td><td>调用消息发送接口成功的耗时分布情况。分布区间如下：: <br>le_1_ms <br>le_5_ms<br>le_10_ms<br>le_20_ms <br>le_50_ms <br>le_200_ms<br>le_500_ms <br>le_overflow</td><td>topic,client_id,invocation_status</td></tr></tbody></table><h3 class="anchor anchorWithStickyNavbar_LWe7" id="消费者-metrics-指标">消费者 Metrics 指标<a href="#消费者-metrics-指标" class="hash-link" aria-label="消费者 Metrics 指标的直接链接" title="消费者 Metrics 指标的直接链接"></a></h3><p>消息队列 RocketMQ 版消费者相关 Metrics 指标中 Label 的说明如下：</p><ul><li>topic: 消息队列 RocketMQ 的主题。</li><li>consumer_group: 消费者分组 ID。</li><li>client_id: 客户端 ID。</li><li>invocation_status: 消费结果, 枚举值包含 success 和 failure。</li></ul><table><thead><tr><th>Metrics 类型</th><th>Metrics name</th><th>单位</th><th>指标说明</th><th>Label</th></tr></thead><tbody><tr><td>Histogram</td><td>rocketmq_process_time</td><td>millisecond</td><td>PushConsumer 的消息处理耗时分布情况.分布区间如下: <br>le_1_ms <br>le_5_ms <br>le_10_ms<br>le_100_ms <br>le_10000_ms<br>le_60000_ms <br>le_overflow</td><td>topic,consumer_group,client_id,invocation_status</td></tr><tr><td>gauge</td><td>rocketmq_consumer_cached_messages</td><td>message</td><td>PushConsumer 本地缓冲队列中的消息条数。</td><td>topic,consumer_group,client_id</td></tr><tr><td>gauge</td><td>rocketmq_consumer_cached_bytes</td><td>byte</td><td>PushConsumer 本地缓冲队列中消息的总大小。</td><td>topic,consumer_group,client_id</td></tr><tr><td>Histogram</td><td>rocketmq_await_time</td><td>millisecond</td><td>消息在 PushConsumer 本地缓冲队列中的排队时间的分布情况:<br>le_1_ms<br> le_5_ms<br>le_20_ms<br>le_100_ms <br>le_1000_ms<br> le_5000_ms <br>le_10000_ms<br>le_overflow</td><td>topic,consumer_group,client_id</td></tr></tbody></table><h2 class="anchor anchorWithStickyNavbar_LWe7" id="指标业务场景">指标业务场景<a href="#指标业务场景" class="hash-link" aria-label="指标业务场景的直接链接" title="指标业务场景的直接链接"></a></h2><p>消息队列 RocketMQ 版主要基于以下业务场景定义 Metrics 指标.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="消息堆积场景">消息堆积场景<a href="#消息堆积场景" class="hash-link" aria-label="消息堆积场景的直接链接" title="消息堆积场景的直接链接"></a></h3><p><img loading="lazy" alt="RocketMQ 队列消息状态" src="/zh/assets/images/message-accumulation-4edf6e541f775da11672dac6d795305f.png" width="1213" height="635" class="img_ev3q"><br>上图表示指定主题的某一队列中各消息的状态，消息队列 RocketMQ 版将处于不同处理阶段的消息数量和耗时进行统计，这些指标可直接反映队列中消息的处理速率和堆积情况，通过观察这些指标可初步判断业务的消费是否异常。具体的指标含义和计算公式如下：</p><table><thead><tr><th>名称</th><th>描述</th><th>计算公式</th></tr></thead><tbody><tr><td>处理中的消息（inflight messages）</td><td>在消费者客户端正在处理，但客户端还未返回消费结果的消息。</td><td>最晚一条拉取消息的位点－最晚一条提交消息的位点</td></tr><tr><td>已就绪消息（ready messages）</td><td>消息在消息队列 RocketMQ 版服务端已就绪，对消费者可见可被消费的消息。</td><td>最大消费位点－最晚一条拉取消息的位点</td></tr><tr><td>已就绪消息的就绪时间（ready time）</td><td>普通消息、顺序消息：消息存储到服务端的时间。 <br> 定时/延时消息：消息定时或延时结束的时间。 <br> 事务消息：事务提交的时间。</td><td>--</td></tr><tr><td>已就绪消息的排队时间（ready message queue time）</td><td>该时间反应消费者拉取消息的及时性。</td><td>当前时间－最早一条就绪消息的就绪时间</td></tr><tr><td>消费处理滞后时间（consumer lag time）</td><td>该时间反应消费者完成消息处理的及时性。</td><td>当前时间－最早一条未提交消息的就绪时间</td></tr></tbody></table><h3 class="anchor anchorWithStickyNavbar_LWe7" id="pushconsumer-消费场景">PushConsumer 消费场景<a href="#pushconsumer-消费场景" class="hash-link" aria-label="PushConsumer 消费场景的直接链接" title="PushConsumer 消费场景的直接链接"></a></h3><p>在 PushConsumer 类型中，消息的实时处理能力是基于 SDK 内部的典型 Reactor 线程模型实现的。如下图所示，SDK 内置了一个长轮询线程，先将消息异步拉取到 SDK 内置的缓存队列中，再分别提交到消费线程中，触发监听器执行本地消费逻辑。<br><img loading="lazy" alt="PushConsumer client" src="/zh/assets/images/pushconsumer-consumption-4910ceb35c5f21c6f74aa07fb3f79134.png" width="1392" height="691" class="img_ev3q"><br>在 PushConsumer 消费场景下，本地缓冲队列相关指标如下：</p><ul><li>本地缓冲队列中的消息量：本地缓冲队列中的消息总条数。</li><li>本地缓冲队列中的消息大小：本地缓冲队列中所有消息大小的总和。</li><li>消息等待处理时间：消息暂存在本地缓冲队列中的时间。</li></ul><h2 class="anchor anchorWithStickyNavbar_LWe7" id="metrics-指标获取方式">Metrics 指标获取方式<a href="#metrics-指标获取方式" class="hash-link" aria-label="Metrics 指标获取方式的直接链接" title="Metrics 指标获取方式的直接链接"></a></h2><p>目前支持 gRPC OTLP 和 Prometheus 两种 exporter</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="grpc-otlp-exporter">gRPC OTLP exporter<a href="#grpc-otlp-exporter" class="hash-link" aria-label="gRPC OTLP exporter的直接链接" title="gRPC OTLP exporter的直接链接"></a></h3><p>gRPC OTLP exporter 会周期性地向指定的 OpenTelemetry Collector 上报 metrics</p><p>前置条件：需要部署支持 <a href="https://github.com/open-telemetry/oteps/blob/main/text/0035-opentelemetry-protocol.md" target="_blank" rel="noopener noreferrer">GRPC OpenTelemetry Protocol</a> 的 OpenTelemetry Collector</p><p>开启 Broker metrics 的 gRPC OTLP exporter 需要进行以下配置：</p><ol><li>将 <code>metricsExporterType</code> 设置为 <code>OTLP_GRPC</code></li><li>将 <code>metricsGrpcExporterTarget</code> 设置为 OpenTelemetry Collector 提供的 endpoint</li></ol><p>可选配置：</p><ol><li><code>metricsGrpcExporterHeader</code>：为 gRPC OTLP exporter 附加请求头，格式为 key1:value1,key2:value2</li><li><code>metricGrpcExporterTimeOutInMills</code>：设置 gRPC OTLP exporter 的请求超时时间</li><li><code>metricGrpcExporterIntervalInMills</code>：设置 gRPC OTLP exporter 的上报间隔</li></ol><h3 class="anchor anchorWithStickyNavbar_LWe7" id="prometheus-exporter">Prometheus exporter<a href="#prometheus-exporter" class="hash-link" aria-label="Prometheus exporter的直接链接" title="Prometheus exporter的直接链接"></a></h3><p>Prometheus exporter 仅支持 Pull 模式和 Cumulative 聚合，详见 <a href="https://opentelemetry.io/docs/reference/specification/metrics/sdk_exporters/prometheus/" target="_blank" rel="noopener noreferrer">OpenTelemetry Metrics Exporter - Prometheus</a></p><p>开启 Broker metrics 的 Prometheus exporter 需要进行以下配置：</p><ol><li>将 <code>metricsExporterType</code> 设置为 <code>PROM</code></li></ol><p>访问 <code>http://<broker-ip>:5557/metrics</code> 来查看 metrics，在 Prometheus 中配置服务发现或手动配置拉取任务即可采集 metrics</p><p>可选配置：</p><ol><li><code>metricsPromExporterPort</code>：Broker 暴露 metrics 服务的端口号，默认为 <code>5557</code></li><li><code>metricsPromExporterHost</code>：暴露 metrics 服务的主机名，默认为 Broker 向 NameServer 注册的地址，即 <code>brokerIP1</code></li></ol></div><footer class="theme-doc-footer 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