Add blog: Flink monitoring (#784)
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+---
+title: "Monitoring Flink with SkyWalking"
+author: "YiMing Shao"
+date: 2025-04-25
+description: "SkyWalking 10.3 introduces a new Flink monitoring dashboard, and this article will demonstrate the usage of this monitoring dashboard."
+tags:
+- Flink
+---
+
+# Background
+[Apache Flink](https://flink.apache.org/) is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.
+
+[Apache SkyWalking](https://skywalking.apache.org/) is an application performance monitor tool for distributed systems, especially designed for microservices, cloud native and container-based (Kubernetes) architectures.
+
+[OpenTelemetry](https://opentelemetry.io/) is a collection of APIs, SDKs, and tools. Use it to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) to help you analyze your software’s performance and behavior.
+
+Since `SkyWalking` 10.3, a new out-of-the-box feature has been introduced that enables Flink monitoring data to be visualized on the SkyWalking UI via the OpenTelemetry Collector, which gathers metrics from Flink endpoints.
+
+# Development
+
+## Preparation
+1. [SkyWalking OAP,v10.3 +](https://github.com/apache/skywalking)
+2. [Flink v2.0-preview1 +](https://github.com/apache/flink)
+3. [OpenTelemetry-collector v0.87+](https://github.com/open-telemetry/opentelemetry-collector-contrib)
+
+## Process
+ 1. Set up `SkyWalking` oap and UI.
+ 2. Set up the `Flink` cluster By configuring `jobmanager` and `taskmanager` to expose prometheus http endpoints.
+ 3. Set up `OpenTelemetry-collector`.
+ 4. Run your job.
+
+## Data flow
+
+
+## Configuration
+
+### docker-compose
+````
+version: "3"
+
+services:
+ oap:
+ extends:
+ file: ../../script/docker-compose/base-compose.yml
+ service: oap
+ ports:
+ - "12800:12800"
+ networks:
+ - e2e
+
+ banyandb:
+ extends:
+ file: ../../script/docker-compose/base-compose.yml
+ service: banyandb
+ ports:
+ - 17912
+
+ jobmanager:
+ image: flink:2.0-preview1
+ environment:
+ - |
+ FLINK_PROPERTIES=
+ jobmanager.rpc.address: jobmanager
+ metrics.reporter.prom.factory.class: org.apache.flink.metrics.prometheus.PrometheusReporterFactory
+ metrics.reporter.prom.port: 9260
+ ports:
+ - "8081:8081"
+ - "9260:9260"
+ command: jobmanager
+ healthcheck:
+ test: ["CMD", "curl", "-f", "http://localhost:8081"]
+ interval: 30s
+ timeout: 10s
+ retries: 3
+ networks:
+ - e2e
+
+ taskmanager:
+ image: flink:2.0-preview1
+ environment:
+ - |
+ FLINK_PROPERTIES=
+ jobmanager.rpc.address: jobmanager
+ metrics.reporter.prom.factory.class: org.apache.flink.metrics.prometheus.PrometheusReporterFactory
+ metrics.reporter.prom.port: 9261
+ depends_on:
+ jobmanager:
+ condition: service_healthy
+ ports:
+ - "9261:9261"
+ command: taskmanager
+ healthcheck:
+ test: ["CMD", "curl", "-f", "http://localhost:9261/metrics"]
+ interval: 30s
+ timeout: 10s
+ retries: 3
+ networks:
+ - e2e
+
+ executeJob:
+ image: flink:2.0-preview1
+ depends_on:
+ taskmanager:
+ condition: service_healthy
+ command: >
+ bash -c "
+ ./bin/flink run -m jobmanager:8081 examples/streaming/WindowJoin.jar"
+ networks:
+ - e2e
+
+ otel-collector:
+ image: otel/opentelemetry-collector:${OTEL_COLLECTOR_VERSION}
+ networks:
+ - e2e
+ command: [ "--config=/etc/otel-collector-config.yaml" ]
+ volumes:
+ - ./otel-collector-config.yaml:/etc/otel-collector-config.yaml
+ expose:
+ - 55678
+ depends_on:
+ oap:
+ condition: service_healthy
+
+networks:
+ e2e:
+````
+
+If you plan to expose metrics data using the pushGateway pattern,
+please refer to the [documentation](https://nightlies.apache.org/flink/flink-docs-release-2.0-preview1/docs/deployment/metric_reporters/#prometheuspushgateway).
+
+### OpenTelemetry-collector
+````
+receivers:
+ prometheus:
+ config:
+ scrape_configs:
+ - job_name: "flink-jobManager-monitoring"
+ scrape_interval: 30s
+ static_configs:
+ - targets: ['jobmanager:9260']
+ labels:
+ cluster: flink-cluster
+ relabel_configs:
+ - source_labels: [ __address__ ]
+ target_label: jobManager_node
+ replacement: $$1
+ metric_relabel_configs:
+ - source_labels: [ job_name ]
+ action: replace
+ target_label: flink_job_name
+ replacement: $$1
+ - source_labels: [ ]
+ target_label: job_name
+ replacement: flink-jobManager-monitoring
+
+ - job_name: "flink-taskManager-monitoring"
+ scrape_interval: 30s
+ static_configs:
+ - targets: [ "taskmanager:9261" ]
+ labels:
+ cluster: flink-cluster
+ relabel_configs:
+ - source_labels: [ __address__ ]
+ regex: (.+)
+ target_label: taskManager_node
+ replacement: $$1
+ metric_relabel_configs:
+ - source_labels: [ job_name ]
+ action: replace
+ target_label: flink_job_name
+ replacement: $$1
+ - source_labels: [ ]
+ target_label: job_name
+ replacement: flink-taskManager-monitoring
+
+exporters:
+ otlp:
+ endpoint: oap:11800
+ tls:
+ insecure: true
+
+processors:
+ batch:
+service:
+ pipelines:
+ metrics:
+ receivers:
+ - prometheus
+ processors:
+ - batch
+ exporters:
+ - otlp
+````
+
+Warning:
+Please do not edit the value of the `job_name` configuration, otherwise `SkyWalking` will not handle these data.
+`oap` means the address of your `SkyWalking oap` address,please replace it accordingly.
+Since the original `Flink metrics` contain the `job_name` labels, and SkyWalking relies on the `job_name` label to handle OpenTelemetry data,
+to avoid conflicts, we use `metric_relabel_configs` to rename the original `job_name` label to `flink_job_name`.
+
+# Metrics Definition
+
+Monitoring metrics involve in `Cluster Metrics`, `TaskManager Metrics`, and `Job Metrics`.
+
+## Cluster Metrics
+
+
+
+
+`Cluster Metrics` mainly focuses on statistics from the perspective of the entire cluster, as well as displaying JVM-related metrics of the JobManager, such as:
+
+- `Running Jobs`：The number of currently running jobs.
+- `TaskManagers`：The number of TaskManagers.
+- `Task Managers Slots Total`：The total number of TaskManager slots.
+- `Task Managers Slots Available`：The number of available TaskManager slots.
+- `JVM CPU Load`：The CPU load of the JobManager's JVM.
+
+## TaskManager Metrics
+
+
+
+
+
+`TaskManager Metrics` mainly focuses on statistics from the perspective of individual TaskManager nodes, such as:
+
+- `JVM Memory Heap Used`：The amount of JVM heap memory used on the TaskManager node.
+- `JVM Memory Heap Available`：The amount of JVM heap memory available on the TaskManager node.
+- `NumRecordsIn`：The number of records received per minute by the TaskManager.
+- `NumBytesInPerSecond`：The number of bytes received per second by the TaskManager.
+- `IsBackPressured`：Indicates whether the TaskManager node is under backpressure.
+- `IdleTimeMsPerSecond`：The idle time per second of the TaskManager node.
+
+## Job Metrics
+
+
+
+
+`Job Metrics`mainly focuses on statistics from the perspective of running jobs, such as:
+
+- `Job RunningTime`：The duration for which the job has been running.
+- `Job Restart Number`：The number of times the job has been restarted.
+- `Checkpoints Failed`：The number of failed checkpoints.
+- `NumBytesInPerSecond`：The number of bytes received per second by the job.
+
+You can find explanations for each metric in the tip of the corresponding chart.
+
+
+# References
+
+- [Flink Prometheus](https://nightlies.apache.org/flink/flink-docs-release-2.0-preview1/docs/deployment/metric_reporters/#prometheus)
+- [SkyWalking Flink Monitoring](https://skywalking.apache.org/docs/main/next/en/setup/backend/backend-flink-monitoring/)
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1. [SkyWalking OAP, v10.0+](https://github.com/apache/skywalking).
2. [ActiveMQ v6.0.X+](https://activemq.apache.org/components/classic/download/).
3. [JMX Exporter v0.20.0](https://github.com/prometheus/jmx_exporter/releases). If using docker, refer [bitnami/jmx-exporter](https://github.com/bitnami/containers/tree/main/bitnami/jmx-exporter).
-4. [OpenTelmetry-Collector v0.92.0](https://github.com/open-telemetry/opentelemetry-collector-contrib).
+4. [OpenTelemetry-Collector v0.92.0](https://github.com/open-telemetry/opentelemetry-collector-contrib).
### Preparation
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+---
+title: "使用 SkyWalking 监控 Flink"
+author: "邵一鸣"
+date: 2025-04-25
+description: "SkyWalking 10.3 引入了新的 Flink 监控面板,本文将演示该监控面板的使用。"
+tags:
+- Flink
+---
+
+# 背景介绍
+ Apache Flink 是一个框架和分布式处理引擎，用于在无边界和有边界数据流上进行有状态的计算。Flink 能在所有常见集群环境中运行，并能以内存速度和任意规模进行计算。
+从SkyWalking OAP 10.3 版本开始，新增了对来自Flink的指标数据监控面板，本文将展示并介绍如何使用 SkyWalking来监控Flink。
+
+# 部署
+
+## 准备
+
+1. [SkyWalking oap服务,v10.3 +](https://github.com/apache/skywalking)
+2. [Flink v2.0-preview1 +](https://github.com/apache/flink)
+3. [OpenTelemetry-collector v0.87+](https://github.com/open-telemetry/opentelemetry-collector-contrib)
+
+## 启动流程
+1. 启动 `jobmanager` 和 `taskmanager`
+2. 启动 `skywalking oap` 和 `ui`
+3. 启动 `opentelmetry-collector`
+4. 启动job
+
+## DataFlow:
+
+
+## 配置
+### docker-compose
+````
+version: "3"
+
+services:
+ oap:
+ extends:
+ file: ../../script/docker-compose/base-compose.yml
+ service: oap
+ ports:
+ - "12800:12800"
+ networks:
+ - e2e
+
+ banyandb:
+ extends:
+ file: ../../script/docker-compose/base-compose.yml
+ service: banyandb
+ ports:
+ - 17912
+
+ jobmanager:
+ image: flink:2.0-preview1
+ environment:
+ - |
+ FLINK_PROPERTIES=
+ jobmanager.rpc.address: jobmanager
+ metrics.reporter.prom.factory.class: org.apache.flink.metrics.prometheus.PrometheusReporterFactory
+ metrics.reporter.prom.port: 9260
+ ports:
+ - "8081:8081"
+ - "9260:9260"
+ command: jobmanager
+ healthcheck:
+ test: ["CMD", "curl", "-f", "http://localhost:8081"]
+ interval: 30s
+ timeout: 10s
+ retries: 3
+ networks:
+ - e2e
+
+ taskmanager:
+ image: flink:2.0-preview1
+ environment:
+ - |
+ FLINK_PROPERTIES=
+ jobmanager.rpc.address: jobmanager
+ metrics.reporter.prom.factory.class: org.apache.flink.metrics.prometheus.PrometheusReporterFactory
+ metrics.reporter.prom.port: 9261
+ depends_on:
+ jobmanager:
+ condition: service_healthy
+ ports:
+ - "9261:9261"
+ command: taskmanager
+ healthcheck:
+ test: ["CMD", "curl", "-f", "http://localhost:9261/metrics"]
+ interval: 30s
+ timeout: 10s
+ retries: 3
+ networks:
+ - e2e
+
+ executeJob:
+ image: flink:2.0-preview1
+ depends_on:
+ taskmanager:
+ condition: service_healthy
+ command: >
+ bash -c "
+ ./bin/flink run -m jobmanager:8081 examples/streaming/WindowJoin.jar"
+ networks:
+ - e2e
+
+ otel-collector:
+ image: otel/opentelemetry-collector:${OTEL_COLLECTOR_VERSION}
+ networks:
+ - e2e
+ command: [ "--config=/etc/otel-collector-config.yaml" ]
+ volumes:
+ - ./otel-collector-config.yaml:/etc/otel-collector-config.yaml
+ expose:
+ - 55678
+ depends_on:
+ oap:
+ condition: service_healthy
+
+networks:
+ e2e:
+````
+如果是使用`pushGateWay`模式来暴露metrics数据请[参考](https://nightlies.apache.org/flink/flink-docs-release-2.0-preview1/docs/deployment/metric_reporters/#prometheuspushgateway)。
+
+
+### OpenTelemetry-collector
+````
+receivers:
+ prometheus:
+ config:
+ scrape_configs:
+ - job_name: "flink-jobManager-monitoring"
+ scrape_interval: 30s
+ static_configs:
+ - targets: ['jobmanager:9260']
+ labels:
+ cluster: flink-cluster
+ relabel_configs:
+ - source_labels: [ __address__ ]
+ target_label: jobManager_node
+ replacement: $$1
+ metric_relabel_configs:
+ - source_labels: [ job_name ]
+ action: replace
+ target_label: flink_job_name
+ replacement: $$1
+ - source_labels: [ ]
+ target_label: job_name
+ replacement: flink-jobManager-monitoring
+
+ - job_name: "flink-taskManager-monitoring"
+ scrape_interval: 30s
+ static_configs:
+ - targets: [ "taskmanager:9261" ]
+ labels:
+ cluster: flink-cluster
+ relabel_configs:
+ - source_labels: [ __address__ ]
+ regex: (.+)
+ target_label: taskManager_node
+ replacement: $$1
+ metric_relabel_configs:
+ - source_labels: [ job_name ]
+ action: replace
+ target_label: flink_job_name
+ replacement: $$1
+ - source_labels: [ ]
+ target_label: job_name
+ replacement: flink-taskManager-monitoring
+
+exporters:
+ otlp:
+ endpoint: oap:11800
+ tls:
+ insecure: true
+
+processors:
+ batch:
+service:
+ pipelines:
+ metrics:
+ receivers:
+ - prometheus
+ processors:
+ - batch
+ exporters:
+ - otlp
+
+````
+注意:
+`job_name`的值请不要修改,否则 skyWalking 不会处理这部分数据。
+`oap` 为 `skywalking oap` 地址,请自行替换。
+因为原始`flink`数据中含有`job_name`标签，而skyWalking又根据`job_name`标签来处理对应OTEL任务的数据，
+为了避免冲突，使用`metric_relabel_configs`替换原始数据中`job_name`的标签为`flink_job_name`。
+
+
+# 监控指标
+
+指标分为三个维度,cluster,taskManager,job
+
+## Cluster Metrics
+
+
+
+
+
+`Cluster Metrics`主要是站在集群的角度统计以及jobManager的jvm相关指标展示,比如
+
+- `Running Jobs`：正在运行的任务数量
+- `TaskManagers`：taskManager数量
+- `Task Managers Slots Total`：taskManager slot数量
+- `Task Managers Slots Available`：taskManager可用slot数量
+- `JVM CPU Load`：jobManager的jvm占用cpu的负载
+
+
+## TaskManager Metrics
+
+
+
+
+
+`TaskManager Metrics`主要是站在taskManager节点的角度来统计展示,比如
+
+- `JVM Memory Heap Used`：taskManager节点JVM已用内存大小。
+- `JVM Memory Heap Available`：taskManager节点JVM可用内存大小。
+- `NumRecordsIn`：taskManager每分钟接受的数据数量。
+- `NumBytesInPerSecond`：taskManager每秒接受的Bytes数量。
+- `IsBackPressured`：该taskManager节点是否处在背压。
+- `IdleTimeMsPerSecond`：该taskManager节点每秒的闲置时长。
+
+## Job Metrics
+
+
+
+
+`Job Metrics`主要是站在运行任务的角度来统计展示,比如
+
+- `Job RunningTime`：该任务运行的时长。
+- `Job Restart Number`：该任务重启次数。
+- `Checkpoints Failed`：失败的checkpoints数量。
+- `NumBytesInPerSecond`：该任务每秒接受的Bytes数量。
+
+
+各个指标的含义可以在图标的 tip 上找到解释
+
+
+
+# 参考文档
+
+- [Flink Prometheus](https://nightlies.apache.org/flink/flink-docs-release-2.0-preview1/docs/deployment/metric_reporters/#prometheus)
+- [SkyWalking Flink Monitoring](https://skywalking.apache.org/docs/main/next/en/setup/backend/backend-flink-monitoring/)
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