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Point stream monitoring to microsite
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spring-cloud-dataflow-docs/src/main/asciidoc/streams-monitoring-cloudfoundry.adoc

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spring-cloud-dataflow-docs/src/main/asciidoc/streams-monitoring-kubernetes.adoc

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spring-cloud-dataflow-docs/src/main/asciidoc/streams-monitoring-local.adoc

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[[streams-monitoring]]
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= Stream Monitoring
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This section describes how to monitor the applications that were deployed as part of a Stream.
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The setup for each platform is different but the general architecture is the same across the platforms.
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The Data Flow 2.x metrics architecture is designed around the https://micrometer.io/[Micrometer library] which is a Vendor-neutral application metrics facade.
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It provides a simple facade over the instrumentation clients for the most popular monitoring systems.
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See the https://micrometer.io/docs[Micrometer documentation] for the list of supported monitoring systems.
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Starting with Spring Boot 2.0, Micrometer is the instrumentation library https://docs.spring.io/spring-integration/docs/current/reference/html/system-management-chapter.html#micrometer-integration[powering the delivery of application metrics from Spring Boot].
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Spring Integration provides https://docs.spring.io/spring-integration/docs/current/reference/html/system-management-chapter.html#micrometer-integration[additional integration] to expose metrics around message rates and errors which is critical to the monitoring of deployed Streams.
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All Spring Cloud Stream App Starters are configured to support two of the most popular monitoring systems, Prometheus and InfluxDB.
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You can declaratively select which monitoring system to use.
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If you are not using Prometheus or InfluxDB, you can customise the App starters to use a different monitoring system as well as include your preferred micrometer monitoring system library in your own custom applications.
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To help you get started monitoring Streams, Data Flow provides https://grafana.com/[Grafana Dashboards] you can install and customize for your needs. Support for monitoring Tasks is on the roadmap.
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The general architecture of how applications are monitored is shown below.
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.The Spring Cloud Data Flow Monitoring Architecture
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image::{dataflow-asciidoc}/images/micrometer-arch.png[Micrometer Monitoring Architecture, scaledwidth="80%"]
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.Each Spring Cloud Stream application sends send metrics to a monitoring system, often a Time Series Database (TSDB).
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.Connect Grafana to the selected monitoring system and install the provided Grafana dashboards that visualize different aspects of the running stream applications..
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.The Data Flow UI provides buttons to open the Grafana dashboard for each stream.
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To allow aggregating metrics per application type, per instance or per stream the Spring <<applications,Cloud Stream Application Starters>> are configured to use the following Micrometer tags:
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[width="100%",frame="topbot",options="header"]
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|===
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|Tag Name| Description
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|stream.name
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|Name of the Stream that contains the applications sending the metrics
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|application.name
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|Name or label of the application reporting the metrics
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|application.type
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|The type (Sourcer, Processor or SInk) of the application reporting the metrics.
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|application.guid
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|Unique instance identifier of the application instance reporting the metrics
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|application.index
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|application instance id (when available)
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|===
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If the Data Flow server is started with the `spring.cloud.dataflow.grafana-info.url` property pointing to your Grafana URL, then the Grafana feature is enabled and Data Flow UI will provide you with Grafana-buttons that can open particular dashboard for given stream, application or application instance. Following screenshot illustrates these buttons:
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image::{dataflow-asciidoc}/images/grafana-scdf-ui-buttons-streams.png[Data Flow UI Grafana Buttons - Streams, scaledwidth="70%"]
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image::{dataflow-asciidoc}/images/grafana-scdf-ui-buttons-apps.png[Data Flow UI Grafana Buttons - Applications, scaledwidth="70%"]
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As setting up Prometheus and InfluxDB is different depending on the platform you are running on, we provide instructions for each platform.
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In Spring Cloud Data Flow 2.x, local server and Kubernetes instructions have been provided.
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include::streams-monitoring-local.adoc[]
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include::streams-monitoring-kubernetes.adoc[]
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Please see the link:https://dataflow.spring.io/docs/feature-guides/streams/monitoring/[Stream Monitoring] Guide of the microsite for more information on how to monitor the applications that were deployed as part of a Stream.
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