[DOCS] Move pipeline viewer pages (#8567)

* [DOCS] Move pipeline viewer pages

* [DOCS] Addressed feedback about monitoring info
This commit is contained in:
Lisa Cawley 2017-11-02 16:25:44 -07:00 committed by lcawley
parent 06d78688f8
commit 5cc3ef8ea2
11 changed files with 7 additions and 168 deletions

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@ -74,11 +74,6 @@ include::static/performance-checklist.asciidoc[]
:edit_url: https://github.com/elastic/logstash/edit/{branch}/docs/static/monitoring.asciidoc
include::static/monitoring.asciidoc[]
// Pipeline viewer
:edit_url: https://github.com/elastic/logstash/edit/{branch}/docs/static/pipeline-viewer.asciidoc
include::static/pipeline-viewer.asciidoc[]
// Monitoring APIs
:edit_url: https://github.com/elastic/logstash/edit/{branch}/docs/static/monitoring-apis.asciidoc

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@ -12,37 +12,11 @@ The metrics collected by Logstash include:
runtime stats.
* Hot threads.
You can use the <<logstash-monitoring-ui,monitoring UI>> in {xpack} to view
these metrics and gain insight into how your Logstash deployment is running.
You can use the basic <<monitoring,monitoring APIs>> providing by Logstash
to retrieve these metrics. These APIs are available by default without
requiring any extra configuration.
Or you can use the basic <<monitoring,monitoring APIs>> providing by Logstash
to retrieve these metrics.
The <<logstash-pipeline-viewer,pipeline viewer>> in {xpack} offers additional
visibility into the behavior and performance of complex pipeline configurations.
It shows a graph representation of the overall pipeline topology, data flow, and
branching logic, overlayed with important metrics, like events per second, for
each plugin in the view.
[role="xpack"]
[[logstash-monitoring-ui]]
=== Monitoring UI
NOTE: Monitoring is an X-Pack feature under the Basic License and is therefore
*free to use*. To get started, consult the
{xpack-ref}/monitoring-logstash.html[Logstash monitoring documentation].
When running Logstash 5.2 or greater, you can use the
https://www.elastic.co/products/x-pack/monitoring[monitoring feature in X-Pack]
to gain deep visibility into metrics about your Logstash deployment. In the
overview dashboard, you can see all events received and sent by Logstash, plus
info about memory usage and uptime:
image::static/images/overviewstats.png[Logstash monitoring overview dashboard in Kibana]
Then you can drill down to see stats about a specific node:
image::static/images/nodestats.png[Logstash monitoring node stats dashboard in Kibana]
See the {xpack-ref}/monitoring-logstash.html[Logstash monitoring documentation] to learn
how to set up and use this feature.
ifdef::include-xpack[]
:edit_url!:
include::{xls-repo-dir}/monitoring/index.asciidoc[]
endif::include-xpack[]

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@ -1,130 +0,0 @@
[role="xpack"]
[[logstash-pipeline-viewer]]
=== Pipeline Viewer UI
NOTE: The Logstash pipeline viewer is an
https://www.elastic.co/products/x-pack[X-Pack] feature under the Basic License
and is therefore free to use.
The pipeline viewer in {xpack} provides a simple way for you to visualize and
monitor the behavior of complex Logstash pipeline configurations. Within the
pipeline viewer, you can explore a directed acyclic graph (DAG) representation
of the overall pipeline topology, data flow, and branching logic. The diagram
is overlayed with important metrics, like events per second and time spent in
milliseconds, for each plugin in the view.
The diagram includes visual indicators to draw your attention to potential
bottlenecks in the pipeline, making it easy for you to diagnose and fix
problems.
[IMPORTANT]
==========================================================================
When you configure the stages in your Logstash pipeline, make sure you specify
semantic IDs. If you don't specify IDs, Logstash generates them for you.
Using semantic IDs makes it easier to identify the configurations that are
causing bottlenecks. For example, you may have several grok filters running
in your pipeline. If you haven't specified semantic IDs, you won't be able
to tell at a glance which filters are slow. If you specify semantic IDs,
such as `apacheParsingGrok` and `cloudwatchGrok`, you'll know exactly which
grok filters are causing bottlenecks.
==========================================================================
Before using the pipeline viewer, you need to
{logstash-ref}/setup-xpack.html[set up {xpack}] and configure
{xpack-ref}/monitoring-logstash.html[Logstash monitoring].
[float]
==== What types of problems does the pipeline viewer show?
The pipeline viewer highlights CPU% and event latency in cases where the values
are anomalous. The purpose of these highlights is to enable users to quickly
identify processing that is disproportionately slow. This may not necessarily
mean that anything is wrong with a given plugin, since some plugins are slower
than others due to the nature of the work they do. For instance, you may find
that a grok filter that uses a complicated regexp runs a lot slower than a
mutate filter that simply adds a field. The grok filter might be highlighted in
this case, though it may not be possible to further optimize its work.
The exact formula used is a heuristic, and thus is subject to change.
[float]
==== View the pipeline diagram
To view the pipeline diagram:
. In Logstash, start the Logstash pipeline that you want to monitor.
+
Assuming that you've set up Logstash monitoring, Logstash will begin shipping
metrics to the monitoring cluster.
. Navigate to the Monitoring tab in Kibana.
+
You should see a Logstash section.
+
image::static/images/monitoring-ui.png[Monitoring UI]
. Click the *Pipelines* link under Logstash to see all the pipelines that are
being monitored.
+
Each pipeline is identified by a pipeline ID (`main` by default). For each
pipeline, you'll see a list of all versions of the pipeline stats that were
captured during the specified time range.
+
image::static/images/pipeline-viewer-overview.png[Pipeline Overview]
+
The version information is auto-generated by Logstash. Each time you modify a
pipeline, Logstash generates a new version hash. Viewing different versions
of the pipeline stats allows you see how changes to the pipeline over time
affect throughput and other metrics. Note that Logstash stores multiple versions
of the pipeline stats; it does not store multiple versions of the pipeline
configurations themselves.
. Click a pipeline version in the list to drill down and explore the pipeline
diagram.
+
The diagram shows all the stages feeding data through the pipeline. It also shows
conditional logic.
+
image::static/images/pipeline-diagram.png[Pipeline Diagram]
+
The information displayed on each node varies depending on the plugin type.
+
Here's an example of an *input* node:
+
image::static/images/pipeline-input-detail.png[Input node]
+
The *I* badge indicates that this is an input stage. The node shows:
+
--
* input type - *stdin*
* user-supplied ID - *logfileRead*
* throughput expressed in events per second - *0.7 e/s*
Here's an example of a *filter* node.
image::static/images/pipeline-filter-detail.png[Filter node]
The filter icon indicates that this is a filter stage. The node shows:
* filter type - *sleep*
* user-supplied ID - *caSleep*
* worker usage expressed as the percentage of total execution time - *0%*
* performance - the number of milliseconds spent processing each event - *20.00 ms/e*
* throughput - the number of events sent per second - *0.0 e/s*
Stats that are anomalously slow appear highlighted in the pipeline viewer.
This doesn't necessarily indicate a problem, but it highlights potential
bottle necks so that you can find them quickly.
An *output* node shows the same information as a filter node, but it has an
*O* badge to indicate that it is an output stage:
image::static/images/pipeline-output-detail.png[Output node]
--
. Hover over a node in the diagram, and you'll see only the related nodes that
are ancestors or descendants of the current node.
. Explore the diagram and look for performance anomalies.