Learn integrations category changes (#14510)
* Better present netdata pandas and fix how to add new charts to netdata * Properly categorize statsd and show it as a generic collector. Move asterisk and k6 Elevate anomaly detection to "monitor anything"
Chris Akritidis committed
Feb 12, 2023 at 09:28 UTC
aebab7080db556eb7393f20a096094a4a1895ff4
9 files changed
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collectors/COLLECTORS.md
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@@ -27,17 +27,30 @@ explicitly [disable the Go version](https://github.com/netdata/netdata/blob/mast
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and enable the Python version. Netdata then skips the Go version and attempts to load the Python version and its
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accompanying configuration file.
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+## Add your application to Netdata
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+
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If you don't see the app/service you'd like to monitor in this list:
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+- If your application has a Prometheus endpoint, Netdata can monitor it! Look at our
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+ [generic Prometheus collector](https://github.com/netdata/go.d.plugin/blob/master/modules/prometheus/README.md).
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+
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+- If your application is instrumented to expose [StatsD](https://blog.netdata.cloud/introduction-to-statsd/) metrics,
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+ see our [generic StatsD collector](https://github.com/netdata/netdata/blob/master/collectors/statsd.plugin/README.md).
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+
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+- If you have data in CSV, JSON, XML or other popular formats, you may be able to use our
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+ [generic structured data (Pandas) collector](https://github.com/netdata/netdata/blob/master/collectors/python.d.plugin/pandas/README.md),
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+
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- Check out our [GitHub issues](https://github.com/netdata/netdata/issues). Use the search bar to look for previous
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discussions about that collector—we may be looking for assistance from users such as yourself!
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+
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- If you don't see the collector there, you can make
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a [feature request](https://github.com/netdata/netdata/issues/new/choose) on GitHub.
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+
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- If you have basic software development skills, you can add your own plugin
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in [Go](https://learn.netdata.cloud/docs/agent/collectors/go.d.plugin#how-to-develop-a-collector)
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or [Python](https://github.com/netdata/netdata/blob/master/docs/guides/python-collector.md)
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-Supported Collectors List:
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+## Available Collectors
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- [Service and application collectors](#service-and-application-collectors)
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- [Generic](#generic)
collectors/REFERENCE.md
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@@ -14,9 +14,9 @@ and on [our website](https://www.netdata.cloud/integrations). The documentation
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necessary configuration options and prerequisites for that collector. In most cases, either the charts are automatically generated
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without any configuration, or you just fulfil those prerequisites and [configure the collector](#configure-a-collector).
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-If the application you are interested in monitoring is not listed in our integrations,
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-look at our [generic Prometheus collector](https://github.com/netdata/go.d.plugin/blob/master/modules/prometheus/README.md)
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-or [write a custom collector in Go](https://github.com/netdata/go.d.plugin/blob/master/docs/how-to-write-a-module.md).
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+If the application you are interested in monitoring is not listed in our integrations, the collectors list includes
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+the available options to
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+[add your application to Netdata](https://github.com/netdata/netdata/edit/master/collectors/COLLECTORS.md#add-your-application-to-netdata).
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If we do support your collector but the charts described in the documentation don't appear on your dashboard, the reason will
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be one of the following:
collectors/python.d.plugin/alarms/README.md
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@@ -3,7 +3,7 @@ title: "Alarms"
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custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/python.d.plugin/alarms/README.md"
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sidebar_label: "Alarms"
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learn_status: "Published"
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-learn_rel_path: "Integrations/Monitoring"
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+learn_rel_path: "Integrations/Monitor/Netdata"
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-->
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# Alarms - graphing Netdata alarm states over time
collectors/python.d.plugin/anomalies/README.md
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@@ -5,8 +5,7 @@ custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/pyth
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sidebar_url: "Anomalies"
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sidebar_label: "anomalies"
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learn_status: "Published"
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-learn_topic_type: "References"
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-learn_rel_path: "Integrations/Monitor/Misc"
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+learn_rel_path: "Integrations/Monitor/Anything"
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-->
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# Anomaly detection with Netdata
collectors/python.d.plugin/pandas/README.md
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<!--
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custom_edit_url: https://github.com/netdata/netdata/edit/master/collectors/python.d.plugin/pandas/README.md
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-title: "Pandas Netdata Collector"
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-sidebar_label: "Pandas Netdata Collector"
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+title: "Ingest structured data (Pandas)"
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+sidebar_label: "Ingest structured data (Pandas)"
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learn_status: "Published"
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learn_topic_type: "References"
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-learn_rel_path: "Integrations/Monitoring"
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+learn_rel_path: "Integrations/Monitor/Anything"
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-->
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-# Pandas Netdata Collector
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+# Ingest structured data (Pandas)
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<a href="https://pandas.pydata.org/" target="_blank">
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<img src="https://pandas.pydata.org/docs/_static/pandas.svg" alt="Pandas" width="100px" height="50px" />
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</a>
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-A python collector using [pandas](https://pandas.pydata.org/) to pull data and do pandas based
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-preprocessing before feeding to Netdata.
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+[Pandas](https://pandas.pydata.org/) is a de-facto standard in reading and processing most types of structured data in Python.
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+If you have metrics appearing in a CSV, JSON, XML, HTML, or [other supported format](https://pandas.pydata.org/docs/user_guide/io.html),
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+either locally or via some HTTP endpoint, you can easily ingest and present those metrics in Netdata, by leveraging the Pandas collector.
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+
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+The collector uses [pandas](https://pandas.pydata.org/) to pull data and do pandas-based
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+preprocessing, before feeding to Netdata.
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## Requirements
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collectors/python.d.plugin/zscores/README.md
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sidebar_label: "zscores"
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learn_status: "Published"
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learn_topic_type: "References"
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-learn_rel_path: "Integrations/Monitor/Uncategorized"
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+learn_rel_path: "Integrations/Monitor/Netdata"
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-->
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# Z-Scores - basic anomaly detection for your key metrics and charts
collectors/statsd.plugin/README.md
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<!--
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-title: "statsd.plugin"
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+title: "StatsD"
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description: "The Netdata Agent is a fully-featured StatsD server that collects metrics from any custom application and visualizes them in real-time."
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custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/statsd.plugin/README.md"
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-sidebar_label: "statsd.plugin"
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+sidebar_label: "StatsD"
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learn_status: "Published"
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-learn_topic_type: "References"
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-learn_rel_path: "Integrations/Monitor/Apm"
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+learn_rel_path: "Integrations/Monitor/Anything"
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-->
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-StatsD is a system to collect data from any application. Applications send metrics to it, usually via non-blocking UDP communication, and StatsD servers collect these metrics, perform a few simple calculations on them and push them to backend time-series databases.
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+[StatsD](https://github.com/statsd/statsd) is a system to collect data from any application. Applications send metrics to it,
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+usually via non-blocking UDP communication, and StatsD servers collect these metrics, perform a few simple calculations on
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+them and push them to backend time-series databases.
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-If you want to learn more about the StatsD protocol, we have written a [blog post](https://www.netdata.cloud/blog/introduction-to-statsd/) about it!
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+If you want to learn more about the StatsD protocol, we have written a
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+[blog post](https://blog.netdata.cloud/introduction-to-statsd/) about it!
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-Netdata is a fully featured statsd server. It can collect statsd formatted metrics, visualize them on its dashboards and store them in it's database for long-term retention.
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+Netdata is a fully featured statsd server. It can collect statsd formatted metrics, visualize
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+them on its dashboards and store them in it's database for long-term retention.
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-Netdata statsd is inside Netdata (an internal plugin, running inside the Netdata daemon), it is configured via `netdata.conf` and by-default listens on standard statsd port 8125. Netdata supports both TCP and UDP packets at the same time.
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+Netdata statsd is inside Netdata (an internal plugin, running inside the Netdata daemon), it is
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+configured via `netdata.conf` and by-default listens on standard statsd port 8125. Netdata supports
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+both TCP and UDP packets at the same time.
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Since statsd is embedded in Netdata, it means you now have a statsd server embedded on all your servers.
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-Netdata statsd is fast. It can collect several millions of metrics per second on modern hardware, using just 1 CPU core. The implementation uses two threads: one thread collects metrics, another thread updates the charts from the collected data.
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+Netdata statsd is fast. It can collect several millions of metrics per second on modern hardware, using
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+just 1 CPU core. The implementation uses two threads: one thread collects metrics, another thread updates
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+the charts from the collected data.
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## Available StatsD synthetic application charts
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-Netdata ships with a few synthetic chart definitions to automatically present application metrics into a more uniform way. These synthetic charts are configuration files (you can create your own) that re-arrange statsd metrics into a more meaningful way.
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+Netdata ships with a few synthetic chart definitions to automatically present application metrics into a
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+more uniform way. These synthetic charts are configuration files (you can create your own) that re-arrange
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+statsd metrics into a more meaningful way.
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On synthetic charts, we can have alarms as with any metric and chart.
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@@ -38,13 +47,16 @@ On synthetic charts, we can have alarms as with any metric and chart.
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## Metrics supported by Netdata
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-Netdata fully supports the StatsD protocol and also extends it to support more advanced Netdata specific use cases. All StatsD client libraries can be used with Netdata too.
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+Netdata fully supports the StatsD protocol and also extends it to support more advanced Netdata specific use cases.
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+All StatsD client libraries can be used with Netdata too.
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- **Gauges**
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- The application sends `name:value|g`, where `value` is any **decimal/fractional** number, StatsD reports the latest value collected and the number of times it was updated (events).
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+ The application sends `name:value|g`, where `value` is any **decimal/fractional** number, StatsD reports the
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+ latest value collected and the number of times it was updated (events).
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- The application may increment or decrement a previous value, by setting the first character of the value to `+` or `-` (so, the only way to set a gauge to an absolute negative value, is to first set it to zero).
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+ The application may increment or decrement a previous value, by setting the first character of the value to
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+ `+` or `-` (so, the only way to set a gauge to an absolute negative value, is to first set it to zero).
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[Sampling rate](#sampling-rates) is supported.
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[Tags](#tags) are supported for changing chart units, family and dimension name.
collectors/statsd.plugin/asterisk.md
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custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/statsd.plugin/asterisk.md"
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sidebar_label: "Asterisk"
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learn_status: "Published"
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-learn_topic_type: "References"
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-learn_rel_path: "References/Collectors references/Apm/Statsd"
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+learn_rel_path: "Integrations/Monitor/VoIP"
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-->
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# Asterisk monitoring with Netdata
collectors/statsd.plugin/k6.md
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custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/statsd.plugin/k6.md"
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sidebar_label: "K6 Load Testing"
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learn_status: "Published"
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-learn_topic_type: "References"
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-learn_rel_path: "References/Collectors references/Apm/Statsd"
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+learn_rel_path: "Integrations/Monitor/apps"
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-->
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# K6 Load Testing monitoring with Netdata