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"

9 files changed, 57 insertions, 31 deletions

diff --git a/collectors/COLLECTORS.md b/collectors/COLLECTORS.md
index 198aa0cef8..97d5ac2b39 100644
--- a/collectors/COLLECTORS.md
+++ b/collectors/COLLECTORS.md
@@ -27,17 +27,30 @@ explicitly [disable the Go version](https://github.com/netdata/netdata/blob/mast
 and enable the Python version. Netdata then skips the Go version and attempts to load the Python version and its
 accompanying configuration file.
 
+## Add your application to Netdata
+
 If you don't see the app/service you'd like to monitor in this list:
 
+- If your application has a Prometheus endpoint, Netdata can monitor it! Look at our 
+  [generic Prometheus collector](https://github.com/netdata/go.d.plugin/blob/master/modules/prometheus/README.md).
+
+- If your application is instrumented to expose [StatsD](https://blog.netdata.cloud/introduction-to-statsd/) metrics, 
+  see our [generic StatsD collector](https://github.com/netdata/netdata/blob/master/collectors/statsd.plugin/README.md).
+
+- If you have data in CSV, JSON, XML or other popular formats, you may be able to use our 
+  [generic structured data (Pandas) collector](https://github.com/netdata/netdata/blob/master/collectors/python.d.plugin/pandas/README.md),
+
 - Check out our [GitHub issues](https://github.com/netdata/netdata/issues). Use the search bar to look for previous
   discussions about that collector—we may be looking for assistance from users such as yourself!
+
 - If you don't see the collector there, you can make
   a [feature request](https://github.com/netdata/netdata/issues/new/choose) on GitHub.
+
 - If you have basic software development skills, you can add your own plugin
   in [Go](https://learn.netdata.cloud/docs/agent/collectors/go.d.plugin#how-to-develop-a-collector)
   or [Python](https://github.com/netdata/netdata/blob/master/docs/guides/python-collector.md)
 
-Supported Collectors List:
+## Available Collectors
 
 - [Service and application collectors](#service-and-application-collectors)
     - [Generic](#generic)
diff --git a/collectors/REFERENCE.md b/collectors/REFERENCE.md
index 8ca4ef7f8e..96c6057d35 100644
--- a/collectors/REFERENCE.md
+++ b/collectors/REFERENCE.md
@@ -14,9 +14,9 @@ and on [our website](https://www.netdata.cloud/integrations). The documentation
 necessary configuration options and prerequisites for that collector. In most cases, either the charts are automatically generated 
 without any configuration, or you just fulfil those prerequisites and [configure the collector](#configure-a-collector).
 
-If the application you are interested in monitoring is not listed in our integrations, 
-look at our [generic Prometheus collector](https://github.com/netdata/go.d.plugin/blob/master/modules/prometheus/README.md) 
-or [write a custom collector in Go](https://github.com/netdata/go.d.plugin/blob/master/docs/how-to-write-a-module.md).
+If the application you are interested in monitoring is not listed in our integrations, the collectors list includes 
+the available options to 
+[add your application to Netdata](https://github.com/netdata/netdata/edit/master/collectors/COLLECTORS.md#add-your-application-to-netdata).
 
 If we do support your collector but the charts described in the documentation don't appear on your dashboard, the reason will 
 be one of the following:
diff --git a/collectors/python.d.plugin/alarms/README.md b/collectors/python.d.plugin/alarms/README.md
index 4eaca4d103..9ffb3da220 100644
--- a/collectors/python.d.plugin/alarms/README.md
+++ b/collectors/python.d.plugin/alarms/README.md
@@ -3,7 +3,7 @@ title: "Alarms"
 custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/python.d.plugin/alarms/README.md"
 sidebar_label: "Alarms"
 learn_status: "Published"
-learn_rel_path: "Integrations/Monitoring"
+learn_rel_path: "Integrations/Monitor/Netdata"
 -->
 
 # Alarms - graphing Netdata alarm states over time
diff --git a/collectors/python.d.plugin/anomalies/README.md b/collectors/python.d.plugin/anomalies/README.md
index 7c20a388b9..2013213c13 100644
--- a/collectors/python.d.plugin/anomalies/README.md
+++ b/collectors/python.d.plugin/anomalies/README.md
@@ -5,8 +5,7 @@ custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/pyth
 sidebar_url: "Anomalies"
 sidebar_label: "anomalies"
 learn_status: "Published"
-learn_topic_type: "References"
-learn_rel_path: "Integrations/Monitor/Misc"
+learn_rel_path: "Integrations/Monitor/Anything"
 -->
 
 # Anomaly detection with Netdata
diff --git a/collectors/python.d.plugin/pandas/README.md b/collectors/python.d.plugin/pandas/README.md
index 06bb8542f4..24eddb6ee9 100644
--- a/collectors/python.d.plugin/pandas/README.md
+++ b/collectors/python.d.plugin/pandas/README.md
@@ -1,20 +1,24 @@
 <!--
 custom_edit_url: https://github.com/netdata/netdata/edit/master/collectors/python.d.plugin/pandas/README.md
-title: "Pandas Netdata Collector"
-sidebar_label: "Pandas Netdata Collector"
+title: "Ingest structured data (Pandas)"
+sidebar_label: "Ingest structured data (Pandas)"
 learn_status: "Published"
 learn_topic_type: "References"
-learn_rel_path: "Integrations/Monitoring"
+learn_rel_path: "Integrations/Monitor/Anything"
 -->
 
-# Pandas Netdata Collector
+# Ingest structured data (Pandas)
 
 <a href="https://pandas.pydata.org/" target="_blank">
   <img src="https://pandas.pydata.org/docs/_static/pandas.svg" alt="Pandas" width="100px" height="50px" />
  </a>
 
-A python collector using [pandas](https://pandas.pydata.org/) to pull data and do pandas based 
-preprocessing before feeding to Netdata.
+[Pandas](https://pandas.pydata.org/) is a de-facto standard in reading and processing most types of structured data in Python.
+If you have metrics appearing in a CSV, JSON, XML, HTML, or [other supported format](https://pandas.pydata.org/docs/user_guide/io.html), 
+either locally or via some HTTP endpoint, you can easily ingest and present those metrics in Netdata, by leveraging the Pandas collector.
+
+The collector uses [pandas](https://pandas.pydata.org/) to pull data and do pandas-based 
+preprocessing, before feeding to Netdata.
 
 ## Requirements
 
diff --git a/collectors/python.d.plugin/zscores/README.md b/collectors/python.d.plugin/zscores/README.md
index 0caa88ea61..f41ec42e13 100644
--- a/collectors/python.d.plugin/zscores/README.md
+++ b/collectors/python.d.plugin/zscores/README.md
@@ -5,7 +5,7 @@ custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/pyth
 sidebar_label: "zscores"
 learn_status: "Published"
 learn_topic_type: "References"
-learn_rel_path: "Integrations/Monitor/Uncategorized"
+learn_rel_path: "Integrations/Monitor/Netdata"
 -->
 
 # Z-Scores - basic anomaly detection for your key metrics and charts
diff --git a/collectors/statsd.plugin/README.md b/collectors/statsd.plugin/README.md
index 462c099754..538f7f6f00 100644
--- a/collectors/statsd.plugin/README.md
+++ b/collectors/statsd.plugin/README.md
@@ -1,29 +1,38 @@
 <!--
-title: "statsd.plugin"
+title: "StatsD"
 description: "The Netdata Agent is a fully-featured StatsD server that collects metrics from any custom application and visualizes them in real-time."
 custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/statsd.plugin/README.md"
-sidebar_label: "statsd.plugin"
+sidebar_label: "StatsD"
 learn_status: "Published"
-learn_topic_type: "References"
-learn_rel_path: "Integrations/Monitor/Apm"
+learn_rel_path: "Integrations/Monitor/Anything"
 -->
 
-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.
+[StatsD](https://github.com/statsd/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.
 
-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!
+If you want to learn more about the StatsD protocol, we have written a 
+[blog post](https://blog.netdata.cloud/introduction-to-statsd/) about it!
 
 
-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.
+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.
 
-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. 
+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. 
 
 Since statsd is embedded in Netdata, it means you now have a statsd server embedded on all your servers. 
 
-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.
+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.
 
 ## Available StatsD synthetic application charts
 
-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.
+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.
 
 On synthetic charts, we can have alarms as with any metric and chart.
 
@@ -38,13 +47,16 @@ On synthetic charts, we can have alarms as with any metric and chart.
 
 ## Metrics supported by Netdata
 
-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.
+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.
 
 - **Gauges**
 
-     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).
+     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).
 
-     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). 
+     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). 
 
      [Sampling rate](#sampling-rates) is supported.
      [Tags](#tags) are supported for changing chart units, family and dimension name.
diff --git a/collectors/statsd.plugin/asterisk.md b/collectors/statsd.plugin/asterisk.md
index 9d7948111e..fa3bdafc17 100644
--- a/collectors/statsd.plugin/asterisk.md
+++ b/collectors/statsd.plugin/asterisk.md
@@ -3,8 +3,7 @@ title: "Asterisk monitoring with Netdata"
 custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/statsd.plugin/asterisk.md"
 sidebar_label: "Asterisk"
 learn_status: "Published"
-learn_topic_type: "References"
-learn_rel_path: "References/Collectors references/Apm/Statsd"
+learn_rel_path: "Integrations/Monitor/VoIP"
 -->
 
 # Asterisk monitoring with Netdata
diff --git a/collectors/statsd.plugin/k6.md b/collectors/statsd.plugin/k6.md
index 7a1e367737..d202c88fbe 100644
--- a/collectors/statsd.plugin/k6.md
+++ b/collectors/statsd.plugin/k6.md
@@ -3,8 +3,7 @@ title: "K6 load test monitoring with Netdata"
 custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/statsd.plugin/k6.md"
 sidebar_label: "K6 Load Testing"
 learn_status: "Published"
-learn_topic_type: "References"
-learn_rel_path: "References/Collectors references/Apm/Statsd"
+learn_rel_path: "Integrations/Monitor/apps"
 -->
 
 # K6 Load Testing monitoring with Netdata