doc: add a doc on how to track user metric using action log (#692)

* doc: add a doc on how to track user metric using action log
Signed-off-by: feng-tao <fengtao04@gmail.com>

* chore: update doc
Signed-off-by: feng-tao <fengtao04@gmail.com>

* Update docs/tutorials/how-to-track-user-metric.md
Signed-off-by: Tao Feng <fengtao04@gmail.com>
Co-authored-by: jornh <jornhansen@gmail.com>

* Update docs/tutorials/how-to-track-user-metric.md
Signed-off-by: Tao Feng <fengtao04@gmail.com>
Co-authored-by: jornh <jornhansen@gmail.com>

* Update docs/tutorials/how-to-track-user-metric.md
Signed-off-by: Tao Feng <fengtao04@gmail.com>
Co-authored-by: jornh <jornhansen@gmail.com>
Co-authored-by: jornh <jornhansen@gmail.com>

docs/tutorials/how-to-track-user-metric.md

+# How to track Amundsen user metric
+
+After you have deployed Amundsen into production, you want to track how user interacts with Amundsen for various reasons. 
+
+The easier way is to leverage [Google Analytics](https://analytics.google.com/analytics/web/) for basic user tracking. You could first
+get the analytics token for your domain and put it as the [frontend config](https://github.com/amundsen-io/amundsenfrontendlibrary/blob/54de01bdc574665316f0517aefbd55cf7ca37ef0/amundsen_application/static/js/config/config-default.ts#L22)
+
+
+Besides implementing Google Analytics, we provide a way called `action_logging` to do fine grained user action tracking. 
+The `action_logging` is a decorator to allow you to integrate user info and pipe it to your inhouse event tracking system(e.g Kafka).
+
+You need to put the custom method into entry_points following this 
+[example](https://github.com/amundsen-io/amundsenfrontendlibrary/blob/54de01bdc574665316f0517aefbd55cf7ca37ef0/docs/configuration.md#action-logging).
+
+And here is the IDL proto we used at Lyft to send the event message:
+```bash
+message UserAction {
+    // Sending host name
+    google.protobuf.StringValue host_name = 1;
+    // start time in epoch ms
+    google.protobuf.Int64Value start_epoch_ms = 2;
+    // end time in epoch ms
+    google.protobuf.Int64Value end_epoch_ms = 3;
+    // json array contains positional arguments
+    common.LongString pos_args_json = 4;
+    // json object contains key word arguments
+    common.LongString keyword_args_json = 5;
+    // json object contains output of command
+    common.LongString output = 6;
+    // an error message or exception stacktrace
+    common.LongString error = 7;
+    // `user`
+    google.protobuf.StringValue user = 8;
+}
+```
+
+It matches the action log model defined in [here](https://github.com/amundsen-io/amundsenfrontendlibrary/blob/ccfd2d6b82957fef347e956b243e4048c191fc0d/amundsen_application/log/action_log_model.py).
+
+Once you have the event in your data warehouse, you could start building different KPI user metric:
+- WAU
+- DAU
+- Top 50 active user
+- Top search term
+- Top popular tables
+- Search click index
+- Metadata edits
+- Metadata edit leaders
+- Amundsen user per role (by joining with employee data)
+- ...