clarify that our log handlers shouldn't be used for "normal" log shipping

docs/django.asciidoc

@@ -191,11 +191,17 @@ ELASTIC_APM = {
 
 [float]
 [[django-logging]]
-=== Logging
+=== Integrating with Python logging
 
-For fine-grained control over logging use Python's built-in logging module.
-If you are new to how the logging module works together with Django, read more
-https://docs.djangoproject.com/en/1.7/topics/logging/[in the Django documentation].
+To easily send Python `logging` messages as "error" objects to Elasticsearch,
+we provide a `LoggingHandler` which you can use in your logging setup.
+The log messages will be enriched with a stack trace, data from the request, and more.
+
+NOTE: the intended use case for this handler is to send high priority log messages (e.g. log messages with level `ERROR`)
+to Elasticsearch. For normal log shipping, we recommend using {filebeat-ref}[filebeat].
+
+If you are new to how the `logging` module works together with Django, read more
+https://docs.djangoproject.com/en/2.1/topics/logging/[in the Django documentation].
 
 An example of how your `LOGGING` setting could look:
 

docs/flask.asciidoc

@@ -158,6 +158,7 @@ apm = ElasticAPM(app, logging=True)
 
 NOTE: using `logging=True` can lead to high number of logs being sent to Elastic APM.
 We recommend to always limit logging with Elastic APM to a high level (`WARNING` or `ERROR`).
+For shipping of less urgent logs, we recommend to use {filebeat-ref}[filebeat].
 
 For fine-grained control, you can initialize a logging handler and add it,
 just as you would with any other handler.