JH-A-Kim commented on code in PR #67994:
URL: https://github.com/apache/airflow/pull/67994#discussion_r3384425157


##########
airflow-core/docs/core-concepts/overview.rst:
##########
@@ -49,15 +49,19 @@ A minimal Airflow installation consists of the following 
components:
   a configuration property of the *scheduler*, not a separate component and 
runs within the scheduler
   process. There are several executors available out of the box, and you can 
also write your own.
 
-* A *Dag processor*, which parses Dag files and serializes them into the
+* A *Dag processor*, which parses Dag files from a *Dag bundle* and serializes 
them into the
   *metadata database*. More about processing Dag files can be found in
   :doc:`/administration-and-deployment/dagfile-processing`
 
-* A *webserver*, which presents a handy user interface to inspect, trigger and 
debug the behaviour of
-  Dags and tasks.
+* A *Dag bundle*, which is configured for the *Dag processor* to parse Dag 
files from and allow *workers* to access the correct version of the Dag file. 
By default, this is a local folder on disk. More about Dag bundles can be found 
in
+  :doc:`/administration-and-deployment/dag-bundles`
 
-* A folder of *Dag files*, which is read by the *scheduler* to figure out what 
tasks to run and when to
-  run them.
+* An *API Server*, which serves the REST API and presents a handy user 
interface to inspect, trigger and debug the behaviour of
+  Dags and tasks. The API server is also used by *workers* to communicate 
state back to Airflow, without requiring direct access
+  to the *metadata database*.
+
+* The *Task SDK*, which is an isolated runtime environment inside the 
*workers* that executes the user-defined Dag code.

Review Comment:
   Thank you for the help. I resolved in this commit 
ed153f0b9d2b124fdb2cfe2d7e479c5ee50bc94d
   
   Thank you!



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