Update airflow.md (#1400)

Co-authored-by: guyhardonag <[email protected]>

docs/using/airflow.md

@@ -1,10 +1,43 @@
 ---
 layout: default
 title: Airflow
-description: Querying data in lakeFS from Presto is the same as querying data in S3 from Presto. It is done using the Hive connector.
+description: Easily build reproducible data pipelines with Airflow and lakeFS using commits, without modifying the code or logic of your job.
 parent: Using lakeFS with...
 nav_order: 10
 has_children: false
 ---
 
-# Using lakeFS with Airflow
+# Using lakeFS with Airflow
+
+
+There are two aspects we will need to handle in order to run Airflow with lakeFS:
+
+## Access and Insert data through lakeFS
+Since lakeFS supports AWS S3 API, it works seamlessly with all operators that work on top of S3 (such as SparkSubmitOperator, S3FileTransormOperator, etc.)
+
+All we need to do is set lakeFS as the endpoint-url and use our lakeFS credentials instead of our S3 credentials and that’s about it.
+
+We could then run tasks on lakeFS using the lakeFS path convention 
+
+```s3://[REPOSITORY]/[BRANCH]/PATH/TO/OBJECT```
+
+The lakeFS docs contain explanations and examples on how to use lakeFS with [AWS CLI](aws_cli.md), [Spark](spark.md), [Presto](presto.md) and many more. 
+
+## Run lakeFS commands such as creating branches, committing, merging, etc.
+We currently have two options to run lakeFS commands with Airflow
+Using the SimpleHttpOperator to send [API requests](../reference/api.md) to lakeFS. Or we could use the bashOperator with [lakeCTL](../quickstart/lakefs_cli.md) commands.
+
+For example, a commit task using the bashOperator:
+
+```python
+
+commit_extract = BashOperator(
+       task_id='commit_extract',
+       bash_command='lakectl commit lakefs://example_repo@example_dag_branch -m "extract data"',
+       dag=dag,
+       )
+```
+
+
+
+