3688 docs rfc writing test for anagha (#3689)

* feat: add Apache Airflow integration


Signed-off-by: Iain Cox <[email protected]>
Co-authored-by: Anastasiia Tovpeko <[email protected]>

use-timescale/integrations/apache-airflow.md

@@ -0,0 +1,150 @@
+---
+title: Integrate Apache Airflow with Timescale Cloud
+excerpt: How to install the psql client for PostgreSQL
+products: [cloud, mst, self_hosted]
+keywords: [connect, integrate, apache, airflow]
+---
+
+import IntegrationPrereqs from "versionContent/_partials/_integration-prereqs.mdx";
+
+# Integrate Apache Airflow with $CLOUD_LONG
+
+Apache Airflow® is a platform created by the community to programmatically author, schedule, and monitor workflows.
+
+A [DAG (Directed Acyclic Graph)][Airflow-DAG] is the core concept of Airflow, collecting [Tasks][Airflow-Task] together,
+organized with dependencies and relationships to say how they should run. You declare a DAG in a Python file
+in the `$AIRFLOW_HOME/dags` folder of your Airflow instance.
+
+This page shows you how to use a Python connector in a DAG to integrate Apache Airflow with a $SERVICE_LONG.
+
+## Prerequisites
+
+<IntegrationPrereqs />
+
+* [Install Python3 and pip3][install-python-pip] 
+* [Install Apache Airflow][install-apache-airflow]
+
+   Ensure that your Airflow instance has network access to $CLOUD_LONG.
+
+This example DAG uses the `company` table you create in  [Create regular PostgreSQL tables for relational data][create-a-table-in-timescale]
+
+## Install python connectivity libraries
+
+To install the Python libraries required to connect to $CLOUD_LONG:
+
+<Procedure>
+
+1. **Enable PostgreSQL connections between Airflow and $CLOUD_LONG**
+
+    ```bash
+    pip install psycopg2-binary
+    ```
+
+1. **Enable PostgreSQL connection types in the Airflow UI**
+
+    ```bash
+    pip install apache-airflow-providers-postgres
+    ```
+
+</Procedure>
+
+## Create a connection between Airflow and your $SERVICE_LONG
+
+In your Airflow instance, securely connect to your $SERVICE_LONG:
+
+<Procedure>
+
+1.  **Run Airflow**
+
+    On your development machine, run the following command:
+
+    ```bash
+    airflow standalone
+    ```
+
+    The username and password for Airflow UI are displayed in the `standalone | Login with username`
+    line in the output.
+
+1. **Add a connection from Airflow to your $SERVICE_LONG**
+
+   1. In your browser, navigate to `localhost:8080`, then select `Admin` > `Connections`.
+   1. Click `+` (Add a new record), then use your [connection info][connection-info] to fill in 
+      the form. The `Connection Type` is `Postgres`.
+
+</Procedure> 
+
+## Exchange data between Airflow and your $SERVICE_LONG
+
+To exchange data between Airflow and your $SERVICE_LONG:
+
+<Procedure>
+
+1. **Create and execute a DAG** 
+
+   To insert data in your $SERVICE_LONG from Airflow:
+   1. In `$AIRFLOW_HOME/dags/timescale_dag.py`, add the following code:
+
+       ```python
+       from airflow import DAG
+       from airflow.operators.python_operator import PythonOperator
+       from airflow.hooks.postgres_hook import PostgresHook
+       from datetime import datetime
+   
+       def insert_data_to_timescale():
+           hook = PostgresHook(postgres_conn_id='the ID of the connenction you created')
+           conn = hook.get_conn()
+           cursor = conn.cursor()
+           """
+             This could be any query. This example inserts data into the table
+             you create in:
+      
+             https://docs.timescale.com/getting-started/latest/tables-hypertables/#create-regular-postgresql-tables-for-relational-data
+            """            
+           cursor.execute("INSERT INTO company (symbol, name) VALUES (%s, %s)",
+                   ('new_company_symbol', 'New Company Name'))
+           conn.commit()
+           cursor.close()
+           conn.close()
+   
+       default_args = {
+           'owner': 'airflow',
+           'start_date': datetime(2023, 1, 1),
+           'retries': 1,
+       }
+   
+       dag = DAG('timescale_dag', default_args=default_args, schedule_interval='@daily')
+   
+       insert_task = PythonOperator(
+           task_id='insert_data',
+           python_callable=insert_data_to_timescale,
+           dag=dag,
+       )
+       ```
+      This DAG uses the `company` table created in [Create regular PostgreSQL tables for relational data][create-a-table-in-timescale].
+
+   1.  In your browser, refresh the [Airflow UI][Airflow_UI].
+   1.  In `Search DAGS`, type `timescale_dag` and press ENTER.  
+   1.  Press the play icon and trigger the DAG:
+       ![daily eth volume of assets](https://assets.timescale.com/docs/images/integrations-apache-airflow.png)
+1. **Verify that the data appears in $CLOUD_LONG** 
+
+   1. In [Timescale Console][console], navigate to your service and click `SQL editor`. 
+   1. Run a query to view your data. For example: `SELECT symbol, name FROM company;`. 
+
+      You see the new rows inserted in the table.
+
+</Procedure>
+
+You have successfully integrated Apache Airflow with $CLOUD_LONG and created a data pipeline.
+
+
+[create-a-table-in-timescale]: /getting-started/:currentVersion:/tables-hypertables/#create-regular-postgresql-tables-for-relational-data
+[install-apache-airflow]: https://airflow.apache.org/docs/apache-airflow/stable/start.html
+[install-python-pip]: https://docs.python.org/3/using/index.html
+[console]: https://console.cloud.timescale.com/
+[create-service]: /getting-started/:currentVersion:/services/
+[enable-timescaledb]: /self-hosted/:currentVersion:/install/
+[connection-info]: /use-timescale/:currentVersion:/integrations/find-connection-details/
+[Airflow-DAG]: https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html#dags
+[Airflow-Task]:https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/tasks.html
+[Airflow_UI]: localhost:8080

use-timescale/integrations/index.md

@@ -41,6 +41,15 @@ Some of the most in-demand integrations for $CLOUD_LONG are listed below, with l
 |:---------------------------:|-----------------------------------------------------------------------------------------------------------------------------|
 | [Terraform][terraform]      | An infrastructure-as-code tool that enables you to safely and predictably provision and manage infrastructure in any cloud. |
 
+
+## Data engineering and extract, transform, load
+
+|               Name               | Description                                              |
+|:--------------------------------:|----------------------------------------------------------|
+| [Apache Airflow][apache-airflow] | Programmatically author, schedule, and monitor workflows. |
+
+
+
 [psql]: /use-timescale/:currentVersion:/integrations/psql/
 [qstudio]: /use-timescale/:currentVersion:/integrations/qstudio/
 [dbeaver]: /use-timescale/:currentVersion:/integrations/dbeaver/
@@ -49,4 +58,5 @@ Some of the most in-demand integrations for $CLOUD_LONG are listed below, with l
 [grafana]: /use-timescale/:currentVersion:/integrations/grafana/
 [tableau]: /use-timescale/:currentVersion:/integrations/tableau/
 [terraform]: /use-timescale/:currentVersion:/integrations/terraform
+[apache-airflow]: /use-timescale/:currentVersion:/integrations/apache-airflow
 [postgresql-integrations]: https://slashdot.org/software/p/PostgreSQL/integrations/

use-timescale/page-index/page-index.js

@@ -796,6 +796,11 @@ module.exports = [
             href: "find-connection-details",
             excerpt: "Learn about connecting to your Timescale database",
           },
+          {
+            title: "Apache Airflow",
+            href: "apache-airflow",
+            excerpt: "Integrate Apache Airflow with Timescale Cloud",
+          },
           {
             title: "Azure Data Studio",
             href: "azure-data-studio",