---
title: "Astronomer"
canonical: "https://docs.vaultspeed.com/space/VPD/3038937120/Astronomer"
format: markdown
---
Astronomer ([https://www.astronomer.io/](https://www.astronomer.io/) ) is a SAAS solution for Apache Airflow, it allows you to easily set up, monitor, and scale Airflow environments.

This document describes how you can use Astronomer to set up an Airflow environment and run the FMC code generated by VaultSpeed.

Follow the getting started guide [https://www.astronomer.io/docs/cloud/stable/get-started/quickstart/](https://www.astronomer.io/docs/cloud/stable/get-started/quickstart/)  until the Develop Locally section.

Download the FMC plugin from VaultSpeed and put it into the plugins directory under the project directory you created during the initialization.

Generate FMC code in VaultSpeed and extract them into the dags folder (optionally remove the `example-dag.py` file).

Download the JDBC Driver needed to connect to your sources and target and copy it into the dags folder.

edit the Dockerfile:

```
FROM astronomerinc/ap-airflow:1.10.12-1-buster-onbuild

RUN mkdir -p /usr/share/man/man1
ENV JAVA_HOME /usr/lib/jvm/java-11-openjdk-amd64/
ENV CLASSPATH /usr/local/airflow/dags/jdbc_driver1.jar;/usr/local/airflow/dags/jdbc_driver2.jar
```

change the JDBC driver to the one you need, if you need multiple (e.g. for sources), add them after each other, separated by “;”

edit packages.txt:

```
default-jdk
```

edit requirements.txt:

```
jaydebeapi>=1.1.1
croniter>=0.3
snowflake-connector-python  # only needed when using Snowflake source/target
confluent-kafka[avro] # only needed when using Kafka source
google-api-python-client # only needed when using BigQuery source/target
pandas-gbq # only needed when using BigQuery source/target
```