In this article you will understand how to deploy the Flight Blender backend / data processsing engine. If you need a front end / display you will need to install Flight Spotlight (which communicates with Blender via the API) and finally for production we also recommend that you use Flight Passport authorization server for endpoint security.
This guide is mainly for technical engineers within organizations who are interested in testing and standing up UTM capability. It is recommended that you are familiar with basic Docker, OAUTH / Bearer Tokens. The server is writted in Django / Python if you want to use / run the in built in data. However, since it is all API based, you can use any tools / languages that you are familar with to communicate with the server.
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This quick start is for local development / testing only, for a more detailed “Production” instance see the currently under development Production Deployment document. The main difference between local development and production is that for production you will need a full fledged OAUTH server like Flight Passport or others. For this quickstart we will use the simple authentication / token generation mechanism that requires not additional server setup. In this quickstart, we will:
For this quick start we will use the sample .env file. You can copy the file to create a new .env file, we will go over the details of the file below.
|Variable Key||Data Type||Description|
|SECRET_KEY||string||This is used in Django, it is recommended that you use a long SECRET Key as string here|
|IS_DEBUG||integer||Set this as 0 if you are using it locally|
|ALLOWED_HOSTS||string||This is used in Django, it is recommended that if you are not using IS_DEBUG above, then this needs to be set as a the domain name, if you are using IS_DEBUG above, then the system automatically allows all hosts|
|REDIS_HOST||string||Blender uses Redis as the backend, you can use localhost if you are running redis locally|
|REDIS_PORT||integer||Normally Redis runs at port 6379, you can set it here, if you dont setup the REDIS Host and Port, Blender will use the default values|
|REDI_PASSWORD||string||In production the Redis instance is password protected, set the password here, see redis.conf for more information|
|REDIS_BROKER_URL||string||Blender has background jobs controlled via Redies, you can setup the Broker URL here|
|HEARTBEAT_RATE_SECS||integer||Generally set it to 1 or 2 seconds, this is used when querying data externally to other USSPs|
|AMQP_URL||string||A full connection url to a AMQP server, when this is set, messages related to your operations are sent to it, your clients can subscribe to them.|
|DSS_SELF_AUDIENCE||string||This is the domain name of the lender instance you can set it as localhost or development / testing|
|AUTH_DSS_CLIENT_ID||string||(optional) Sometimes authorities will provide special tokens for accessing the DSS, if you are using it locally via
|AUTH_DSS_CLIENT_SECRET||string||(optional) Similar to above sometimes authorities provide|
|DSS_BASE_URL||string||Set the URL for DSS if you are using it it can be something like
|POSTGRES_USER||string||Set the user for the Blender Database|
|POSTGRES_PASSWORD||string||Set a strong password for accessing PG in Docker|
|POSTGRES_DB||string||You can name a appropriate name, see the sample file|
|POSTGRES_HOST||string||You can name a appropriate name, see the sample file|
|PGDATA||string||This is where the data is stored, you can use
Once you have created and saved the .env file you can then use the docker-compose.yaml file to start the instance. Just run
docker compose up and a running instance of Flight Blender will be available.
You can run Blender by running
docker compose up and then go to
http://localhost:8000, you should see the Blender Logo and a link to the API and Ping documentation. Congratulations 🎉 we now have a running version of the system!
Next we can now upload flight data. Blender has a extensive API and you can review it, any data uploaded or downloaded is done via the API. The importers directory has a set of scripts that help you with uploading data / flight tracks. For this quickstart, we will use the import_flight_json_blender_local.py script here, you can see the rest of the scripts there to understand how it works.
You will have to setup a environment like Anaconda or similar software package and install dependencies via something like
pip install -r requirements.txt then you can run the import script via
python import_flight_json_blender_local.py this will send some observations to the
/set_air_traffic POST endpoint. This script will send a observation and then wait for 10 seconds and send another one. All of this requires Python.
While the script is running you can install Postman and which should help us query ther API. You can import the Postman Collection prior. You will also need a “NoAuth” Bearer JWT token that you can generate by using the get_access_token.py script. You should have a scope of
blender.read and a audience of
testflight.flightblender.com. We will use this token to go to the Postman collection > Flight Feed Operations > Get airtraffic observations. You should be able to see output of the flight feed as a response!