Plane-NATS

ADS-B Flight Tracking w/ NATS

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Running the server

Standalone

Modify server/cluster-config.json to match your environment

• Adjust cluster.routes IP addresses
• Set the password for cluster.authorization.password
• Set desired client port under listen
• Adjust jetstream values as desired

On each server node (perhaps in Tmux)

• export TOKEN=<your token>
• ./start-server.sh

Using Kubernetes

In a terminal with kubectl and helm setup to connect to your k8s controller

• cd to the server directory
• export TOKEN=<your token>
• ./k8s[-minikube]-startup.sh

Note the client connection URL printed at the end, the port and host may vary (but the port SHOULD be 30303 unless running under minikube)

Running the client

Ensure you have the required python libraries

pip install -r requirements.txt

Set the token and connection environment variables

• export TOKEN=<your token>
• export NATS_HOST="nats://$TOKEN@<host>:<port>"

Run the client in the client-rtl directory

python client.py [-f PLAYBACKFILE]

Running the aircraft annotator

Follow the instructions in aircraft-annotator/README.md

Viewing live data

nats -s nats://$TOKEN@$NATS_HOST sub ">"

Spinning up all components locally with an all-in-one docker-compose

Alternatively, we could spin up all components locally using docker-compose.

First, follow the instructions in aircraft-annotator/README.md to download the plane data to aircraft-annotator/annotator-data/. This is necessary to build the Docker image for aircraft-annotator.

Build containers locally:

docker-compose build

Spin up all components in the background:

export TOKEN=mysecrettoken
docker-compose up -d

View live data:

docker logs -f adsb-nats-nats-box-1

Check backend API healthiness:

./elastic/backend/heartbeat.sh

One could manage the Elasticsearch data with Kibana at http://localhost:5601.