I'll try to make this as short as possible using all the acronyms!
Alpine Linux on a Raspberry Pi with LTE/3G, GNSS, BT and Wifi.
Boot and request Wireguard enrollment over TLS (human acknowledges in Slack to verify inventory), configure WG tunnel, start gRPC producer.
Hop the 2.4 Ghz spectrum at 250 Hz, gopacket sniffs MGT frames for probes and beacons, collects SSID, MAC, RSSI and a ton of other really neat data from the GPS and system itself (temp, procs, load, mem, modem signal strength, carrier, nearby bluetooth peripherals).
Push these events in real-time to gRPC consumer over Wireguard. The ETL aggregates and stores summary data in NoSQL, the raw request is marshalled to JSON and stored in ElasticSearch (in the event of a disaster; also it's fun to use Kibana to find new interesting metrics to report on the customer dashboard).
It's purpose is to determine how many humans are within potential viewing distance of a moving object which may or may not have some form of communique - these devices are installed in vehicles.
Disclaimer: This is a weekend-project/work-in-progress.
Configuring LDAP can be a daunting task, this is a drop-in LDAP management tool (and server) I built to easily add / remove users from my LDAP directory.
I've tested it with Gitlab, Redmine, Apache mod_authz and OwnCloud/NextCloud with great success. It will most likely work for any basic auth you may require.
Credit for UI goes to @creativetimofficial on github.
Alpine Linux on a Raspberry Pi with LTE/3G, GNSS, BT and Wifi.
Boot and request Wireguard enrollment over TLS (human acknowledges in Slack to verify inventory), configure WG tunnel, start gRPC producer.
Hop the 2.4 Ghz spectrum at 250 Hz, gopacket sniffs MGT frames for probes and beacons, collects SSID, MAC, RSSI and a ton of other really neat data from the GPS and system itself (temp, procs, load, mem, modem signal strength, carrier, nearby bluetooth peripherals).
Push these events in real-time to gRPC consumer over Wireguard. The ETL aggregates and stores summary data in NoSQL, the raw request is marshalled to JSON and stored in ElasticSearch (in the event of a disaster; also it's fun to use Kibana to find new interesting metrics to report on the customer dashboard).
It's purpose is to determine how many humans are within potential viewing distance of a moving object which may or may not have some form of communique - these devices are installed in vehicles.