We were able to save significant time and effort by using the Splunk Add-on Builder. CSV is particularly efficient as it minimises the raw event size and Splunk can easily learn the context of the dataset. ![]() ![]() To intercept and decode the UDP traffic, we implemented a simple Splunk modular input to listen on a socket, unpack the char array, reformat the data as CSV, and write it to Splunk via the Python SDK. Splunk as a machine data platform is well equipped to take advantage of the plethora of data on offer, thus providing the basis for an exciting new analytics project.Īny data can be brought into Splunk, but it needs to be in a textual, human readable format for us to comprehend it. Each UDP packet sent includes a char array containing the telemetry data in binary format. The game can be configured to broadcast real-time telemetry data every tenth of a second - equivalent to that of a real-world F1 car - to the local network subnet, or to send UDP traffic to a specific host and port. F1 2016 introduced the feature to expose such metrics via UDP to external devices such as D-BOX, motion platforms, steering wheels and LED devices. Racing simulators have evolved considerably in recent years, adding real-world variables such as fuel usage, damage, tyre properties, suspension settings and more. After discovering telemetry data could be sent via UDP to third party applications, Dave had embarked on a personal project to consume and analyse this data in Splunk. Dave, a keen Formula One enthusiast, had identified a new capability in the F1 2016 PS4 game. ![]() The suggestion of Formula One racing simulators came from a conversation with an exemplary individual who I will refer to as Dave. When an opportunity to demonstrate Splunk to a prominent Formula One team came along, it really motivated us to search for a relevant data set to tailor the value of Splunk. Here at Splunk, we are always on the lookout for new and exciting sources of data to get our hands on.
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