FAQs
Frequently Asked Questions
Dive into the following questions to gain insights into the powerful features that Joule offers and how it can accelerate your application development journey.
What can you build in Joule?
You can build event-driven applications, custom logic, analytics and ML inferencing in Joule. Joule's makes it easy to connect to streaming data and S3 data stores, build analytical business software, trigger best-next-actions and share insights to business users — all on one platform
What do I need to start?
Pull down the getting started project and follow the tutorials once you have dropped your contact details vai the contact page.
Can I build my own components?
Yes! Joule ships with a SDK to enable developers to build advanced analytics, data connectors and sinks, and custom stream processors.
Does Joule support machine learning?
In short yes. Online ML model support is provided using the openscoring JPMML library. Supported models include Random Forest, XGBoost, K-Means, NN, regression, Bayesian etc .
How can i deploy Joule?
Joule has a flexible deployment model based upon containers and raw binary distribution. A single Joule process can support many use cases dependent upon complexity. Joule can be scaled as a cluster of joules executing the same use cases that leverage parallel event processing.
Can Joule run on a Raspberry PI?
Yes, yes and hell yes. Download one of the example use case project or use the project template to get started.
Why call it Joule?
A Joule is a unit of work or energy which is reflective on how the platform was envisioned and developed. A Joule process can either execute part of or complete use case depending upon complexity thus addressing multiple non-functional requirements while bringing simplicity to the solution.
Who develops Joule?
Joule is maintained by Lyndon Adams who has a extensive background in event based stream processing using distributed architectures. There is an open welcome invitation for collaborators to get involved with the project.