Merge pull request #5 from ddebrunner/rel1

Switch to consistent use of v0.3 
tree: 15815b61b6b7f66610dcd688b0df63ed367faf30
  1. .gitignore
  5. analytics/
  6. android/
  7. api/
  8. build.xml
  9. common-build.xml
  10. connectors/
  11. console/
  12. ext/
  13. licences/
  14. platform/
  15. providers/
  16. quarks_overview.html
  17. runtime/
  18. samples/
  19. scripts/
  20. spi/
  21. test/
  22. utils/

Welcome to Quarks!

Quarks is an open source programming model and runtime for edge devices that enables you to analyze data and events at the device.

We want to build a community around Quarks for analytics at the edge, so welcome contributions to any aspect of Quarks including:

  • Feedback from use in IoT and other device environemnts.
  • Support for more device environments
  • Additional connectors to edge sensors or new messgae hibs
  • Analytics to be executed at the edge
  • Sample applications
  • Documentation
  • Testing
  • Bug fixing
  • ...

Please Get Involved!

Quarks is released under the Apache License Version 2.0


Devices and sensors are everywhere. And more are coming online every day. You need a way to analyze all of the data coming from your devices, but it can be expensive to transmit all of the data from a sensor to your central analytics engine.

Quarks is an open source programming model and runtime for edge devices that enables you to analyze data and events at the device. When you analyze on the edge, you can:

  • Reduce the amount of data that you transmit to your analytics server

  • Reduce the amount of data that you store

A Quarks application uses analytics to determine when data needs to be sent to a back-end system for further analysis, action, or storage. For example, you can use Quarks to determine whether a system is running outside of normal parameters, such as an engine that is running too hot.

If the system is running normally, you don’t need to send this data to your back-end system; it’s an added cost and an additional load on your system to process and store. However, if Quarks detects an issue, you can transmit that data to your back-end system to determine why the issue is occurring or how to resolve the issue.

Quarks enables you to shift from a continuous flow of trivial data to an intermittent trickle of meaningful data. This is especially important when the cost of communication is high, such as when using a cellular network to transmit data, or when bandwidth is limited.

The following use cases describe the primary situations in which you would use Quarks:

  • Internet of Things (IoT): Analyze data on distributed edge devices and mobile devices to:
    • Reduce the cost of transmitting data
    • Provide local feedback at the devices
  • Embedded in an application server instance: Analyze application server error logs in real time without impacting network traffic
  • Server rooms and machine rooms: Analyze machine health in real time without impacting network traffic or when bandwidth is limited

Edge devices and back-end systems

You can send data from a Quarks application to your back-end system when you need to perform analysis that cannot be performed on the edge device, such as:

  • Running a complex analytic algorithm that requires more resources, such as CPU or memory, than are available on the edge device.
  • Maintaining large amounts of state information about a device, such as several hours worth of state information for a patient’s medical device.
  • Correlating data from the device with data from other sources, such as:
    • Weather data
    • Social media data
    • Data of record, such as a patient’s medical history or trucking manifests
    • Data from other devices

Quarks communicates with your back-end systems through the following message hubs:

  • MQTT – The messaging standard for IoT
  • IBM Watson IoT Platform – A cloud-based services that provides a device model on top of MQTT
  • Apache Kafka – An enterprise-level message bus
  • Custom message hubs

Your back-end systems can also use analytics to interact with and control edge devices. For example:

  • A traffic alert system can send an alert to vehicles that are heading towards an area where an accident occurred
  • A vehicle monitoring system can reduce the maximum engine revs to reduce the chance of failure before the next scheduled service if it detects patterns that indicate a potential problem