In this blog, we will look at how we can use Apama running on the Raspberry Pi to act as a “Thin Edge” device, and integrate it with Cumulocity IoT Cloud.
A “Thin Edge” platform is designed to handle a potentially large amount of data generated by sensors/devices, perform additional analytics on that data, and then communicate the results (e.g. calculated aggregate values, alarms, etc.) back to a “Thick Edge”/Cloud deployment. … Read More
Apama ships pre-built Docker images via several public stores, including Docker Store and Amazon Marketplace. These are based upon CentOS 7 base images. Some users may want to use a different base OS, for size reasons, support, or access to more recent compilers. Apama supports a wide selection of Linux distribution on-premise, but by default only ships one version of Docker images.
However, we do have a Docker build posted on Github which will take official Apama base images and change them to use a different base OS.… Read More
We introduced Python plug-ins for EPL in this post. The full community installation provides a Python installation, but users of the community core package will need to provide their own. Today we’re going to explore how to do this on various common operating systems.
Configuring Apama to use an external Python
By default Apama will look inside the installation to locate a copy of the Python library when loading Python plug-ins.… Read More
In Apama 10.3 we released integration for Apama with the popular Prometheus monitoring framework. These metrics can then be easily visualized using tools such as Grafana. Apama has had the capability to be monitored via HTTP REST interfaces on Apama correlators for a number of releases now. With Apama 10.3 we added REST endpoints to the correlator that align with the specification used by Prometheus. All of the metrics exposed are of type Counter or Gauge.… Read More
Machine learning is becoming ever more useful in data processing, and with Apama’s new Python plug-in capability it is now even easier to use this from within EPL. There are various machine learning libraries available for use, such as TensorFlow and scikit-learn. We’ve chosen to create this demo using scikit-learn, as an example of outlier detection using this library already exists. We’ll be basing this demo on the example (found here).… Read More
There’s a new Docker image in the Docker Store for Software AG’s 10.3 release called Apama Builder. It differs from the Apama Correlator image in that it can be used to build Apama projects into new images via multi-stage builds. In this blog we will explore how leveraging the Apama Builder along with other common tools, we can easily create an Apama application in a container that is self-testing, self-deploying, and subject to continuous integration.… Read More