As the Internet of Things (IoT) takes hold, the volume and variety of fast-moving data are constantly increasing. The need to analyze this data close to the source and make intelligent decisions fast helped to promote the rise of IoT. Companies are collecting data from sensors and processing it on small edge devices as it flows into the larger system. With SAS Event Stream Processing (ESP), you can analyze this data as the streaming happens and act accordingly with predefined logic. For example, the process could generate immediate alerts on abnormal conditions or just transmit the relevant information.
Have you been wanting to see what SAS Event Stream Processing (ESP) can do to improve your ability to make intelligent decisions to enhance your business performance? If you’re a data scientist, you can harness the power of streaming analytics and machine learning using the environment of your choice, so you can capture more precise insights at the edge and make real-time intelligent decisions in the cloud.
A free 30-day trial of the latest version of ESP is now available in the SAS® Analytics Cloud. This trial environment allows you to interact with an ESP server using Python commands from a Jupyter notebook. You can create your own processes from scratch or use one of the seven pre-populated examples highlighting the use of the ESP Python interface. This means no downloads, no installation, no configuration….just sign up and start experiencing SAS® Event Stream Processing for free on the SAS® Analytics Cloud.
The ESP trial environment allows you to execute Python commands that interact with our ESP server. This uses an ESP module called ESPPy with APIs that instruct the ESP server to execute a specific task, such as defining a streaming project, loading it onto the ESP server, publishing data to the model, or using the output from one of the steps of the project to populate a dashboard. You can either review existing demo examples or create your own using the Python language and a library of APIs without having to install the software on your premises. You can also upload your own data for testing and experimenting. For the trial environment, we recommend datasets that are not too big given current environment storage constraints.
In our next release, we will add even more functionality including other interfaces like our SAS ESP Studio providing a graphic user interface to develop and test the model deployed on the server.
Each ESP trial is considered a separate environment that is generated when you request it. After requesting the trial, you will receive an email with instructions of how to connect to it and become the administrator of this environment. You can then invite additional users to share this environment. Sharing allows your colleagues to use notebook and data files saved in common folders.
SAS Analytics Cloud uses a Kubernetes-based architecture and each trial request becomes an independent tenant of the Cloud. Each tenant may have one or more pods, one for each user. Each pod is a separate environment containing a set of containers with software available in the trial already installed and configured.
The containers in the pod provide the needed components for the trial environment:
Each pod has access to several file storage folders. These folders contain read-only files with the demo examples (/demo), shared files for collaboration among users of the same tenant (/shared), and private files for each user (/my_code and /my_data).
This diagram shows the high-level architecture of a tenant of the ESP trial environment.
As shown in the diagram, the environment has four containers in each pod communicating with each other using predefined ports, and all communication to the external world is through the standard port 443 to ensure no conflicts with firewalls on the user side -- providing a secure environment.
Request your free trial environment today – it’s as easy as visiting www.sas.com/esp and clicking the “Get Free Trial” button on the upper right-hand corner of the page. Please give it a try and let me know what you think at email@example.com.
SAS Event Stream Processing on SAS Analytics Cloud - my journey -- SAS Users blog post by @joeFurbee
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