IoT Analytics Reference Architecture
for developers

Explore technical architecture examples outlining industry best practices and use cases.


ESP and Omnio Integration to bring analytics to the Edge
The project provides the tools needed to deploy SAS ESP edge container along with Omnio to run a Subspace Tracking model on streaming sensor data from a solar farm.

Key takeaways from the example: 
 • 
design, develop, and integrate SAS Event Stream Processing Edge 6.1 (ESP) and Omnio Industrial IoT solutions
 •  reference architecture for building IoT applications requiring reading sensor data from devices
 • use the data for reporting or building predictive models

>> Resources on GitHub <<

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Overview

This reference architecture walks you through the decision-making process involved in designing, developing, and integrating SAS Event Stream Processing Edge 6.1 (ESP) and Omnio Industrial IoT solution. By leveraging Omnio’s plug-and-play connectivity as a service, ESP is able to provide a wide range of analytical capabilities to your IoT solutions. Omnio's edge translation layer onboards your devices, ensuring interoperability, reporting all device data in one format, customized to your existing IoT platform.

In this use case, the ESP and Omnio integration is used to read data from various sensors installed in the solar farm located at the SAS HQ, in Cary, North Carolina. The sensor data includes inverter data, real-time weather data, and combiner boxes data. The data is then used both for building a reporting dashboard and training a Subspace tracking (SST) model to detect both hardware failures in the solar farm and slow degradation of slow panels.


SAS ESP High Availability using Kafka
Learn how to create and deploy an ESP high availability system using kafka as the message broker.

Key takeaways from the example: 
 •
examine high availability concepts and the basics of the Kafka message bus
 • deploy ESP in failover models
 • walk through an end to end example

>> Resources on GitHub <<

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Overview

There are four message buses supported for ESP failover: Tervela, Solace, RabbitMQ and Kafka. This repository will show you how to use SAS Event Stream Processing (ESP) in conjunction with a Kafka message bus to build a real time fault-tolerant application which provides analytic services.

ESP and Kafka work together to create a great high availability system with redundancy built into each part of the system. When combining these two technologies, real-time data pipelines and advanced analytics come together into a fault-tolerant, fast and scalable system.


ESP Kubernetes Guide
The complete guide to SAS Event Stream Processing with Kubernetes provides all the necessary information and guidelines with commands to set up your own Kubernetes cluster and its peripherals.

Key takeaways from the example: 
 •
introduction to container and Kubernetes architecture
 • Kubernetes cluster environment setup
 • end-to-end ESP Kubernetes (ESP-Kube) architecture
 • demo examples using ESP Operator

>> Resources on GitHub <<

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Overview

SAS Event Stream Processing 6.2 with Kubernetes is a framework for controlled and automatic deployment, management, and scaling of SAS Event Stream Processing Servers running in Docker containers across the Kubernetes cluster in a cloud environment. It provides high guarantees on availability, reliability and fault tolerance. The framework leverages features of Kubernetes for resource allocation, storage orchestration, self-monitoring and healing, and secret and configuration management.

The framework comprises of SAS Event Stream Processing Operator which allows starting, stopping, updating, deleting, and monitoring of the ESP Servers docker containers running in the Kubernetes cluster.

SAS Web Clients (SAS Event Stream Processing Studio, SAS Event Stream Processing Streamviewer and SAS Event Stream Processing Manager) also runs in the docker containers in the same cluster and allows seamless access to all the ESP Servers.

This repository provides a thorough deep dive into the SAS Event Stream Processing 6.2 Kubernetes Architecture and guidelines for users to set up their own ESP Operator framework with web clients in a Kubernetes cluster.

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