Monitor and analyze real-time IoT data with a distributed cloud

Summary

In this code pattern, you create an application to monitor automated logs and alerts of real-time Internet of Things (IoT) data with a distributed cloud. You use IBM Cloud Satellite to create a Satellite location and attach hosts from on-premises data centers and edge networks. You then visualize and analyze the incoming IoT data by using IBM Cloud Pak for Data.

Description

The following scenario is considered for this code pattern. In a chemical research plant, the containers containing various chemicals under study are required to be maintained within a certain threshold. In our case, the minimum temperature threshold is 27°F and the maximum threshold is 30°F. Correct and highly accurate temperature control is very important. If the container temperatures are too low or too high, the consequences could be fatal. Hence, a swift action must be taken when a container temperature crosses the defined threshold. If we were to build a solution for this use case on a public cloud, latency could be a real problem.

In this code pattern, you build a live dashboard view of IoT temperature data from the chemical containers located on premises. You also build an application that monitors automated logs and alerts of the real-time IoT data. You use IBM Cloud Satellite distributed cloud capabilities to create a Satellite location and attach hosts from the on-prem data centers and edge networks. You then create a Red Hat OpenShift cluster that resides on a Satellite location and install IBM Cloud Pak for Data on top of the cluster to visualize and analyze the IoT data.

Flow

Architecture flow diagram

  1. Create an IBM Cloud Satellite location and assign hosts.
  2. Create the Red Hat OpenShift on IBM Cloud cluster that will reside in your Satellite location.
  3. Deploy the IoT simulator application on premises.
  4. Install IBM Cloud Pak for Data on the OpenShift cluster.
  5. Build a streams flow on IBM Cloud Pak for Data for the incoming IoT data.
  6. Visualize incoming IoT data by using the IBM Streams analytics service on IBM Cloud Pak for Data.
  7. Deploy the IoT data monitoring and alerting application on the OpenShift cluster.
  8. Consume the IoT data from the simulator in real time.
  9. Monitor the data in real time by using the dashboard UI.

Instructions

The detailed steps for this code pattern are available in the README.md file. The steps show you how to:

  1. Create an IBM Cloud Satellite location.
  2. Attach hosts from your on-premises data centers and edge networks.
  3. Assign hosts to the Satellite location control plane.
  4. Create the OpenShift cluster that will reside in your Satellite location.
  5. Install IBM Cloud Pak for Data on the OpenShift cluster.
  6. Deploy the IoT simulator application.
  7. Build a streams flow and visualize incoming IoT data by using the IBM Streams service on IBM Cloud Pak for Data.
  8. Deploy the IoT data monitoring and alerting application on the OpenShift cluster.