Step 1 – Learn about Streams
If you are new to Streams, please take some time to learn about the Streams technology. If you already have experience with Streams, please move to the next step.
Step 2 – Learn about the Streaming Analytics Service
Please read this quick introduction to the Streaming Analytics Service.
Step 3 – Run a Sample
There are a number of sample applications you can use to learn about the Streaming Analytics service. Please run one or more of the samples below that most closely match your intended use of the Streaming Analytics service.
Deploy the stock trades starter application
This is a simple application that is ready to be deployed to the Streaming Analytics service. You do not have to write any code or install any software.
To try it, download the application file from GitHub, and then watch this video to see how to:
- Create an instance of the Streaming Analytics Service (00:22)
- Run the starter application in the service (00:56)
- See the actual data being processed by an application (02:13)
- Look at the applications logs and any data printed to stdout/stderr (03:17)
End-to-End Starter Applications
Deploy an end-to-end starter application to the cloud if you want to explore how to use Streaming Analytics in the context of a larger application that uses any of the other languages and services available in the IBM Cloud.
EventDetection Starter (compatible with V1 and V2 price plans)
The EventDetection starter application uses the SDK for Node.js runtime in the IBM Cloud. EventDetection uses the Streaming Analytics service to detect simple and complex events in a Stream of real-time weather data.
NYCTraffic Starter (compatibe with V1 price plans only)
The NYCTraffic starter application uses the Liberty for Java runtime in the IBM Cloud. NYCTraffic uses the Streaming Analytics service to analyze a real-time feed of road speeds.
Other Streams Application Samples
Run additional Streams application samples to further explore Streams apps in the cloud. Use the link below to access a wide variety of sample applications. Click on the link and search for “Bluemix” to find the samples that are can be deployed in the cloud.
Step 4 – Learn More about Developing Streams Applications for the Cloud
See the Streaming Analytics Development Guide for a comprehensive description of how to develop and deploy applications to the Streaming Analytics service. The development guide features a sample Streams application that analyzes Twitter data and step-by-step instructions for completing tasks that are part of the application development life cycle.
If you have an existing Streams application that you would like to deploy to the cloud, see Getting your SPL application ready for the cloud.
Step 5 – Learn about Integrating with other IBM Cloud Services
A variety of tutorials and resources are available to help you use the Streaming Analytics service with other IBM Cloud services.
Watson IoT / Internet of Things Platform
File-based Data Sources
The Streams ObjectStorage Toolkit can be used to integrate your Streaming Analytics application with the Object Storage service in IBM Cloud.
Step 6 – Taking Care of your Streams Application in the Cloud
If you have a Streams application running in the Streaming Analytics service, it is most likely one that runs continuously – 24 hours a day and 7 days a week. But how can you make sure that your application is running normally? See Monitoring Your Streams App in the IBM Cloud using the Streams REST API to learn how you can programmatically assess whether your app is operating normally and extract valuable metrics about its execution.