At IBM Think 2018, Jason McGee showed how to modernize a decade-old Java web application called JPetStore into an AI-powered chatbot using nothing more than Docker, Kubernetes, and a few services from IBM Cloud. As a former Java developer who’s new to Kubernetes, I found it was not only a great introduction to emerging cloud technology but also a nostalgic look back at how far we’ve come.
While demos are a great overview, developers – myself included – will want to know more and get hands-on. To that end, we’ve obtained the demo’s code, cleaned it up a bit, and posted a tutorial on GitHub. We’ve also recreated the demo as a quick instructional video on YouTube with a few added enhancements.
Both the code and video will take you through the full modernization story. You’ll start by converting the tiers of the legacy J2EE stack into Docker containers. Then you’ll run and manage those containers using the IBM Cloud Kubernetes service. And finally, you’ll enhance the application with a chatbot microservice that uses Watson Visual Recognition and text messaging to create a new sales channel for the store.
In this tutorial, we will install Splunk Connect for Kubernetes into an existing Splunk instance. Splunk Connect for Kubernetes provides a way to import and search your Kubernetes logging, object, and metrics data in Splunk.
If you’re moving your data over to IBM Cloud Databases for Redis, you’ll need to take some steps to successfully migrate all of your data. We’ve got you covered. In this post, we’ll show you a quick way to start migrating your data across to Databases for Redis, whether your database is on-premise or in the cloud.