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This video takes the advanced app you built in Part 2 and brings it into the world of containers. First you'll install the tooling you need for Docker and Kubernetes. Then you'll create a Docker image from your app and a Kubernetes cluster. From there, it's time to deploy and run your app. By the end of the video your code will be live on the web, running in a Docker container in a Kubernetes cluster in the IBM Cloud.

This video builds on the app you created in part 1, actually tying a web app to a NoSQL database hosted in the IBM Cloud. You'll run the application locally on your machine, then you'll deploy it to the cloud. All the code is available online, so all you have to do is follow along.

A look at the latest features of the IBM Cloud platform. Follow along with this video and you'll build and deploy an app, create a continuous delivery pipeline for it, and add a NoSQL database. All without writing a line of code!

Learn more about high performance computing solutions on IBM Cloud at https://www.ibm.com/cloud-computing/solutions/high-performance-computing-cloud/
Ah, the power of partnerships! IBM Cloud, together with MapD and Bitfusion, were able to scale up to 64 Tesla™ K80 GPUs across 32 servers to filter, query and aggregate a 40-billion-row dataset in just 271 milliseconds. That's a mind-blowing 147 billion rows per SECOND.

IBM Cloud Video is piloting new experimental cognitive technology that can automate the process of segmenting video into scenes based on content. This demonstration uses footage from The Weather Channel’s “Grid Breakers” online series to show how the technology can create scenes by analyzing video.

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