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Build your own machine learning lab!
I’m from Missouri. You’ve got to show me!
Many Missourians still live by the credo: “Don’t just tell me something, you’ve got to show me!” So, when I say something – especially what a certain technology can do – I can’t help but point you to a resource to let you see for yourself.
Get ready for an interactive demo experience
Here’s what I want you to know – and read on so I can show you!
The HPE Ezmeral Container Platform enables enterprises to accelerate artificial intelligence and machine learning; and it enables the deployment of data centric workloads and large-scale applications in the cloud, on premises, or at the edge.
Let’s get right down to it. Hewlett Packard Enterprise (HPE) has an Interactive Demo Experience (IDE) that lets you sit in the driver’s seat with HPE Ezmeral Container Platform and the HPE Ezmeral Data Fabric. Hey! Don’t skip ahead and click that link yet. Read on a bit…I have pictures.
Figure 1 - The HPE Ezmeral Container Platform Integrated Demo Experience
The IDE is really cool. You can do several things with it such as:
- Setup Kubernetes (K8s) clusters & tenants (K8s namespaces)
- Create and register K8s applications for your namespaces
- Deploy a K8s Machine Learning Lifecyle (yes, an entire AI/ML pipeline)
- Create a mirror of the volume containing all the important data in your your K8s clusters.
What is this a demo of again?
By the description of what is in the IDE, you should start to get the sense that HPE developed and released some amazing software, called HPE Ezmeral. One of those software products is the HPE Ezmeral Container Platform.
This platform is, in fact, a central control plane that helps you create and manage clusters of containerized applications utilizing fully open-source, CNCF-certified Kubernetes. You can use the WebUI or a fully automated REST interface to configure and manage your clusters with the HPE Ezmeral Container Platform.
You can even import entire clusters from your favorite public cloud. (See figure 2 below.)
Figure 2: Import a cluster from your favorite cloud.
Experience how simple it is to create a new K8s cluster and see how they are managed right alongside other clusters, even your imported clusters. This is why I say you can deploy and manage resources on-premises, in the cloud, or at the edge. From this single control plane, you are in control of it all. (See figure 3.)
Figure 3: Create your own K8s Cluster.In the demo, you can create an AI/ML pipeline using the HPE Ezmeral Container Platform. (Figure 4)
Figure 4: Create an entire AIML Pipeline from the App Store.In addition, you can also play around with the HPE Ezmeral Data Fabric that does for data what Kubernetes does for applications.
Figure 5: HPE Ezmeral Data Fabric WebUI (formerly MapR).HPE Ezmeral Data Fabric was built with distributed applications in mind and provides APIs to many common AI and ML applications such as Spark, Kafka, and SQL. It also supports multiple storage protocols and their APIs such as POSIX (NFSv3,NFSv4, FUSE), REST, K8s CSI (File & Block) and HDFS.
Enough words – the demo link please!
As promised, you should now take HPE Ezmeral for a spin. The demo is 100% online and ready for you right now. Just go to this link: http://www.hpe.com/demos/ezmeral
Have fun! You can go fully interactive, watch videos, or do a little of both. Feel free to leave a comment below and share your experience in building your machine learning lab!
For more information, visit the HPE Ezmeral Container Platform webpage.
Don
Hewlett Packard Enterprise
twitter.com/HPE_Ezmeral
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Don_Wake
Don has spent the past 20 years building, testing, marketing, and selling enterprise storage, networking, and compute solutions in the rapidly evolving information technology industry. Today he is focused on the HPE Ezmeral Container Platform. The HPE Ezmeral Container Platform is exciting to work on as it offers the ultimate toolkit to manage, deploy, execute, and monitor data-centric applications on software- and hardware-based architectures in the cloud, on premises, and at the edge.
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