IBM watsonx.data is underpinned by a resilient infrastructure established on Red Hat OpenShift. This framework enables you to seamlessly implement watsonx.data in any cloud or on-premises settings, delivering unparalleled adaptability and flexibility.
To provide a clearer representation of the technology stacks, we can visualize it as follows:
Software Layer: Cloud Pak for Data (Data Fabric), watsonx.data (Data Lakehouse)
Hybrid cloud platform Layer: Red Hat Openshift
Infrastructure Layer: IBM Storage Fusion HCI
Deploying IBM Watsonx.data on-premises is easier than ever, thanks to the seamless integration of the IBM Storage Fusion HCI System and IBM Storage Ceph. Together, they provide everything you need for your standalone data lakehouse infrastructure.
Why?
IBM Storage Fusion HCI System is a hosting platform for watsonx and it provides the following capabilities:
- Data sharing and self-service access.
- Data caching to accelerate IBM watsonx.data performance.
- Local S3 object store.
- IBM Storage Ceph provides an external S3 object store for IBM watsonx.data. This S3 object store can be the main S3 object store for IBM watsonx.data, or alongside S3 object store with other on-premise or public cloud object stores.
IBM Storage Fusion offers a seamlessly integrated, ready-to-use platform for operating and managing all on-premises Red Hat OpenShift applications. You may find more information about Storage Fusion in IBM product site here.
In this post, I'm providing a high level tutorial on accessing watsonx.data from the on-premise deployment of Cloud Pak for Data software. The tutorial includes actual screenshots of the Storage Fusion hardware that was physically deployed in our client's site. Upon logging into the Storage Fusion console, you will see this user-friendly interface:
Within the application tab, you can view specific details related to your applications, including instance, operator, or manager information. Critical details such as storage capacity and usage, backup status, success rate, and policy are also accessible.
To access the Red Hat OpenShift console, navigate to Infrastructure > Dashboard and initiate the Red Hat OpenShift Console.
The Red Hat OpenShift console will become visible as follows. To reach the Cloud Pak for Data console, go to Networking > Routes. Locate your Cloud Pak for Data route named 'cpd' and its corresponding 'location.' Access your Cloud Pak for Data instance console by clicking on the specified location.
In both SaaS and software deployment flavors, watsonx.data can be utilized as a cartridge in IBM Cloud Pak for Data. You can think of a cartridge as a modular component or service that can be added to Cloud Pak for Data. Adding watsonx.data as a cartridge in Cloud Pak for Data means that you are enriching your data sources, transforming your silo traditional data warehouse or data lake into a next generation data lakehouse.
When you successfully log in into Cloud Pak for Data console, you will see this. To access your watsonx.data instance, navigate to Services > Instnaces.
On the Instances page, you'll come across a comprehensive list of all your instances. In this demo, we've only set up the data lakehouse (watsonx.data) cartridge so far. Did you know you can build a complete data fabric by adding more data cartridges that specifically suit your organization's requirements? Feel free to explore more cartridges for Cloud Pak for Data here.
From here, click the 3-dots button and click 'Open'.
Upon successful login, you'll be greeted by your Watsonx.data console.
Congratulations!
You can now begin linking your data sources within your next-generation data lakehouse and scale your AI workloads across all your data.
In my next blog post, I'll be giving you a sneak peek into the watsonx.data capability, demonstrating how it's set to transform the way you view your data. Say goodbye to data silos and messy data swamps—with watsonx.data, you can expect to unlock more value from your data. This enables you to build a more sophisticated AI, trusted data through data governance, storage optimization, and cost savings.
Muz
Ecosystem Technical Enablement Specialist | Data & AI
IBM APAC Ecosystem Technical Enablement Team
#watsonx.data