IBM this week extended the reach of the IBM Cloud Private (ICP) for Data platform to include the Red Hat OpenShift platform based on Kubernetes. ICP also aligns with Red Hat and Hortonworks on the Open Hybrid Architecture Initiative for building hybrid big data applications on the Red Hat OpenShift platform.
In addition, IBM today announced it has extended ICP for Data to enable analytics queries to access data anywhere, by leveraging container-based technologies.
ICP for Data combines analytics and data management platform under of common set of graphical interfaces that runs on top of Kubernetes. Built on IBM Cloud Private, ICP for Data includes an enterprise metadata catalog along with capabilities such as data federation/virtualization, data warehousing, data integration, data science/machine learning and tools for building embedded dashboard. IBM is making available a free trial version of the platform, dubbed ICP for Data Experiences.
This latest initiative extends an existing alliance between Red Hat and IBM involving the deployment of containerized middleware from IBM on the Red Hat OpenShift platform. Rob Thomas, general manager of IBM Analytics, says via these partnerships IBM is striving to make it easier to distribute analytics applications across an extended enterprise.
The goal, he says, is to make it possible to launch SQL queries against data sources spanning the cloud to the network edge. By leveraging Kubernetes and containers, it becomes much easier to deploy analytics applications alongside sources of data versus having to move data into a central repository, he notes.
In the case of the Open Hybrid Architecture Initiative, that also means collaborating on a joint effort to optimize Hortonworks Data Platform, Hortonworks DataFlow, Hortonworks DataPlane and IBM Cloud Private for Data for deployment on Red Hat OpenShift. IBM and Hortonworks will extend those efforts to integrate services offered provided via Hortonworks DataPlane with the IBM Cloud Private for Data platform.
IBM is pursuing a similar approach to applying machine learning algorithms, sponsoring StackExchange AI, a new community on the Stack Overflow Network. Stack Overflow facilitates conversations and sharing among more than 50 million developers a month. The IBM Watson platform already makes extensive use of containers and Kubernetes to expose deep learning algorithms.
In effect, Kubernetes is becoming a de facto standard for delivering a wide variety of application payloads. Within that context, it’s increasingly apparent that microservices based on containers and Kubernetes will play a critical role in distributing and democratizing AI-infused analytics. In fact, just about every enterprise application soon will either have AI functions embedded in it or will be able to invoke an analytics application infused with AI via REST application programming interfaces. Many organizations are now engaged in a race to leverage AI before rivals can employ those capabilities, which means it might be difficult to sustain a competitive advantage using AI. But it’s clear that any application that is unable to take advantage of AI soon will be rendered obsolete.