Every day 2.5 quintillion bytes of big data is created - this data comes from externally sourced websites, blog posts, tweets, sensors of various types and public data initiatives such as the human genome project as well as audio and video recordings from smart devices/apps and the Internet of Things (IoT). Many businesses are learning how to look beyond just data volume (storage requirements), velocity (port bandwidth) and variety (voice, video and data) of this data; they are learning how to use the data to make intelligent business decisions.
Today, every organization, across geographies and industries can innovate digitally, creating more customer value and differentiation while helping to level the competitive playing field. The ability to capture and analyze big data and apply context-based visibility and control into actionable information is what creates an intelligent enterprise. It entails using data to get real-time insights across the lines of business which can then drive improved operations, innovation, new areas of growth and deliver enhanced customer and end user experiences
Here are just a few examples of organizations taking advantage of these insights:
Search engines like Google managed search requests by an always-on productivity AI platform, which aims to predict what we want and suggests what we should do, based on multiple parameters including location, type of device, user profile and other variables.
Facebook’s underlying technologies are always learning about our social likes and dislikes, friendships, associated businesses and more, providing an algorithm that suggests who we should befriend or what organizations we should join.
Venues that offer “free WiFi” use this offering to determine how to best engage with us based on our locations, interests and associations, either for their own organization or for business partners (think of sponsors at a sporting event or advertising partners in an airport terminal).
Becoming an intelligent enterprise
The intelligent enterprise is not a product or a specific action: It’s a corporate mindset. It entails using digital competencies and processes, powered by a suite of data-driven technologies to gain a competitive advantage. The companies that fit this definition are frequently using modern open hybrid cloud technologies, along with a digital network edge of connected systems/devices and artificial intelligence (AI) and machine learning (ML) tools paired with big data analytics to distill real-time insights about operations, market conditions and customers.
To think about it algorithmically: The intelligent enterprise = open hybrid cloud technologies + digital network edge + Intelligent technologies
Size doesn’t matter in this case. An intelligent enterprise could be a large, well-established company continuously receiving real-time insights to gain an edge against similar-sized competitors on a global scale, or it could be a startup going after an established market and its competitors using intelligent technologies to enhance its offerings regardless of scale.
Red Hat and SAS: providing enterprises with an intelligence advantage across cloud environments
As companies migrate to cloud solutions for both their core and edge infrastructure, they frequently have two requirements: flexibility and openness. These characteristics offer the ability to more quickly spin up additional resources, access the popular enterprise solutions with agility, and the capacity to run workloads across cloud environments, from private to public.
Yesterday, Red Hat and SAS announced a collaboration to optimize analytical capabilities across the hybrid cloud which will enable organizations to use open hybrid cloud technologies and analytical capabilities to drive business-level intelligence.
Red Hat OpenShift, the industry’s most comprehensive enterprise Kubernetes platform, provides a more portable container and Kubernetes platform that can help customers manage their infrastructure across the hybrid cloud. OpenShift enables customers to migrate applications more seamlessly across IT footprints. It includes the world’s leading enterprise Linux platform, container runtime, networking, monitoring, container registry, authentication and authorization capabilities, all key pieces of enterprise-grade cloud-native infrastructure.
Red Hat OpenShift is available across a variety of cloud environments including AWS, Microsoft Azure, Google Cloud Platform, IBM Cloud, OpenStack and VMware, along with the flexibility to combine public and private resources for hybrid cloud deployments. It also helps organizations develop, deploy and manage existing and container-based applications more seamlessly across physical, virtual and public cloud infrastructures, including multiple public clouds.
This provides for container-based applications like SAS Viya to be deployed on a myriad of public cloud or hybrid cloud environments with the flexibility to shift or scale workloads as business needs dictate. We hear from our customers that hybrid cloud combines the necessary agility to innovate more quickly with the control of on-premises datacenters, while still enabling them to use and extend existing public cloud infrastructure investments.
With a public or hybrid cloud environment based on OpenShift, customers can have a much higher level of agility, making it easier to move between and across different types of private (bare metal vs. virtualized vs.OpenStack) and public cloud footprints. Because OpenShift is based on open source software, enterprises can also benefit from the continuous community innovation, a generally lower operational cost and less vendor lock-in.
Using SAS analytics in a Red Hat OpenShift environment, customers can more quickly realize results while still maintaining control as to where they run their analytics workloads. SAS Viya provides a modern, flexible cloud-based architecture that supports agile development and deployment of both SAS and open source AI and ML models in a single governed platform. Optimizing the cloud-native design of SAS Viya in Red Hat OpenShift gives customers an expanded choice and greater control across hybrid environments.
With Red Hat and SAS, enterprises can enjoy real intelligence in business by using their accumulated knowledge to create new knowledge—new intelligence—so that they can better respond to changes and challenges in evolving business environments.
Specifically, Red Hat OpenShift provides a host of features aimed at enabling Kubernetes clusters to more effectively run, accelerate and scale AI/ML Workloads across hybrid cloud environments. This includes features like:
AI/ML on OpenShift initiatives and OpenShift Operators for creating more predictive and AI analytics capabilities.
AI for IT operations (AIOps) to automate the identification and resolution of common information technology (IT) for the use of big data analytics, machine learning (ML) and other artificial intelligence (AI) technologies.
Device plugins for access to GPUs and other specialized hardware to applications running in containers.
Huge Pages support to enable containers with large memory requirements to run more efficiently.
Multi-network support to allow more than one network interface per container for better traffic management.
Yesterday’s announcement is an expansion of the existing collaboration between Red Hat and SAS and marks what we feel is an exciting time for our respective companies and our customers. This work will enable organizations to use open hybrid cloud technologies and analytical capabilities to become more intelligent, across all industries. Intelligence drives business transformation, and we’re pleased to be able to support these initiatives with our partners like SAS!
Ali Kafel is product marketing director, Hybrid Cloud Ecosystem at Red Hat.