Modern Data and AI application deployments are expanding through open source containers and hybrid multi-cloud support, but how can you achieve the benefits of infrastructure optimization and unified operationalization without vendor lock-in?
In this era of increasing AI/ML workloads and the need to operationalize AI, there are various options not just for where these intelligent applications can be deployed but also on how we can deploy them. Deploying and scaling AI across the enterprise is a tedious task as the 3V’s (volume, velocity, and variety) of data explode, not to forget the restricting regulations, and legacy workloads, organizations have to deal with. Additionally, enterprises are finding it difficult to manage multiple point solutions to accelerate their journey to AI, with reduce costs while improving productivity and flexibility.
Cost Savings of IBM Cloud Pak for Data on Red Hat OpenShift
Red Hat OpenShift container platform provides organizations with the choice to run on top of physical or virtual, public or private cloud, and hybrid cloud infrastructure with minimal friction providing standardization, control, and visibility. Based on a cloud-native and micro-services architecture, it allows you to focus on the AI/ML application development and lifecycle using Cloud Pak for Data, without having to bother about the infrastructure specifics on where it runs. Efficient automated container orchestration with over the air updates, rapid container lifecycle management and integrated monitoring makes it the Kubernetes foundation you’ve been waiting for. Based on Cloud Pak for Data with the underlying container orchestration platform of Red Hat OpenShift, could reduce the overall infrastructure management efforts by 65 percent to 85 percent and improve hardware utilization.
Improve ROI with IBM Cloud Pak for Data System
Pre-integrated solutions are optimized to improve productivity, drive innovation and while reducing costs and deployment risks. The Cloud Pak for Data System is one such deployment option allowing you to deploy your private cloud in a box within a few hours with pre-installed and optimized for your Data and AI needs. It offers instant pre-assembled(software) provisioning with data virtualization and has capabilities to collect, organize and analyze data. It provides a set of “Lego” building blocks (hardware) allowing customers to quickly stand up and scale a high-performance private cloud in a box for “Data and AI.”
IBM Cloud Pak for Data System is a hyper-converged inter-operable platform that provides software defined network, storage and compute to reduce complexity, increase scalability, and accelerate time to value. It helps maximize ROI can significantly reduce the Total Cost or Ownership (TCO) for clients in their analytics/AI journey.
Infrastructure savings of IBM Cloud Pak for Data on Power Systems
Power Systems are ranked #1 in every major reliability category and deliver the most reliable on-premises infrastructure to meet around-the-clock customer demands. Cloud Pak for Data on Red Hat OpenShift deployed on Power Systems allows you to easily integrate with your organization’s private or hybrid cloud strategy. It provides the foundation for executing AI workloads using GPU-accelerated POWER 9 technology. With Power Systems, clients can take advantage of superior core performance and memory bandwidth to deliver both performance and price-performance advantages.
Flexible platform: Land and expand or plug and play architecture
- Containers and container management efficiencies totaling USD 12.5 million to USD 14.4 million. With Cloud Pak for Data, companies can improve their readiness for cloud migration, improve licensing flexibility with IBM, and reduce both hardware purchases and infrastructure management efforts.
- Based on the customer interviews, Forrester modeled the financial impact for the composite organization with the following estimates:
- The composite organization has 10 data stores located in different countries.
- For each data store, there are three IT FTEs responsible for managing the infrastructure. With Cloud Pak for Data, the composite expects to reduce that effort by between 65 percent to 85 percent, which allows the IT FTEs to spend more time on higher value tasks (e.g., innovation).
- A third of the composite organization’s servers are refreshed annually. Due to an increase in hardware utilization, the composite expects to reduce the amount of hardware purchases by 33 percent during each refresh cycle.
This yields a three-year projected PV ranging from USD 12.5 million to USD 14.4 million. The summary table for the low, mid, and high projections is shown below, followed by the detailed calculations for each projection.
As you embark on your data architecture modernization, choose a solution that not only provides you with a flexible infrastructure, but one that helps you reduce costs while accelerating business insights. Take the next steps by signing up for our webinar on June 23 joined by our guest, Forrester analyst speaker, to learn more on the benefits of a unified data and AI platform.
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