The strategy behind this partnership is for IBM and Nutanix to provide channel partners with a turnkey hyper-converged solution for large enterprise customers who are interested in private clouds.
For IBM, they are looking to Nutanix for managing workloads such as big data, but also other intensive workloads such as machine learning, DevOps, and artificial intelligence (AI). IBM said they were looking for an alliance vendor partner with solutions that could scale.
According to IBM, reliable storage, fast networks, and scalability combined are not featured on too many data centres in the market today. Many of the data centres released – even a few years ago – their design has made them virtually obsolete. Combining Nutanix Enterprise Cloud Platform and Power Systems are capable of big data workloads as well as new AI workloads.
This deal is a multi-year initiative that will see IBM/Nutanix deliver what they say are “simple-to-deploy,” web-scale architecture supporting Power-based scale-out computing.
Beyond workloads such as AI and big data. The new solutions will also target:
- Mission-critical workloads, such as databases, large scale data warehouses, web infrastructure, and mainstream enterprise apps;
- Cloud Native Workloads, including full stack open source middleware and enterprise databases and Containers;
- There will also be a fully integrated one-click management stack with Prism, to eliminate silos and reduce the need for specialized IT skills to build and operate cloud-driven infrastructure; and
- Deploying stateful cloud native services using Acropolis Container Services with automated deployment and enterprise-class persistent storage.
Stefanie Chiras, VP Power Systems at IBM, hyper-converged systems continue on a rapid growth trajectory, with a market size forecast of nearly $6 billion by 2020.
Channel partner should note that IBM is planning on also selling the Nutanix-based Power Systems through its own direct sales force as well as with solution providers. IBM and Nutanix has not yet divulged release dates, models and supported server configurations.