Dell EMC Builds on Composable Infrastructure Strategy

Dell EMC’s PowerEdge MX Server Adapts to Changes in Compute Landscape

Daily Tech Briefing Aug. 24
Written By
eWEEK Staff
eWEEK Staff
Aug 24, 2018
2 minute read
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Today’s topics include Dell EMC rolling out its modular PowerEdge MX server, and Pure Storage acquiring deduplication company StorReduce.

Dell EMC announced Aug. 21 that starting Sept. 12 its new modular system called the PowerEdge MX will be generally available. Designed to be able to adapt to changes in the compute landscape, PowerEdge MX offers enterprises the flexibility to run a wide array of workloads and to easily provision resources as needed.

The system is a key component of Dell EMC’s larger Kinetic Infrastructure composable infrastructure strategy, which calls for cloudlike environments where data center resources are brought together into a single pool that applications can draw from to run most quickly and efficiently.


The PowerMX server comes without a midplane, which means the system can adapt to any changes in technology that happen in the future, including changes in processor and GPU technologies and to storage and connectivity. Having no midplane also means the PowerMX can support fully disaggregated components, from memory-centric devices to GPUs and field-programmable gate arrays.

All-flash storage maker Pure Storage on Aug. 21 announced the acquisition of StorReduce, a cloud-first software-defined storage solution for managing large-scale unstructured data. Financial terms of the acquisition were not disclosed.

The acquisition allows Pure Storage to add sophisticated deduplication technology to its object storage portfolio and expand its public cloud integrations to meet the growing demand to manage unstructured data in multi-cloud environments.

According to StorReduce CEO Vanessa Wilson, “With the combination of StorReduce’s data-reduction capabilities and Pure’s flash and object storage technologies, we can now optimize many modern cloud-native applications as well as many existing unstructured data workloads.”

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