HPE Introduces Data Management System For Hybrid Cloud. What Does It Mean?

"Today’s announcement marks an important milestone in HPE’s vision to become an edge-to-cloud platform-as-a-service company."

In 2018, Hewlett Packard Enterprise (HPE) introduced HPE GreenLake to deliver IT outcomes with hardware, software, and on-premise expertise. Three years later, HPE now offers a full cloud-operational model for data storage and management. HPE, in a public release, said, “Storage complexity is the roadblock to innovation. You must reimagine the experience – and that is exactly what we are doing today by bringing the cloud operational experience to our customers’ on-premises environments.”

A company must change how it manages data and infrastructure with automation, self-service, and mobilisation from edge-to-cloud across the data lifecycle to embrace digital transformation. This calls for an overhaul of its storage architectures. However, storage architectures are still plagued by complexity arising from LUNs, RAID groups, HBAs, resource planning, and load balancing.

To reduce storage complexity, HPE has introduced a system called Unified DataOps.


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Unified DataOps

Calling it a north star for HPE, the company introduced a data and infrastructure management system for hybrid clouds called Unified DataOps. Based on a unique architectural blueprint, Unified DataOps brings together data-centric policies, automation, cloud-native control and operations, and AI-driven insights to eliminate the complexity of data management, promote operational agility, minimise business risk, and accelerate data-driven decision making.

HPE is delivering Unified DataOps through its data services platform, featuring three new innovations:

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Data Services Cloud Console: It is a SaaS-based console for data and infrastructure management. It took 18 months to develop this console. Rather than managing data and infrastructure manually through a fragmented approach, it delivers unified data operations as a service.

Built on a unique cloud-native architecture, the console is designed to abstract and control infrastructure and data workflows from edge-to-cloud across data and infrastructure lifecycle, setting the base for data management streamlining.

With Data Services Cloud Console, the deployment takes just a few minutes due to auto-discovery and configuration, instead of days or weeks as with traditional systems. It is easier to manage hundreds of systems and can be controlled from anywhere on any device. HPE claims that with Data Service Cloud Console, organisations can now get a cloud-like experience for their enterprise storage.

Data Ops Manager: The new Data Ops Manager feature of HPE is delivered through the Data Services Cloud Console for the global management of data infrastructure from anywhere. The intent-based provisioning helps bring a paradigm shift in the data infrastructure provisioning with an AI-based and application-centric approach that enables self-service, eliminates guesswork and optimises service level objectives (SLOs).

Alletra: It is a cloud-native data infrastructure that powers data from edge to cloud and is managed by Data Services Cloud Console. Alletra features a portfolio of workload-optimised systems that consist of Alletra 9000 and 6000 product families that have on-premise block-level access to all NVMe flash storage in 4U chassis with management and data services through the online console. It offers the capability to deliver architectural flexibility that can run the application without compromise.

Developers can connect to Alletra via consistent API, whether on-premise or cloud-based. They can facilitate persistent volume provisioning, expand volumes and take snapshots of data for reuse. Alletra offers simple data mobility across clouds using replication to HPE Cloud Volumes and operates in hybrid clouds by design. 

The Alletra array operations are monitored by HPE’s InfoSight with predictive analytics that helps in detecting and fixing problems without any external support. InfoSight uses artificial intelligence and machine learning to track Alletra’s status. 

HPE GreenLake

HPE GreenLake is an outcome-based IT consumption model that simplifies IT and frees up resources. It offers a suite of curated solutions that deliver IT outcomes with hardware, software, and on-premise expertise. As per HPE, GreenLake can accelerate time to value, align IT economics with business outcomes, simplify operations, and gain control.

It offers the following features:

  • User-based operation
  • Pay-as-you-go solution
  • Simplicity, scalability, pay per use features of public cloud combined with the security and control of on-premise IT
  • Robust services that are specific to users’ needs

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Shraddha Goled
I am a technology journalist with AIM. I write stories focused on the AI landscape in India and around the world with a special interest in analysing its long term impact on individuals and societies. Reach out to me at

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