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Mastering Mega VMs HCI 2.0

What Do We Mean When We Say Mega-VM?

What exactly do we mean when we say mega-VM? They’re what occurs when storage and computer demands aren’t in sync in a hyperconverged system. Perhaps an application requires a lot of storage but not a lot of computation, or a lot of compute but not a lot of storage.

When storage and computation resources cannot be increased independently, this type of mismatch is a major issue. Customers discover that HCI is only delivering a fraction of what they had anticipated for when this occurs. Instead of 15-20 compute VMs per node, they may only be able to accommodate three or four mega-VMs, leaving the storage capacity unutilized.

HCI promised extraordinary flexibility and efficiency, but this isn’t it. Many applications have benefited from the notion of combining storage, networking, and computing resources into a single “mega-server” that is easy and quick to scale—but not all of them.

As a result, data center managers must often reallocate resources, move virtual machines to new nodes, or change application limitations. One misbehaving’monster’ might cause a delay or even a crash in the programs it shares resources with.

Mega-VMs are classified into three categories. The first are mission-critical programs that require their own pool of I/O, such as Oracle databases or SAP HANA deployments.

The second category includes programs that have high peak demand at predictable periods, such as reporting software at the end of a quarter, oor a large payroll processing application.

Finally, Mega-VMs in a test or development environment, especially now that AI and machine learning are being used by developers. These virtual machines frequently need peak I/O at irregular periods. To deliver the outcomes we value: insights into consumers, goods, and the market, AI and machine learning require quick access to massive datasets.

Traditional HCI can result in costly (and wasteful) overprovisioning in all of these instances. These inefficiencies are eliminated with HPE HCI 2.0. HCI 2.0 is disaggregated, unlike traditional HCI, which works on off-the-shelf hardware.

Data centers may be controlled and expanded according to their individual needs using HPE ProLiant servers and HPE Nimble Storage dHCI, which operate together under HPE InfoSight, a smart VM-aware management software. HPE Nimble Storage devices may be plugged in and available for apps in 15 minutes if extra storage is required.

If more computing power is needed, HPE ProLiant servers may be added to the network and auto-configure with minimum supervision. HPE InfoSight may be set up to guarantee that resources are available when and where they are needed. To create room for a mega-VM with a ‘hungry’ application, or when InfoSight detects a maintenance issue like an impending disk failure, VMs may be relocated automatically and smoothly from one node to another.

HPE InfoSight solves storage managers’ most complex challenges with systems modeling, predictive algorithms, and statistical analysis, ensuring that storage resources are dynamically and intelligently allocated to meet the changing demands of business-critical applications.

HPE InfoSight is powered by a robust engine that applies deep data analytics to telemetry data collected from HPE Nimble Storage arrays throughout the world. Each HPE Nimble Storage array collects more than 30 million sensor values every day.

The HPE InfoSight engine converts the millions of data points acquired into useful information, allowing clients to achieve considerable operational efficiencies. If an issue cannot be automatically rectified by HPE InfoSight, it is immediately reported to HPE support, who will give Level 3 help remotely.

HPE’s HCI 2.0 revolutionizes the data center, enabling your company to meet the needs of compute- and storage-hungry mega-VMs. and opening the path for more efficient, and productive ,data operations.

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