vmware-vsphere-persistent-memory-performance-must-have-pdf-download

VMware vSphere Persistent Memory Performance – Must Have PDF Download

Vladen Seget posted an intersting blog about a must have PDF Download from VMware vSphere.

Please find here Vladen’s post with all comments. Thanks Vladen and go ahead! You can also find a lot other interesting articles from Vladen, just follow the link and scroll down to More from ESX Virtualization.

VMware vSphere Persistent memory (PMEM) has been announced with vSphere 6.7, but the feature only works with the latest hardware from selected vendors. With supported hardware modules, customers can use this very fast storage, as a new storage tier for enterprise applications. vSphere Persistent Memory Performance is the topic of today’s post.

vSphere persistent memory works only with some hardware support, but how actually the underlying piece of hardware looks like? Our longtime readers remember perhaps Diablo Technologies and our detailed write-up from TFD. They presented this technology already quite a few years back, before completely disappearing from the marketplace.

Persistent memory is an amazing technology that multiplies the storage performances of servers. It was developed as RAM module that retains its content (across reboots too) and vSphere supports Two different modes of access to those modules. As vPMEM disk (exposed to a VM as datastore) or as vPMEM (direct and uninterrupted access to the NVDIMM hardware).

To sum Persistent memory features:

  • DRAM-like latency and bandwidth
  • Regular load/store CPU instructions
  • Paged/mapped by operating system just like DRAM
  • Data is persistent across reboots

Persistent memory and vSphere 6.7?

Here is an overview.

Quote:

vSphere can carve out a piece of the local persistent memory in a machine and present it to a VM as a local disk. This disk will be able to provide ultra-fast local storage without any lift-n-shift of workloads. In this mode, no guest OS change or application change is required to take advantage of the fast PMEM hardware. Virtual disks of a VM can be live migrated from regular storage (e.g. SAN, vSAN, NFS) to PMEM based disk using storage vMotion.

VMware is continuously working with a broad ecosystem including hardware vendors, OEMS and ISVs to develop and support PMEM. vSphere has been enabled to manage and expose the persistent memory feature to VMs. There are different ways in which one can leverage the PMEM feature in a virtualized environment

You can also expose persistent memory directly to the VMs.

Memory Performance

Photo courtesy of Vladan Seget

Quote:

vSphere can also slice a piece of the local persistent memory in a server and present it to a VM as a virtual NVDIMM. This is a new type of virtual device that exposes a byte addressable persistent memory to the VM. Virtual NVDIMM is compatible with latest Guest Operating Systems which support persistent memory such as Windows 2016, RedHat Enterprise Linux 7.4, etc. But, applications need not change and can still use legacy (block based) file interfaces like read, write, mmap.

vSphere Persistent Memory Performance

VMware has released recently a new PDF where you’ll see the actual performance and one of the conclusions is that it’s much faster then NVMe SSD storage. vSphere Persistent Memory Performance is tightened to a hardware where the hardware has to have support for those NVDIMM modules itself.

The hardware module from Diablo Technologies looked like this:

Memory Performance

Photo courtesy of Vladan Seget

VMware vSphere Persistent Memory Performance PDF details the setup, the lab gear, the hardware. But also the software used, the tools and the workloads which were used during the testing. It’s a definitely a must have PDF.

Quote:

vSphere PMEM gives up to 8x throughput and improvement in micro-benchmarks and up to 35% improvement in Tier-1 workloads compared to NVMe SSD.

Here is a direct link to the whitepaper: VMware vSphere Persistent Memory Performance PDF.

Thanks Vladen and keep going!

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Blockchain PoCs were unsuccessful due to complexity and lack of developers.

Still the goal of data immutability as well as client verification is a crucial. Furthermore, the system needs to be easy to use and operate (allowing backup, maintenance windows aso.).

Implementation:

immudb is running in different datacenters across the globe. All clinical trial information is stored in immudb either as transactions or the pdf documents as a whole.

Having that single source of truth with versioned, timestamped, and cryptographically verifiable records, enables a whole new way of transparency and trust.

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Store the source data, the decision and the rule base for financial support from governments timestamped, verifiable.

A very important functionality is the ability to compare the historic decision (based on the past rulebase) with the rulebase at a different date. Fully cryptographic verifiable Time Travel queries are required to be able to achieve that comparison.

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While the source data, rulebase and the documented decision are stored in verifiable Blobs in immudb, the transaction is stored using the relational layer of immudb.

That allows the use of immudb’s time travel capabilities to retrieve verified historic data and recalculate with the most recent rulebase.

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immudb runs embedded on the IoT device itself and is consistently audited by external probes. The data transfer to audit is minimal and works even with minimum bandwidth and unreliable connections.

Whenever the IoT devices are connected to a high bandwidth, the data transfer happens to a data center (large immudb deployment) and the source and destination date integrity is fully verified.

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CI/CD and application build logs need to be stored auditable and tamper-evident.
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Scalability is key as billions of artifacts are expected within the next years.
Next to a possibility of integrity validation, data needs to be retrievable by pipeline job id or digital asset checksum.

Implementation:

As part of the CI/CD audit functionality, data is stored within immudb using the Key/Value functionality. Key is either the CI/CD job id (i. e. Jenkins or GitLab) or the checksum of the resulting build or container image.

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