speed-up-vm-whats-new-in-vmware-vsphere-6

VMware released an official technical guide about What’s New in VMware vSphere 6 also covering some performance improvements and how to speed up VMs. The good news – many performance improvements happen automatically

You can find the document here: 

What’s New in the VMware vSphere® 6.0 Platform

Firefox at speed

Photo courtesy of Elsie esq.(CC Attribution)

NUMA

To give you one example we see very often causing a performance problem in vSphere 5.x – NUMA, simplified the architecture shortening the communication way between CPU and memory. Unfortunately NUMA cannot only speed up VM’s it can also slow down massively if the VMs are too large from a resource perspective to be served by one CPU/Memory Node. You can read some amazing articles around NUMA from Frank Dennemann here.

vNUMA Enhancements When a vNUMA virtual machine with the hot-add memory option is enabled and memory is hot-added to it, that memory is now allocated equally across all NUMA regions. In previous releases, all new memory was allocated only to region 0. This enhancement ensures that all regions benefit from the increase in RAM, enabling the virtual machine to scale without requiring any downtime.

That is one of the big news in vSphere 6 helping to maintain the NUMA performance improvement even running Monster VMs. If you’re still running vSphere 5.x you should check for NUMA improvements.

Virtual Desktops

Another major improvement to speed up VM running desktop OS comes with the NVIDIA Grid support:

Using GRID vGPU technology, the graphics commands of each virtual machine are passed directly to the GPU, without translation by the hypervisor. This enables the GPU hardware to be time sliced, to deliver the ultimate in shared virtualized graphics performance. GRID vGPU offers the most flexibility of any solution, enabling deployment of virtual machines across a wide range of users and graphics applications, including Microsoft PowerPoint slides and YouTube videos, to the most-demanding engineer using intensive 3D CAD software

Speed UP VM - NVIDIA Grid support

Photo courtesy of NVIDIA

Virtual Hardware

Last but not least there has been again a big improvement of the supported virtual hardware. Now you can definitely create big monster VMs:

vSphere 6.0 introduces a new virtual machine compatibility level with several new features such as support for 128 vCPUs and 4TB of RAM, hot-add RAM enhancements to vNUMA, WDDM 1.1 GDI acceleration, a USB 3.0 xHCI controller, and several serial and parallel port enhancements

CNIL
Metrics and Logs

(formerly, Opvizor Performance Analyzer)

VMware vSphere & Cloud
PERFORMANCE MONITORING, LOG ANALYSIS, LICENSE COMPLIANCE!

Monitor and Analyze Performance and Log files:
Performance monitoring for your systems and applications with log analysis (tamperproof using immudb) and license compliance (RedHat, Oracle, SAP and more) in one virtual appliance!

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Use Case - Tamper-resistant Clinical Trials

Goal:

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.

Use Case - Finance

Goal:

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.

Implementation:

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.

Use Case - eCommerce and NFT marketplace

Goal:

No matter if it’s an eCommerce platform or NFT marketplace, the goals are similar:

  • High amount of transactions (potentially millions a second)
  • Ability to read and write multiple records within one transaction
  • prevent overwrite or updates on transactions
  • comply with regulations (PCI, GDPR, …)


Implementation:

immudb is typically scaled out using Hyperscaler (i. e. AWS, Google Cloud, Microsoft Azure) distributed across the Globe. Auditors are also distributed to track the verification proof over time. Additionally, the shop or marketplace applications store immudb cryptographic state information. That high level of integrity and tamper-evidence while maintaining a very high transaction speed is key for companies to chose immudb.

Use Case - IoT Sensor Data

Goal:

IoT sensor data received by devices collecting environment data needs to be stored locally in a cryptographically verifiable manner until the data is transferred to a central datacenter. The data integrity needs to be verifiable at any given point in time and while in transit.

Implementation:

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.

Use Case - DevOps Evidence

Goal:

CI/CD and application build logs need to be stored auditable and tamper-evident.
A very high Performance is required as the system should not slow down any build process.
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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