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More information about the CloudXPRT results submission process

Earlier this month, we discussed the possibility of using a periodic results submission process for CloudXPRT instead of the traditional rolling publication process that we’ve used for the other XPRTs. We’ve received some positive responses to the idea, and while we’re still working out some details, we’re ready to share the general framework of the process we’re planning to use.

  • We will establish a results review group, which only official BenchmarkXPRT Development Community members can join.
  • We will update the CloudXPRT database with new results once a month, on a pre-published schedule.
  • Two weeks before each publication date, we will stop accepting submissions for consideration for that review cycle.
  • One week before each publication date, we will send an email to the results review group that includes the details of that month’s submissions for review.
  • The results review group will serve as a sanity check process and a forum for comments on the month’s submissions, but we reserve the right of final approval for publication.
  • We will not restrict publishing results outside of the monthly review cadence, but we will not automatically add those results to the results database.
  • We may add externally published results to our database, but will do so only after vetting, and only on the designated day each month.

Our goal is to strike a balance between allowing the tech press, vendors, or other testers to publish CloudXPRT results on their own schedule, and simultaneously building a curated results database that OEMs or other parties can use to compete for the best results.

We’ll share more details about the review group, submission dates, and publications dates soon. Do you have questions or comments about the new process? Let us know what you think!

Justin

CloudXPRT is up next, and we’re thinking about how to handle results submission and publication

Last month, we provided an update on the CloudXPRT development process and more information about the three workloads that we’re including in the first build. We’d initially hoped to release the build at the end of April, but several technical challenges have caused us to push the timeline out a bit. We believe we’re very close to ready, and look forward to posting a release announcement soon.

In the meantime, we’d like to hear your thoughts about the CloudXPRT results publication process. Traditionally, we’ve published XPRT results on our site on a rolling basis. When we complete our own tests, receive results submissions from other testers, or see results published in the tech media, we authenticate them and add them to our site. This lets testers make their results public on their timetable, as frequently as they want.

Some major benchmark organizations use a different approach, and create a schedule of periodic submission deadlines. After each deadline passes, they review the batch of submissions they’ve received and publish all of them together on a single later date. In some cases, they release results only two or three times per year. This process offers a high level of predictability. However, it can pose significant scheduling obstacles for other testers, such as tech journalists who want to publish their results in an upcoming device review and need official results to back up their claims.

We’d like to hear what you think about the different approaches to results submission and publication that you’ve encountered. Are there aspects of the XPRT approach that you like? Are there things we should change? Should we consider periodic results submission deadlines and publication dates for CloudXPRT? Let us know what you think!

Justin

Make confident choices about your company’s future tech with the XPRTs

Durham, NC, April 23, 2020 — Principled Technologies and the BenchmarkXPRT Development Community have released a video on the benefits of consulting the XPRTs before committing to new technology purchases.

AIXPRT, one of the battery of XPRT benchmark tools, runs image-classification and object-detection workloads to determine how well tech handles AI and machine learning.

CloudXPRT, another XPRT tool, accurately measures the end-to-end performance of modern, cloud-first applications deployed on infrastructure as a service (IaaS) platforms – allowing corporate decision-makers to select the best configuration for every objective.

All of the XPRTs give companies the real-world information necessary to determine which prospective future tech p – and which will disappoint

According to the video, “The XPRTs don’t just look at specs and features; they gauge a technology solution’s real-world performance and capabilities. So you know whether switching environments is worth the investment. How well solutions support machine learning and other AI capabilities. If next-gen releases beat their rivals or fall behind the curve.”

Watch the video at facts.pt/pyt88k5. To learn more about how AIXPRT, CloudXPRT, WebXPRT, MobileXPRT, TouchXPRT, CrXPRT, and HDXPRT can help IT decision-makers can make confident choices about future purchases, go to www.BenchmarkXPRT.com.

About Principled Technologies, Inc.
Principled Technologies, Inc. is the leading provider of technology marketing and learning & development services. It administers the BenchmarkXPRT Development Community.

Principled Technologies, Inc. is located in Durham, North Carolina, USA. For more information, please visit www.principledtechnologies.com.

Company Contact
Justin Greene
BenchmarkXPRT Development Community
Principled Technologies, Inc.
1007 Slater Road, Suite #300
Durham, NC 27703
BenchmarkXPRTsupport@PrincipledTechnologies.com

More details about CloudXPRT’s workloads

About a month ago, we posted an update on the CloudXPRT development process. Today, we want to provide more details about the three workloads we plan to offer in the initial preview build:

  • In the web-tier microservices workload, a simulated user logs in to a web application that does three things: provides a selection of stock options, performs Monte-Carlo simulations with those stocks, and presents the user with options that may be of interest. The workload reports performance in transactions per second, which testers can use to directly compare IaaS stacks and to evaluate whether any given stack is capable of meeting service-level agreement (SLA) thresholds.
  • The machine learning (ML) training workload calculates XGBoost model training time. XGBoost is a gradient-boosting framework  that data scientists often use for ML-based regression and classification problems. The purpose of the workload in the context of CloudXPRT is to evaluate how well an IaaS stack enables XGBoost to speed and optimize model training. The workload reports latency and throughput rates. As with the web-tier microservices workload, testers can use this workload’s metrics to compare IaaS stack performance and to evaluate whether any given stack is capable of meeting SLA thresholds.
  • The AI-themed container scaling workload starts up a container and uses a version of the AIXPRT harness to launch Wide and Deep recommender system inference tasks in the container. Each container represents a fixed amount of work, and as the number of Wide and Deep jobs increases, CloudXPRT launches more containers in parallel to handle the load. The workload reports both the startup time for the containers and the Wide and Deep throughput results. Testers can use this workload to compare container startup time between IaaS stacks; optimize the balance between resource allocation, capacity, and throughput on a given stack; and confirm whether a given stack is suitable for specific SLAs.

We’re continuing to move forward with CloudXPRT development and testing and hope to add more workloads in subsequent builds. Like most organizations, we’ve adjusted our work patterns to adapt to the COVID-19 situation. While this has slowed our progress a bit, we still hope to release the CloudXPRT preview build in April. If anything changes, we’ll let folks know as soon as possible here in the blog.

If you have any thoughts or comments about CloudXPRT workloads, please feel free to contact us.

Justin

CloudXPRT development news

Last month, Bill announced that we were starting work on a new data center benchmark. CloudXPRT will measure the performance of modern, cloud-first applications deployed on infrastructure as a service (IaaS) platformson-premises platforms, externally hosted platforms, and hybrid clouds that use a mix of the two. Our ultimate goal is for CloudXPRT to use cloud-native components on an actual stack to produce end-to-end performance metrics that can help users determine the right IaaS configuration for their business.

Today, we want to provide a quick update on CloudXPRT development and testing.

  • Installation. We’ve completely automated the CloudXPRT installation process, which leverages Kubernetes or Ansible tools depending on the target platform. The installation processes differ slightly for each platform, but testing is the same.
  • Workloads. We’re currently testing potential workloads that focus on three areas: web microservices, data analytics, and container scaling. We might not include all of these workloads in the first release, but we’ll keep the community informed and share more details about each workload as the picture becomes clearer. We are designing the workloads so that testers can use them to directly compare IaaS stacks and evaluate whether any given stack can meet service level agreement (SLA) thresholds.
  • Platforms. We want CloudXPRT to eventually support testing on a variety of popular externally hosted platforms. However, constructing a cross-platform benchmark is complicated and we haven’t yet decided which external platforms the first CloudXPRT release will support. We’ve successfully tested the current build with on-premises IaaS stacks and with one externally hosted platform, Amazon Web Services. Next, we will test the build on Google Cloud Hosting and Microsoft Azure.
  • Timeline. We are on track to meet our target of releasing a CloudXPRT preview build in late March and the first official build about two months later. If anything changes, we’ll post an updated timeline here in the blog.

If you would like to share any thoughts or comments related to CloudXPRT or cloud benchmarking, please feel free to contact us.

Justin

CloudXPRT is on the way

A few months ago, we wrote about the possibility of creating a datacenter XPRT. In the intervening time, we’ve discussed the idea with folks both in and outside of the XPRT Community. We’ve heard from vendors of datacenter products, hosting/cloud providers, and IT professionals that use those products and services.

The common thread that emerged was the need for a cloud benchmark that can accurately measure the performance of modern, cloud-first applications deployed on modern infrastructure as a service (IaaS) platforms, whether those platforms are on-premises, hosted elsewhere, or some combination of the two (hybrid clouds). Regardless of where clouds reside, applications are increasingly using them in latency-critical, highly available, and high-compute scenarios.

Existing datacenter benchmarks do not give a clear indication of how applications will perform on a given IaaS infrastructure, so the benchmark should use cloud-native components on the actual stacks used for on-prem and public cloud management.

We are planning to call the benchmark CloudXPRT. Our goal is for CloudXPRT to address the needs described above while also including the elements that have made the other XPRTs successful. We plan for CloudXPRT to

  • Be relevant to on-prem (datacenter), private, and public cloud deployments
  • Run on top of cloud platform software such as Kubernetes
  • Include multiple workloads that address common scenarios like web applications, AI, and media analytics
  • Support multi-tier workloads
  • Report relevant metrics including both throughput and critical latency for responsiveness-driven applications and maximum throughput for applications dependent on batch processing

CloudXPRT’s workloads will use cloud-native components on an actual stack to provide end-to-end performance metrics that allow users to choose the best IaaS configuration for their business.

We’ve been building and testing preliminary versions of CloudXPRT for the last few months. Based on the progress so far, we are shooting to have a Community Preview of CloudXPRT ready in mid- to late-March with a version for general availability ready about two months later.

Over the coming weeks, we’ll be working on getting out more information about CloudXPRT and continuing to talk with interested parties about how they can help. We’d love to hear what workflows would be of most interest to you and what you would most like to see in a datacenter/cloud benchmark. Please feel free to contact us!

Bill

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