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Category: results

Default requirements for CloudXPRT results submissions

Over the past few weeks, we’ve received questions about whether we require specific test configuration settings for official CloudXPRT results submissions. Currently, testers have the option to edit up to 12 configuration options for the web microservices workload and three configuration options for the data analytics workload. Not all configuration options have an impact on testing and results, but a few of them can drastically affect key results metrics and how long it takes to complete a test. Because new CloudXPRT testers may not anticipate those outcomes, and so many configuration permutations are possible, we’ve come up with a set of requirements for all future results submissions to our site. Please note that testers are still free to adjust all available configuration options—and define service level agreement (SLA) settings—as they see fit for their own purposes. The requirements below apply only to results testers want to submit for publication consideration on our site, and to any resulting comparisons.

Web microservices results submission requirement

Starting with the May results submission cycle, all web microservices results submissions must have the workload.cpurequestsvalue, which lets the user designate the number of CPU cores the workload assigns to each pod, set to 4. Currently, the benchmark supports values of 1, 2, and 4, with the default value of 4. While 1 and 2 CPU cores per pod may be more appropriate for relatively low-end systems or configurations with few vCPUs, a value of 4 is appropriate for most datacenter processors, and it often enables CSP instances to operate within the benchmark’s max default 95th percentile latency SLA of 3,000 milliseconds.

In future CloudXPRT releases, we may remove the option to change the workload.cpurequests value from the config.json file and simply fix the value in the benchmark’s code to promote test predictability and reasonable comparisons. For more information about configuration options for the web microservices workload, please consult the Overview of the CloudXPRT Web Microservices Workload white paper.

Data analytics results submission requirement

Starting with the May results submission cycle, all data analytics results submissions must have the best reported performance (throughput_jobs/min) correspond to a 95th percentile SLA latency of 90 seconds or less. We have received submissions where the throughput was extremely high, but the 95th percentile SLA latency was up to 10 times the 90 seconds that we recommend in CloudXPRT documentation. High latency values may be acceptable for the unique purposes of individual testers, but they do not provide a good basis for comparison between clusters under test. For more information about configuration options with the data analytics workload, please consult the Overview of the CloudXPRT Data Analytics Workload white paper.

We will update CloudXPRT documentation to make sure that testers know to use the default configuration settings if they plan to submit results for publication. If you have any questions about CloudXPRT or the CloudXPRT results submission process, please let us know.

Justin

The CloudXPRT v1.1 beta is available!

Last week, we announced that a CloudXPRT v1.1 beta was on the way. We’re happy to say that the v1.1 beta is now available to the public on a dedicated CloudXPRT v1.1 beta download page. While CloudXPRT v1.01 remains the officially supported version on CloudXPRT.com and in our GitHub repository, interested testers can use the v1.1 beta version in new environments as we finalize the v1.1 build for official release. You are welcome to publish results as we do not expect results to change in the final, official release.

As we mentioned in last week’s post, the CloudXPRT v1.1 beta includes the following changes:

  • We’ve added support for Ubuntu 20.04.2 or later for on-premises testing.
  • We’ve consolidated and standardized the installation packages for both workloads. Instead of one package for the data analytics workload and four separate packages for the web microservices workload, each workload has a single installation package that supports on-premises testing and testing with all three supported CSPs.
  • We’ve incorporated Terraform to help create and configure VMs, which helps to prevent problems when testers do not allocate enough storage per VM prior to testing.
  • We’ve replaced the Calico network plugin in Kubespray with Weave, which helps to avoid some of the network issues testers have occasionally encountered in the CPS environment.

Please feel free to share the link to the beta download page. (To avoid confusion, the beta will not appear in the main CloudXPRT download table.) We can’t yet state definitively whether results from the new version will be comparable to those from v1.01. We have not observed any significant differences in performance, but we haven’t tested every possible test configuration across every platform. If you observe different results when testing the same configuration with v1.01 and v1.1 beta, please send us the details so we can investigate.

If you have any questions about CloudXPRT or the CloudXPRT v1.1 beta, please let us know!

Justin

The Overview of the CloudXPRT Data Analytics Workload white paper is now available!

Today, we expand our portfolio of CloudXPRT resources with a paper on the benchmark’s data analytics workload. While we summarized the workload in the Introduction to CloudXPRT white paper, the new paper goes into much greater detail.

In addition to providing practical information about the data analytics installation package and minimum system requirements, the paper describes the workload’s test configuration variables, structural components, task workflows, and test metrics. It also discusses interpreting test results and the process for submitting results for publication.

CloudXPRT is the most complex tool in the XPRT family, and the new paper is part of our effort to create more—and better—CloudXPRT documentation. We plan to publish additional CloudXPRT white papers in the coming months, with possible future topics including the impact of adjusting specific test configuration options, recommendations for results reporting, and methods for analysis.

We hope that the Overview of the CloudXPRT Data Analytics Workload paper will serve as a go-to resource for CloudXPRT testers, and will answer any questions you have about the workload. You can find links to the paper and other resources in the Helpful Info box on CloudXPRT.com and the CloudXPRT section of our XPRT white papers page.

If you have any questions, please let us know!

Justin

The XPRTs can help with your holiday shopping

The biggest shopping days of the year are fast approaching, and if you’re researching phones, tablets, Chromebooks, or laptops in preparation for Black Friday and Cyber Monday sales, the XPRTs can help! One of the core functions of the XPRTs is to help cut through all the marketing noise by providing objective, reliable measures of a device’s performance. For example, instead of trying to guess whether a new Chromebook is fast enough to handle the demands of remote learning, you can use its CrXPRT and WebXPRT performance scores to see how it stacks up against the competition when handling everyday tasks.

A good place to start your search for scores is our XPRT results browser. The browser is the most efficient way to access the XPRT results database, which currently holds more than 2,600 test results from over 100 sources, including major tech review publications around the world, OEMs, and independent testers. It offers a wealth of current and historical performance data across all the XPRT benchmarks and hundreds of devices. You can read more about how to use the results browser here.

Also, if you’re considering a popular device, chances are good that someone has already published an XPRT score for that device in a recent tech review. The quickest way to find these reviews is by searching for “XPRT” within your favorite tech review site, or by entering the device name and XPRT name (e.g. “Apple iPad” and “WebXPRT”) in a search engine. Here are a few recent tech reviews that use one or more of the XPRTs to evaluate a popular device:


The XPRTs can help consumers make better-informed and more confident tech purchases this holiday season, and we hope you’ll find the data you need on our site or in an XPRT-related tech review. If you have any questions about the XPRTs, XPRT scores, or the results database please feel free to ask!

Justin

A first look at the upcoming AIXPRT learning tool

Last month, we announced that we’re working on a new AIXPRT learning tool. Because we want tech journalists, OEM lab engineers, and everyone who is interested in AIXPRT to be able to find the answers they need in as little time as possible, we’re designing this tool to serve as an information hub for common AIXPRT topics and questions.

We’re still finalizing aspects of the tool’s content and design, so some details may change, but we can now share a sneak peak of the main landing page. In the screenshot below, you can see that the tool will feature four primary areas of content:

  • The FAQ section will provide quick answers to the questions we receive most from testers and the tech press.
  • The AIXPRT basics section will describe specific topics such as the benchmark’s toolkits, networks, workloads, and hardware and software requirements.
  • The testing and results section will cover the testing process, the metrics the benchmark produces, and how to publish results.
  • The AI/ML primer will provide brief, easy-to-understand definitions of key AI and ML terms and concepts for those who want to learn more about the subject.

We’re excited about the new AIXPRT learning tool, and will share more information here in the blog as we get closer to a release date. If you have any questions about the tool, please let us know!

Justin

The CloudXPRT results viewer is live

We’re happy to announce that the CloudXPRT results viewer is now live with results from the first few rounds of CloudXPRT Preview testing we conducted in our lab. Here are some tips to help you to navigate the viewer more efficiently:

  • Click the tabs at the top of the table to switch from Data analytics workload results to Web microservices workload results.
  • Click the header of any column to sort the data on that variable. Single click to sort A to Z and double-click to sort Z to A.
  • Click the link in the Source/details column to visit a detailed page for that result, where you’ll find additional test configuration and system hardware information and the option to download results files.
  • By default, the viewer displays eight results per page, which you can change to 16, 48, or Show all.
  • The free-form search field above the table lets you filter for variables such as cloud service or processor.

We’ll be adding more features, including expanded filtering and sorting mechanisms, to the results viewer in the near future. We’re also investigating ways to present multiple data points in a graph format, which will allow visitors to examine performance behavior curves in conjunction with factors such as concurrency and resource utilization.

We welcome your CloudXPRT results submissions! To learn about the new submission and review process we’ll be using, take a look at last week’s blog.

If you have any questions or suggestions for ways that we can improve the results viewer, please let us know!

Justin

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