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Category: White papers

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

We’ve fixed an installation bug in the CloudXPRT Data Analytics Workload package

Yesterday, we published an updated CloudXPRT Data Analytics workload package that fixes a problem during the package installation process. CloudXPRT uses the Helm utility, which serves as a package manager for the Kubernetes container orchestration system. Helm accesses files in a default repository, and the version of Helm that we originally used with CloudXPRT tries to access files that are no longer available. We fixed the problem by updating the code to use the latest version of Helm.

This update does not change how the benchmark workload runs, and has no impact on benchmark results. We apologize if this bug caused headaches for any testers during installation, and we appreciate your patience as we worked on a fix.

As a reminder for testers interested in experimenting with the CloudXPRT Data Analytics workload, the Overview of the CloudXPRT Data Analytics Workload paper is now available. 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, or have encountered any obstacles during testing, 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

Improved CloudXPRT documentation is coming soon

CloudXPRT is undoubtedly the most complex tool in the XPRT family of benchmarks. To run the cloud-native benchmark’s multiple workloads across different hardware and software platforms, testers need two things: (1) at least a passing familiarity with a wide range of cloud-related toolkits, and (2) an understanding that changing even one test configuration variable can affect test results. While the complexity of CloudXPRT makes it a powerful and flexible tool for measuring application performance on real-world IaaS stacks, it also creates a steep learning curve for new users.

Benchmark setup and configuration can involve a number of complex steps, and the corresponding instructions should be thorough, unambiguous, and intuitive to follow. For all of the XPRT tools, we strive to publish documentation that provides quick, easy-to-find answers to the questions users might have. Community members have asked us to improve the clarity and readability of the CloudXPRT setup, configuration, and individual workload documentation. In response, we are working to create more—and better—CloudXPRT documentation.

If you’re intimidated by the benchmark’s complexity, helping you is one of our highest priorities. In the coming weeks and months, we’ll be evaluating all of our CloudXPRT documentation, particularly from the perspective of new users, and will release more information about the new documentation as it becomes available.

We also want to remind you of some of the existing CloudXPRT resources. We encourage everyone to check out the Introduction to CloudXPRT and Overview of the CloudXPRT Web Microservices Workload white papers. (Note that we’ll soon be publishing a paper on the benchmark’s data analytics workload.) Also, a couple of weeks ago, we published the CloudXPRT learning tool, which we designed to serve as an information hub for common CloudXPRT topics and questions, and to help tech journalists, OEM lab engineers, and everyone who is interested in CloudXPRT find the answers they need as quickly as possible.

Thanks to all who let us know that there was room for improvement in the CloudXPRT documentation. We rely on that kind of feedback and always welcome it. If you have any questions or suggestions regarding CloudXPRT or any of the other XPRTs, please let us know!

Justin

We’re working on an AIXPRT learning tool

For anyone interested in learning more about AIXPRT, the Introduction to AIXPRT white paper provides detailed information about its toolkits, workloads, system requirements, installation, test parameters, and results. However, for AIXPRT.com visitors who want to find the answers to specific AIXPRT-related questions quickly, a white paper can be daunting.

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’ve decided to develop a new learning tool that will serve as an information hub for common AIXPRT topics and questions.

The new learning tool will be available online through our site. It will offer quick bites of information about the fundamentals of AIXPRT, why the benchmark matters, the benefits of AIXPRT testing and results, machine learning concepts, key terms, and practical testing concerns.

We’re still working on the tool’s content and design. Because we’re designing this tool for you, we’d love to hear the topics and questions you think we should include. If you have any suggestions, please let us know!

Justin

Coming soon: a white paper about the CloudXPRT web microservices workload

Soon, we’ll be expanding our portfolio of CloudXPRT resources with a white paper that focuses on the benchmark’s web microservices workload. While we summarized the workload in the Introduction to CloudXPRT white paper, the new paper will discuss the workload in much greater detail.

In addition to providing practical information about the web microservices installation packages 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.

As we’ve noted, CloudXPRT is one of the more complex tools in the XPRT family, with no shortage of topics to explore further. We plan to publish a companion overview for the data analytics workload, and possible future topics include the impact of adjusting specific test configuration options, recommendations for results reporting, and methods for analysis.

We hope that the upcoming Overview of the CloudXPRT Web Microservices Workload paper will serve as a go-to resource for CloudXPRT testers, and will answer any questions you have about the workload. Once it goes live, we’ll provide links 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

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