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As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. Measuring the speed of time Is there already a microbenchmark for os::javaTimeMillis()? I also shared setting the clocksource in my talks and in my 2015 [Linux tunables] post.
It was called Jellly at the time (mid 2015) but it was an early build of what OctoPerf would become. And when we started in 2015, JMeter was undoubtedly the best tool around. You have to remember this was in 2015, a lot has changed since, Gatling is definitely a stronger tool.
This was a chance to talk about other things I've been working on, such as the present and future of hardware performance. The video is on [youtube]: The slides are on [slideshare] or as a [PDF]: I work on many areas of performance, but recently I've had a lot of demand to talk about BPF. Ford, et al., “TCP
Hardware virtualization for cloud computing has come a long way, improving performance using technologies such as VT-x, SR-IOV, VT-d, NVMe, and APICv. The latest AWS hypervisor, Nitro, uses everything to provide a new hardware-assisted hypervisor that is easy to use and has near bare-metal performance. I'd expect between 0.1%
Adoption is now really starting to explode in 2015 as more and more businesses understand the power analytics has to empower their organizations. In the past analytics within an organization was the pinnacle of old style IT: a centralized data warehouse running on specialized hardware. Cloud enables self-service analytics.
As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. Measuring the speed of time Is there already a microbenchmark for os::javaTimeMillis()? I also shared setting the clocksource in my talks and in my 2015 Linux tunables post.
## References I've reproduced the references from my SREcon22 keynote below, so you can click on links: - [Gregg 08] Brendan Gregg, “ZFS L2ARC,” [link] Jul 2008 - [Gregg 10] Brendan Gregg, “Visualizations for Performance Analysis (and More),” [link] 2010 - [Greenberg 11] Marc Greenberg, “DDR4: Double the speed, double the latency?
As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. Measuring the speed of time Is there already a microbenchmark for os::javaTimeMillis()? I also shared setting the clocksource in my talks and in my 2015 [Linux tunables] post.
This was a chance to talk about other things I've been working on, such as the present and future of hardware performance. The video is on [youtube]: The slides are [here] or as a [PDF]: first prev next last / permalink/zoom I work on many areas of performance, but recently I've had a lot of demand to talk about BPF. Ford, et al., “TCP
In this particular investigation, which spanned twenty months, we suspected hardware failure, compiler bugs, linker bugs, and other possibilities. Jumping too quickly to blaming hardware or build tools is a classic mistake, but in this case the mistake was that we weren’t thinking big enough. Russian translation is here.
Hardware virtualization for cloud computing has come a long way, improving performance using technologies such as VT-x, SR-IOV, VT-d, NVMe, and APICv. The latest AWS hypervisor, Nitro, uses everything to provide a new hardware-assisted hypervisor that is easy to use and has near bare-metal performance. I'd expect between 0.1%
JavaScript-Heavy # Since at least 2015, building JavaScript-first websites has been a predictably terrible idea, yet most of the sites I trace on a daily basis remain mired in script. [1] India's speed test medians are moving quickly, but variance is orders-of-magnitude wide, with 5G penetration below 25% in the most populous areas.
References I've reproduced the references from my SREcon22 keynote below, so you can click on links: [Gregg 08] Brendan Gregg, “ZFS L2ARC,” [link] , Jul 2008 [Gregg 10] Brendan Gregg, “Visualizations for Performance Analysis (and More),” [link] , 2010 [Greenberg 11] Marc Greenberg, “DDR4: Double the speed, double the latency?
Devices and networks have evolved too: Alex Russell @slightlylate An update on mobile CPUs and the Performance Inequality Gap: Mid-tier Android devices (~$300) now get the single-core performance of a 2014 iPhone and the multi-core perf of a 2015 iPhone. Hardware Past As Performance Prologue. Mind The Gap. Tap for a larger version.
A close monitoring of the hardware enthusiast community, including many of the most respected hardware analysts and reviewers paints an even more dire picture about Intel in the server processor space. This made it easier for database professionals to make the case for a hardware upgrade, and made the typical upgrade more worthwhile.
Anyway, the following patch seems to make the load average much more consistent WRT the subjective speed of the system. They are demand on the system, albeit for software resources rather than hardware resources. ## Decomposing Linux load averages Can the Linux load average value be fully decomposed into components? Yes, I'd say so.
You need a business stakeholder buy-in, and to get it, you need to establish a case study, or a proof of concept using the Performance API on how speed benefits metrics and Key Performance Indicators ( KPIs ) they care about. Start Render time, Speed Index ). Treo Sites provides competitive analysis based on real-world data.
You need a business stakeholder buy-in, and to get it, you need to establish a case study, or a proof of concept using the Performance API on how speed benefits metrics and Key Performance Indicators ( KPIs ) they care about. Note : If you use Page Speed Insights or Page Speed Insights API (no, it isn’t deprecated!),
You need a business stakeholder buy-in, and to get it, you need to establish a case study on how speed benefits metrics and Key Performance Indicators ( KPIs ) they care about. Note : If you use Page Speed Insights (no, it isn’t deprecated), you can get CrUX performance data for specific pages instead of just the aggregates.
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