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Most jobs I was offered were related to older technologies like Prolog/Cobol. 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. How did you get into performance engineering?
The building blocks of multi-tenancy are Linux namespaces , the very technology that makes LXC, Docker, and other kinds of containers possible. Unfortunately, these default namespace boundaries are not sufficient to prevent container escape, as seen in CVEs like CVE-2015–2925.
It's an exciting time for developments in computer performance, not just for the BPF technology (which I often [write about]) but also for processors with 3D stacking and cloud vendor CPUs (e.g., This was a chance to talk about other things I've been working on, such as the present and future of hardware performance.
HPU: Holographic Processing Unit (HPU) is the specific hardware of Microsoft’s Hololens. SPU: Stream Processing Unit (SPU) is related to the specialized hardware to process the data streams of video. TPU: Tensor Processing Unit (TPU) is Google’s specialized hardware for neural network.
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.
2015-2020: Overhead As part of production rollout I did many performance overhead tests, which I've described publicly before: The overhead of adding frame pointers to everything (libc and Java) was usually less than 1%, with one exception of 10%. We may get there with future technologies I'll cover later.
It's an important vendor-neutral space to share the latest in technology. USENIX has been a great help to my career and my employers, and I hope it is just as helpful for you. And now, helping bring USENIX conferences to Australia by giving the first keynote: I could not have scripted or expected it.
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.
It's an exciting time for developments in computer performance, not just for the BPF technology (which I often [write about]) but also for processors with 3D stacking and cloud vendor CPUs (e.g., This was a chance to talk about other things I've been working on, such as the present and future of hardware performance.
If you have been paying attention to the technology press over the past 12-18 months, you may have noticed a rather large number of negative stories about Intel's processor business. This made it easier for database professionals to make the case for a hardware upgrade, and made the typical upgrade more worthwhile.
My development collogues and I are starting a regular blog series, outlining the vast range of scalability improvements, allowing SQL Server 2016 to run across a wide array of hardware configurations, faster and better than previous releases of SQL Server. Try SQL Server 2016 Today.
It's an important vendor-neutral space to share the latest in technology. USENIX has been a great help to my career and my employers, and I hope it is just as helpful for you. And now, helping bring USENIX conferences to Australia by giving the first keynote: I could not have scripted or expected it. It was a great privilege.
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] Having provisioned more than adequately in the 4G era, new technology isn't having the same impact from pent-up demand.
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. At Netflix, we've been using these technologies as they've been made available for instance types in the AWS EC2 cloud. I'd expect between 0.1% small (thanks @cperciva ). ## 3.
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. At Netflix, we've been using these technologies as they've been made available for instance types in the AWS EC2 cloud. I'd expect between 0.1% small (thanks @cperciva ). ## 3.
On the other hand, we have hardware constraints on memory and CPU due to JavaScript parsing times (we’ll talk about them in detail later). In real-life world, most products aren’t even close: an median bundle size today is around 417KB , which is up 42% compared to early 2015.
On the other hand, we have hardware constraints on memory and CPU due to JavaScript parsing times (we’ll talk about them in detail later). In real-life world, most products aren’t even close: an average bundle size today is around 400KB , which is up 35% compared to late 2015. We could also go beyond the bundle size budget though.
The new region will give Nordic-based businesses, government organisations, non-profits, and global companies with customers in the Nordics, the ability to leverage the AWS technology infrastructure from data centers in Sweden. In 2014 and 2015 respectively, AWS opened offices in Stockholm and Espoo, Finland.
On the other hand, we have hardware constraints on memory and CPU due to JavaScript parsing and execution times (we’ll talk about them in detail later). compared to early 2015. It’s still important to prioritize critical resources as early as possible, but 14 KB might not be that relevant with BBR in place.) ( thanks, Victor, Barry! ).
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