This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
AWS Graviton2); for memory with the arrival of DDR5 and High Bandwidth Memory (HBM) on-processor; for storage including new uses for 3D Xpoint as a 3D NAND accelerator; for networking with the rise of QUIC and eXpress Data Path (XDP); and so on. Ford, et al., “TCP
## 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?
When we released Always On Availability Groups in SQL Server 2012 as a new and powerful way to achieve high availability, hardware environments included NUMA machines with low-end multi-core processors and SATA and SAN drives for storage (some SSDs). As we moved towards SQL Server 2014, the pace of hardware accelerated. Want to dive deeper?
Now, since backup speed and compactness are important for busy, important databases, Percona’s open source physical backup solution – Percona XtraBackup (PXB) , takes into account all these aspects and benefits MySQL world with its exceptional capabilities! Copyright (c) 2016, 2023, Oracle and/or its affiliates.
Back in 2016, I gave a talk outlining the causes and effects of the terrible performance of web apps built using popular tools on the fastest-growing device segment: low-end to mid-range Android phones. A then-representative $200USD device had 4-8 slow (in-order, low-cache) cores, ~2GiB of RAM, and relatively slow MLC NAND flash storage.
Some of the built-in features ( wal_compression ) have been there since 2016, and almost all backup tools do the WAL compression before taking it to the backup repository. Attempts to compress PostgreSQL WAL at different levels have always been around since the beginning. The actual benefit of compression depends on many factors.
Mbps download speed Jake Archibald mentioned his relative getting or the 0.8 Mbps download speed my in-laws get at their house. Ballooning bandwidth and storage have fostered complacency that we can do without. My home internet connection gives me somewhere around 3 Mbps down. It seems blazingly fast compared to the 0.42
The second platform is a managed IoT cloud with customer-facing applications and data management, which went live in 2016. We are excited to offer a comprehensive portfolio of services, from foundational technologies such as compute, storage, and networking to more advanced services such as containers and serverless computing.
AWS Graviton2); for memory with the arrival of DDR5 and High Bandwidth Memory (HBM) on-processor; for storage including new uses for 3D Xpoint as a 3D NAND accelerator; for networking with the rise of QUIC and eXpress Data Path (XDP); and so on. Ford, et al., “TCP
SQL Server 2016 Service Pack 1 (all SKUs) , in combination with Windows Server 2016 (All SKUs) or Windows 10 Client introduces non-volatile memory support for the tail of the log file (LDF) which can significantly increase transaction throughput. Block storage is what you think of today as disk access. Tail Of Log Caching.
Data-bearing members face a higher risk of encountering issues caused by rollbacks, compared to others who utilize different storage methods. This particular write concern prioritizes data longevity over reading speed. The files look something like this: <dbname> <collectionname> 2016-02-08T19-34-44.0.bson
You will need SQL Server 2016 (or later) and Developer Edition (or equivalent) to reproduce the results shown here. This table uses columnstore for its primary storage to produce batch mode execution later on. Batch mode execution is all about speed. You might call this arrangement "off-row" or "out-of-batch" storage.
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?
Back on December 5, 2017, Microsoft announced that they were using AMD EPYC 7551 processors in their storage-optimized Lv2-Series virtual machines. This processor has a base clock speed of 2.0GHz, with an all-core boost speed of 2.55GHz, and a max boost clock speed of 3.0GHz. The L3 cache size is 64MB. Azure Lsv2 Details.
LTS (April 2016). I wrote about it in a previous post, [DTrace for Linux 2016]. I wrote a page on it: [perf]. - **eBPF**: tracing features completed in 2016, this provides efficient programmatic tracing to existing kernel frameworks. The hardest part on Linux is now done: kernel support. It's the official profiler.
Volt Active Data (Volt) is a sophisticated real-time data platform intricately designed with multiple critical components, including high-speed data processing, in-memory storage, and ACID-compliant transactions. Why Jepsen Testing? A major customer found an atomicity bug in our export system last year.
JavaScript is the single most expensive part of any page in ways that are a function of both network capacity and device speed. Thankfully, this is somewhat easier than network speeds: more than half of American mobile users are on Android devices. The true median device from 2016 sold at about ~$200 unlocked.
Tip: There are a number of directives that Clear-Site-Data will accept: "cookies" , "storage" , "executionContexts" , and "*" (which, naturally, means ‘all of the above’). a CDN), to always serve the freshest possible copy, and not to persist anything to storage. Examples and Recipes. headers we might employ. Live Train Timetable Page.
Virtualized in Hardware**: Hardware support for virtualization, and near bare-metal speeds. In this configuration, the AMI and boot is paravirt (PV), the kernel is making hypercalls instead of privileged instructions, and the system is using paravirt network and storage drivers. I'd expect between 0.1% The AMI and boot are now HVM.
Virtualized in Hardware**: Hardware support for virtualization, and near bare-metal speeds. In this configuration, the AMI and boot is paravirt (PV), the kernel is making hypercalls instead of privileged instructions, and the system is using paravirt network and storage drivers. I'd expect between 0.1% The AMI and boot are now HVM.
We organize all of the trending information in your field so you don't have to. Join 5,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content