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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
My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP
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.
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. Individual processes generate WAL records, and latency is very crucial for transactions. The actual benefit of compression depends on many factors.
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.
They can run applications in Sweden, serve end users across the Nordics with lower latency, and leverage advanced technologies such as containers, serverless computing, and more. The second platform is a managed IoT cloud with customer-facing applications and data management, which went live in 2016.
Data-bearing members face a higher risk of encountering issues caused by rollbacks, compared to others who utilize different storage methods. By incorporating journaling into MongoDB, data integrity is maintained while reducing latency for writing, ultimately improving the overall stability and performance of the database.
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
My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP
Back on December 5, 2017, Microsoft announced that they were using AMD EPYC 7551 processors in their storage-optimized Lv2-Series virtual machines. The slightly newer Intel Xeon E5-26xx v4 (Broadwell) series which was introduced in Q1 of 2016, increased that to 2400MHz. They also only have 40 PCIe 3.0 lanes per processor. Memory (GiB).
LTS (April 2016). I wrote about it in a previous post, [DTrace for Linux 2016]. Here's some output from my zfsdist tool, in bcc/BPF, which measures ZFS latency as a histogram on Linux: # zfsdist. Tracing ZFS operation latency. The hardest part on Linux is now done: kernel support. Hit Ctrl-C to end. ^C
It simulates a link with a 400ms RTT and 400-600Kbps of throughput (plus latency variability and simulated packet loss). Simulated packet loss and variable latency, however, can make benchmarking extremely difficult and slow. Our baseline, then, should probably trade lower throughput/higher-latency for packet loss.
At the time of the last Confluence run, the gap had stretched to nearly 1000 APIs, doubling since 2016. Chrome has missed several APIs for 3+ years: Storage Access API. For heavily latency-sensitive use-cases like WebXR, this is a critical component in delivering a good experience. Some relatively minor additions (e.g.
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.
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billion in 2016. By 2021, a distributed cloud would help companies physically put all services closely together, thereby addressing low-latency challenges, minimising the expense of storage and ensuring that data standards are consistent with the laws in a given geographical region. In 2021 what can we expect?
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