Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. Amazon Simple Storage Service (S3). The example below visualizes average latency by API name and stage for a specific AWS API Gateway. Stay tuned for updates in Q1 2020. Requirements.

AWS 132

AWS Metrics IoT Storage 132

Dynatrace

APRIL 26, 2022

STM generates traffic that replicates the typical path or behavior of a user on a network to measure performance for example, response times, availability, packet loss, latency, jitter, and other variables). One use case for STM is to model the behavior of a customer in the form of a flow of transactions along the buyer’s journey.

Monitoring 192

Monitoring Social Media IoT Metrics 192

The Netflix TechBlog

DECEMBER 21, 2020

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 203

Storage Latency Efficiency Data Engineering 203

SQL Performance

APRIL 27, 2020

The basic tier provides up to 5 DTUs with standard storage. The standard tier supports from 10 up to 3000 DTUs with standard storage and the premium tier supports 125 up to 4000 DTUs with premium storage, which is orders of magnitude faster than standard storage. vCore Pricing Tier. GB per vCore. HyperScale Database.

Azure 55

Azure Database Serverless Hardware 55

The Morning Paper

MARCH 17, 2020

higher latency and lower bandwidth)… We have found the actual behavior of Optane DIMMs to be more complicated and nuanced than the "slower, persistent DRAM" label would suggest. The read latency for Optane is 2x-3x higher than DRAM. Optane DIMMs are here! Optane memory is also more pattern-dependent than DRAM. to 0.98.

Scalability 59

Scalability Latency Cache Media 59

The Morning Paper

JUNE 13, 2019

Making queries to an inference engine has many of the same throughput, latency, and cost considerations as making queries to a datastore, and more and more applications are coming to depend on such queries. The following figure highlights how just one of these variables, batch size, impacts throughput and latency on ResNet50.

Hardware 58

Hardware Latency Serverless Energy 58

The Morning Paper

MARCH 10, 2020

So if you want to design a system that will offer good real-world performance, it’s really useful to have benchmarks that accurately represent real-world workloads. This benchmark can synthetically generate more precise key-value queries that represent the reads and writes of key-value stores to the underlying storage system.

Benchmarking 59

Benchmarking Storage Cache Open Source 59

Abhishek Tiwari

JULY 12, 2018

These nodes and edges require a good amount of compute and storage which is typically distributed across a large number servers either running in the cloud or your own data center. If tuned for performance, there is a good change reliability is compromised - and vice versa. In a nutshell, a data pipeline is a distributed system.

Latency 63

Latency Analytics Scalability Engineering 63

The Netflix TechBlog

SEPTEMBER 24, 2021

From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step. Uploading and downloading data always come with a penalty, namely latency.

Cloud 237

Cloud Media Storage Cache 237

The Netflix TechBlog

OCTOBER 27, 2020

The data warehouse is not designed to serve point requests from microservices with low latency. Therefore, we must efficiently move data from the data warehouse to a global, low-latency and highly-reliable key-value store. As most key-value storage engines support efficiently deleting a namespace (e.g.

Latency 243

Latency Storage Big Data Tuning 243

The Netflix TechBlog

JUNE 13, 2023

By collecting and analyzing key performance metrics of the service over time, we can assess the impact of the new changes and determine if they meet the availability, latency, and performance requirements. They enable us to further fine-tune and configure the system, ensuring the new changes are integrated smoothly and seamlessly.

Traffic 279

Traffic Metrics Systems Strategy 279

SQL Server According to Bob

JANUARY 11, 2020

Stable Media Stable media is often confused with physical storage. SQL Server defines stable media as storage that can survive system restart or common failure. Stable media is commonly physical disk storage, but other devices and certain caching facilities qualify as well.

Servers 40

Servers Cache Media Hardware 40

The Netflix TechBlog

NOVEMBER 2, 2021

For example, when we design a new version of VMAF, we need to effectively roll it out throughout the entire Netflix catalog of movies and TV shows. This article explains how we designed microservices and workflows on top of the Cosmos platform to bolster such video quality innovations. VQS is called using the measureQuality endpoint.

Media 171

Media Innovation Metrics Latency 171

SQL Server According to Bob

JANUARY 11, 2020

​​ With new ​​ innovations ​​ come ​​ new terms, designs, ​​ and ​​ algorithms. This is different from ​​ the reference count design ​​ that was ​​ used in SQL Server 7.0 and ​​ 2000.

Servers 40

Servers Cache Database Media 40

All Things Distributed

APRIL 9, 2015

The Amazon ML console and API provide data and model visualization tools, as well as wizards to guide you through the process of creating machine learning models, measuring their quality and fine-tuning the predictions to match your application requirements. The Amazon Elastic File System. for a while already. Details on the AWS Blog.

Lambda 122

Lambda Cloud IoT AWS 122

All Things Distributed

OCTOBER 2, 2017

With these requirements in mind, and a willingness to question the status quo, a small group of distributed systems experts came together and designed a horizontally scalable distributed database that would scale out for both reads and writes to meet the long-term needs of our business. This was the genesis of the Amazon Dynamo database.

Internet 128

Internet Internet AWS Performance 128