Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. better cluster resource utilization.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Smashing Magazine

JANUARY 6, 2020

It will help you build up a company-tailored case study with real data. Furthermore, using data from case studies and experiments published on WPO Stats will help increase sensitivity for business about why performance matters, and what impact it has on user experience and business metrics. Large preview ). Large preview ).

Performance 145

Performance Cache Network Metrics 145

The Symphonia

JANUARY 21, 2019

we help people create a Continuous Deployment pipeline before they start getting into the nitty-gritty of Serverless Architecture. In this article I explain briefly what these tools are, and where I think their strengths and weaknesses lie. CodePipeline is their deployment pipeline service. Build + Test ? CodeBuild is 0.5

AWS 40

AWS Open Source Lambda Serverless 40

Enprowess

AUGUST 6, 2021

Through this article, we’ll answer all of your common questions on technologies: React and Nodejs. Here’s after I thought of writing an infatuated article that covers these queries. This article will notify you of some reasons why you should use Nodejs with React. Is it ok to combine Nodejs with React?

Development 52

Development Virtualization Servers Website 52

Smashing Magazine

JANUARY 7, 2019

It will help you build up a company-tailored case study with real data. Furthermore, using data from case studies and experiments published on WPO Stats will help increase sensitivity for business about why performance matters, and what impact it has on user experience and business metrics. Large preview ).

Performance 103

Performance Cache Metrics Network 103

Alex Russell

MARCH 6, 2021

This step-change, along with improvements to streaming compilation , has helped to ensure that users are less likely to notice the unreasonably-sized JS payloads that "modern" toolchains generate more often than not. Good news has consistently come from the steady pace of browser progress. A 2021 Global Baseline.

Performance 124

Performance Network Cache Metrics 124

The Netflix TechBlog

NOVEMBER 2, 2021

Moorthy and Zhi Li Introduction Measuring video quality at scale is an essential component of the Netflix streaming pipeline. Perceptual quality measurements are used to drive video encoding optimizations , perform video codec comparisons , carry out A/B testing and optimize streaming QoE decisions to mention a few.

Media 171

Media Innovation Metrics Latency 171

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. 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

Nick Desaulniers

APRIL 18, 2014

The tongue of Eden was like a flawless glass; a light of total understanding streamed through it. This reminds me of how seemingly meaningless noop instructions can keep a processor’s pipeline full by preventing stalls, though a pipeline stall doesn’t change the correctness of a program, so it’s an imperfect analogy.

C++ 98

C++ Programming Code Virtualization 98

The Netflix TechBlog

MARCH 1, 2021

A Cosmos service This article will explain why we built Cosmos, how it works and share some of the things we have learned along the way. The first generation of this system went live with the streaming launch in 2007. The centralized data model that had served us well when we were a small team became a liability. Productivity?—?Local

Serverless 228

Serverless Media Latency Social Media 228

Abhishek Tiwari

JULY 20, 2019

Don't be trapped by dogma A lot has been said and written about why something worked for Spotify may not apply to your organisation, and the purpose of this article is not to go in those discussions but to highlight practical issues with these models. Just like architecture, teams should be loosely coupled or better completely de-coupled.

Engineering 61

Engineering Retail Airlines Healthcare 61