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. Key challenges. Performance.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Abhishek Tiwari

JULY 12, 2018

Building data pipelines can offer strategic advantages to the business. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines. Data pipeline initiatives are generally unfinished projects. In this post, we will discuss why you should avoid building data pipelines in first place.

Latency 63

Latency Analytics Scalability Engineering 63

The Netflix TechBlog

FEBRUARY 9, 2022

JAR) form to be executed as part of the user defined data pipeline. data pipeline ?—?a DAG) for the purpose of transforming data using some business logic. Netflix homegrown CLI tool for data pipeline management. task, an atomic unit of data transformation logic, a non-separable execution block in the workflow chain.

Storage 201

Storage Data Engineering Testing Code 201

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 100

AWS Entertainment Open Source Benchmarking 100

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 100

AWS Entertainment Open Source Benchmarking 100

All Things Distributed

AUGUST 24, 2012

The AWS team launched this week Amazon Glacier , a cold storage archive service at the very low price point of $0.01 Which makes this week a good moment to read up on some of the historical work around the costs of data engineering. I am in the midst of my South America tour in the beautiful but very cold Santiago, Chile.

Storage 108

Storage Hardware AWS Data Engineering 108

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. Then we perform frequent batch ETL from application databases to a data warehouse. Classic ETL. then ELT is a more preferred option.

Big Data 40

Big Data Retail Storage Google 40

The Symphonia

JUNE 19, 2018

Some in-depth and unusual client work (want to encrypt a petabyte of S3 storage? From data engineering, to cost management, via conversations about team dynamics and architecture, we like to get involved with all-things-cloud-and-DevOps related at our clients. Unlike the temperature outside. 2 Day Serverless CD Masterclass?

Serverless 40

Serverless AWS DevOps Open Source 40

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 37

AWS Entertainment Open Source Benchmarking 37

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. There are several emerging data trends that will define the future of ETL in 2018. A common theme across all these trends is to remove the complexity by simplifying data management as a whole.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

InfoQ

JANUARY 25, 2023

In this article, Rogerio Robetti discusses the challenges in auto-scaling stateful storage systems and proposes an opinionated design solution to automatically scale up (vertical) and scale out (horizontal) from a single node up to several nodes in a cluster with minimum configuration and interference of the operator. By Rogerio Robetti

Design 144

Design Systems Storage Data Engineering 144

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data.

Cloud 137

Cloud Big Data AWS Analytics 137