The Netflix TechBlog

JULY 26, 2021

Netflix is known for its loosely coupled microservice architecture and with a global studio footprint, surfacing and connecting the data from microservices into a studio data catalog in real time has become more important than ever. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 253

Big Data Government Analytics Processing 253

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. I wanted to understand how I could tune Dynatrace’s problem detection, but to do that I needed to understand the situation first. To achieve that I took two approaches: Visualizing historic problem data via a “Swimlane Visualization”.

Tuning 260

Tuning Architecture Monitoring Big Data 260

Dynatrace

FEBRUARY 16, 2023

The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes. Grail data lakehouse delivers massively parallel processing for answers at scale Modern cloud-native computing is constantly upping the ante on data volume, variety, and velocity.

Analytics 176

Analytics Innovation Metrics Database 176

The Netflix TechBlog

DECEMBER 21, 2020

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. Then deep dive into the merging use case of AutoOptimize and share some results and benefits.

Storage 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

JUNE 7, 2021

Berkeley Packet Filter (BPF) is an in-kernel execution engine that processes a virtual instruction set, and has been extended as eBPF for providing a safe way to extend kernel functionality. After several iterations of the architecture and some tuning, the solution has proven to be able to scale. What is BPF?

Network 325

Network Transportation AWS Cloud 325

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 202

Java Scalability Traffic Architecture 202

Percona

JANUARY 19, 2023

For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant. In this blog post, we will review key topics to consider for managing large datasets more efficiently in MySQL. InnoDB will sort the data in primary key order, and that will serve to reference actual data pages on disk.

Open Source 85

Open Source Storage Database Big Data 85

Percona

JANUARY 14, 2019

However, ClickHouse is super efficient for timeseries and provides “sharding” out of the box (scalability beyond one node). Although such databases can be very efficient with counts and averages, some queries will be slow or simply non existent. Inserts are efficient for bulk inserts only. Processed 4.15

Database 40

Database Analytics Blockchain Healthcare 40

O'Reilly

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Hardware 102

Hardware Storage Big Data Blockchain 102