The Netflix TechBlog

MARCH 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

Tuning 210

Tuning Efficiency Big Data Engineering 210

Dynatrace

JULY 6, 2022

As organizations continue to adopt multicloud strategies, the complexity of these environments grows, increasing the need to automate cloud engineering operations to ensure organizations can enforce their policies and architecture principles. By tuning workflows, you can increase their efficiency and effectiveness.

Artificial Intelligence 182

Artificial Intelligence Tuning Strategy Big Data 182

The Netflix TechBlog

OCTOBER 18, 2022

Meson was based on a single leader architecture with high availability. Usability Netflix is a data-driven company, where key decisions are driven by data insights, from the pixel color used on the landing page to the renewal of a TV-series. Figure 1 shows the high-level architecture.

Java 202

Java Scalability Traffic Architecture 202

The Netflix TechBlog

NOVEMBER 20, 2023

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. Users configure the workflow to read the data in a window (e.g. The window is set based on users’ domain knowledge so that users have a high confidence that the late arriving data will be included or will not matter (i.e.

Processing 210

Processing Big Data Efficiency Engineering 210

The Netflix TechBlog

MARCH 25, 2019

Now, imagine yourself in the role of a software engineer responsible for a micro-service which publishes data consumed by few critical customer facing services (e.g. You are about to make structural changes to the data and want to know who and what downstream to your service will be impacted.

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

The Netflix TechBlog

MAY 26, 2020

And in order to gain visibility into these logs, we need to somehow ingest and enrich this data. It is easier to tune a large Spark job for a consistent volume of data. In other words, we are able to ensure that our Spark app does not “eat” more data than it was tuned to handle. We named this library Sqooby.

Network 150

Network Tuning AWS Big Data 150

The Netflix TechBlog

DECEMBER 21, 2020

This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture. Some of the optimizations are prerequisites for a high-performance data warehouse. Orient: Gather tuning parameters for a particular table that changed.

Storage 203

Storage Latency Efficiency Data Engineering 203