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

Automating IT practices without integrated AIOps presents several challenges. Expect to spend time fine-tuning automation scripts as you find the right balance between automated and manual processing. This requires significant data engineering efforts, as well as work to build machine-learning models.

Artificial Intelligence 188

Artificial Intelligence Tuning Strategy Big Data 188

InfoQ

APRIL 15, 2024

He specifically delved into Venice DB, the NoSQL data store used for feature persistence. The presenter shared the lessons learned from evolving and operating the platform, including cluster management and library versioning. By Rafal Gancarz

Artificial Intelligence 105

Artificial Intelligence Big Data Data Engineering Latency 105

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