Architecture Big Data Data Engineering Engineering 
The Netflix TechBlog
JUNE 1, 2021
Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. What drew you to Netflix?
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.
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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. Rule Execution Engine is responsible for matching the collected logs against a set of predefined rules.
The Netflix TechBlog
NOVEMBER 20, 2023
It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. past 3 hours or 10 days).
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.
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. Big data automation tools. Batch process automation.
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.
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