Architecture Data Engineering Training Tuning 
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).
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. AI that is based on machine learning needs to be trained.
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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.
The Netflix TechBlog
NOVEMBER 20, 2023
IPS enables users to continue to use the data processing patterns with minimal changes. Introduction Netflix relies on data to power its business in all phases. As our business scales globally, the demand for data is growing and the needs for scalable low latency incremental processing begin to emerge. past 3 hours or 10 days).
Abhishek Tiwari
JULY 20, 2019
The engineering organisation described may not work for you because of a team of 8-10 people is still a very big overhead. In this model, software architecture and code ownership is a reflection of the organisational model. Because you are changing team composition, you need robust norms of conduct and engineering practices in place.
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