AWS Data Engineering Latency Scalability 
The Netflix TechBlog
NOVEMBER 22, 2019
by Shefali Vyas Dalal AWS re:Invent is a couple weeks away and our engineers & leaders are thrilled to be in attendance yet again this year! Technology advancements in content creation and consumption have also increased its data footprint. We’ve compiled our speaking events below so you know what we’ve been working on.
The Netflix TechBlog
NOVEMBER 22, 2019
by Shefali Vyas Dalal AWS re:Invent is a couple weeks away and our engineers & leaders are thrilled to be in attendance yet again this year! Technology advancements in content creation and consumption have also increased its data footprint. We’ve compiled our speaking events below so you know what we’ve been working on.
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The Netflix TechBlog
MARCH 7, 2024
In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training. Occasionally, these use cases involve terabytes of data, so we have to pay attention to performance. Internally, we use a production workflow orchestrator called Maestro.
The Netflix TechBlog
NOVEMBER 22, 2019
by Shefali Vyas Dalal AWS re:Invent is a couple weeks away and our engineers & leaders are thrilled to be in attendance yet again this year! Technology advancements in content creation and consumption have also increased its data footprint. We’ve compiled our speaking events below so you know what we’ve been working on.
The Netflix TechBlog
DECEMBER 21, 2020
By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. Some of the optimizations are prerequisites for a high-performance data warehouse. More processing resources. Increase in storage space.
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