Availability Data Engineering Scalability 
The Netflix TechBlog
MARCH 5, 2019
While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. In the Efficiency space, our data teams focus on transparency and optimization.
InfoQ
AUGUST 3, 2023
AWS recently announced the general availability (GA) of Amazon EC2 P5 instances powered by the latest NVIDIA H100 Tensor Core GPUs suitable for users that require high performance and scalability in AI/ML and HPC workloads. The GA is a follow-up to the earlier announcement of the development of the infrastructure.
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InfoQ
JULY 14, 2023
Mei-Chin Tsai, Vinod discuss the internal architecture of Azure Cosmos DB and how it achieves high availability, low latency, and scalability. By Mei-Chin Tsai, Vinod Sridharan
The Netflix TechBlog
MARCH 7, 2024
Importantly, all the use cases were engineered by practitioners themselves. These integrations are implemented through Metaflow’s extension mechanism which is publicly available but subject to change, and hence not a part of Metaflow’s stable API yet. Internally, we use a production workflow orchestrator called Maestro.
The Netflix TechBlog
SEPTEMBER 18, 2020
The Engineer enjoys making data available by piping it in from new sources in optimal ways, building robust data models, prototyping systems, and doing project-specific engineering. They also have an eye for principled engineering, i.e. managing the data under the surface.
The Netflix TechBlog
MARCH 25, 2019
We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.
The Netflix TechBlog
OCTOBER 18, 2022
As Big data and ML became more prevalent and impactful, the scalability, reliability, and usability of the orchestrating ecosystem have increasingly become more important for our data scientists and the company. Meson was based on a single leader architecture with high availability.
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