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1. Streamlining Membership Data Engineering at Netflix with Psyberg

The Netflix TechBlog

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions.

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Presentation: Azure Cosmos DB: Low Latency and High Availability at Planet Scale

InfoQ

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

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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

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. This presents the advantages of the integrated intelligence of the rule-based classifier and the ML service.

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What is IT automation?

Dynatrace

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. Automating IT practices without integrated AIOps presents several challenges.

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QCon London: Lessons Learned From Building LinkedIn’s AI/ML Data Platform

InfoQ

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

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Sustainability at AWS re:Invent 2022 All the talks and videos I could find…

Adrian Cockcroft

COM201 Being ethical in tech: Sustainability tips for work and life — no video, but here is a video of Aerin Booth presenting an earlier version of the talk. Good example, well presented interesting new material. Engaging presentation on an important topic, with some good advice on optimizing ML workloads.

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

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. Give us a holler if you are interested in a thought exchange.