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Scalable Annotation Service?—?Marken

The Netflix TechBlog

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. Marken architecture Above picture represents the block diagram of the architecture for our service. zookeeper service, internationalization service etc.

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Presentation: Maximizing Performance and Efficiency in Financial Trading Systems through Vertical Scalability and Effective Testing

InfoQ

Peter Lawrey discusses achieving vertical scalability by minimizing accidental complexity and using an event-driven architecture. By Peter Lawrey

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Presentation: Sigstore: Secure and Scalable Infrastructure for Signing and Verifying Software

InfoQ

Billy Lynch, Zack Newman discuss the architecture and internals of Sigstore and keyless signing, along with the security considerations that drove the design. By Billy Lynch, Zack Newman

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Choreography Pattern: Optimizing Communication in Distributed Systems

DZone

In today's rapidly evolving technology landscape, it's common for applications to migrate to the cloud to embrace the microservice architecture. While this architectural approach offers scalability, reusability, and adaptability, it also presents a unique challenge: effectively managing communication between these microservices.

Systems 274
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Presentation: Managing 238M Memberships at Netflix

InfoQ

Surabhi Diwan discusses how the Netflix’ membership team outgrew many of its technology and architectural choices as memberships went from a few hundred thousand to 200 million. By Surabhi Diwan

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Presentation: Performance: Adventures in Thread-per-Core Async with Redpanda and Seastar

InfoQ

John Spray describes an experience of building high performance systems with C++20 in an asynchronous runtime, and explores the challenges & tradeoffs in adopting a thread-per-core architecture. By John Spray

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Presentation: Effective Performance Engineering at Twitter-Scale

InfoQ

Yao Yue recapitulates scaling a project at Twitter while summarizing some key lessons learned about effective performance engineering. By Yao Yue