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Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support…

The Netflix TechBlog

Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloads by Kostas Christidis Introduction Timestone is a high-throughput, low-latency priority queueing system we built in-house to support the needs of Cosmos , our media encoding platform.

Latency 212
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Designing Instagram

High Scalability

Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. High Level Design. When the server receives a request for an action (post, like etc.) The streaming data store makes the system extensible to support other use-cases (e.g. System Components.

Design 334
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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology.

Storage 130
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Rapid Event Notification System at Netflix

The Netflix TechBlog

To this end, we developed a Rapid Event Notification System (RENO) to support use cases that require server initiated communication with devices in a scalable and extensible manner. In this blog post, we will give an overview of the Rapid Event Notification System at Netflix and share some of the learnings we gained along the way.

Systems 334
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

You will need to know which monitoring metrics for Redis to watch and a tool to monitor these critical server metrics to ensure its health. Understanding Redis Performance Indicators Redis is designed to handle high traffic and low latency with its in-memory data store and efficient data structures.

Metrics 130
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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

As the number of Titus users increased over the years, the load and pressure on the system increased substantially. cell): Titus Job Coordinator is a leader elected process managing the active state of the system. For example, a batch workflow orchestration system may create multiple jobs which are part of a single workflow execution.

Cache 224
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SLOG: serializable, low-latency, geo-replicated transactions

The Morning Paper

SLOG: serializable, low-latency, geo-replicated transactions Ren et al., SLOG is another research system motivated by the needs of the application developer (aka, user!). Building correct applications is much easier when the system provides strict serializability guarantees. VLDB’19. Let’s make a plan.

Latency 70