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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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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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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

Rather than listing the concepts, function calls, etc, available in Citus, which frankly is a bit boring, I’m going to explore scaling out a database system starting with a single host. I won’t cover all the features but show just enough that you’ll want to see more of what you can learn to accomplish for yourself.

Database 107
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Redis® is an in-memory database that provides blazingly fast performance. This makes it a compelling alternative to disk-based databases when performance is a concern. Redis returns a big list of database metrics when you run the info command on the Redis shell. This blog post lists the important database metrics to monitor.

Metrics 130
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Redis® Monitoring Strategies for 2024

Scalegrid

Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. Redis® Monitoring Essentials Ensuring the performance, reliability, and safety of a Redis® database requires active monitoring. Monitoring tools should also be considered when setting up your Redis® database.

Strategy 130
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues. The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources.

Cache 201
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Designing Instagram

High Scalability

The streaming data store makes the system extensible to support other use-cases (e.g. System Components. The system will comprise of several micro-services each performing a separate task. The system will comprise of several micro-services each performing a separate task. Component Design. Posting on Instagram.

Design 334