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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. Over the past 2.5

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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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Bandwidth or Latency: When to Optimise for Which

CSS Wizardry

When it comes to network performance, there are two main limiting factors that will slow you down: bandwidth and latency. Latency is defined as…. Where bandwidth deals with capacity, latency is more about speed of transfer 2. and reduction in latency. and reduction in latency. Bandwidth is defined as….

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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.

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Scalable Annotation Service?—?Marken

The Netflix TechBlog

The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency. A data model in Marken can be described using schema — just like how we create schemas for database tables etc. The databases we pick should be able to scale horizontally.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

While off-the-shelf models assist many organizations in initiating their journeys with generative AI (GenAI), scaling AI for enterprise use presents formidable challenges. It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security.

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Optimize your environment: Unveiling Dynatrace Hyper-V extension for enhanced performance and efficient troubleshooting

Dynatrace

This presents a challenge for IT operations teams, specifically in identifying and addressing performance issues or planning how to prevent future issues. This spans from the end user’s experience down to the performance of underlying database queries, and from the application code down to the hardware resources it utilizes.