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How To Design For High-Traffic Events And Prevent Your Website From Crashing

Smashing Magazine

How To Design For High-Traffic Events And Prevent Your Website From Crashing How To Design For High-Traffic Events And Prevent Your Website From Crashing Saad Khan 2025-01-07T14:00:00+00:00 2025-01-07T22:04:48+00:00 This article is sponsored by Cloudways Product launches and sales typically attract large volumes of traffic.

Traffic 86
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Optimising for High Latency Environments

CSS Wizardry

This gives fascinating insights into the network topography of our visitors, and how much we might be impacted by high latency regions. Round-trip-time (RTT) is basically a measure of latency—how long did it take to get from one endpoint to another and back again? What is RTT? Where Does CrUX’s RTT Data Come From?

Latency 244
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Migrating Critical Traffic At Scale with No Downtime?—?Part 2

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 2 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. This is where large-scale system migrations come into play.

Traffic 282
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Best Practices for Scaling RabbitMQ

Scalegrid

Scaling RabbitMQ ensures your system can handle growing traffic and maintain high performance. Optimizing RabbitMQ performance through strategies such as keeping queues short, enabling lazy queues, and monitoring health checks is essential for maintaining system efficiency and effectively managing high traffic loads.

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RabbitMQ vs. Kafka: Key Differences

Scalegrid

RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. Its design prioritizes high availability and efficient data transfer with minimal overhead, making it a practical choice for handling real-time data pipelines and distributed event processing.

Latency 147
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Title Launch Observability at Netflix Scale

The Netflix TechBlog

The Challenge of Title Launch Observability As engineers, were wired to track system metrics like error rates, latencies, and CPU utilizationbut what about metrics that matter to a titlessuccess? How can we design systems that recognize these nuances and empower every title to shine and bring joy to ourmembers?

Traffic 168
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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

A quick canary test was free of errors and showed lower latency, which is expected given that our standard canary setup routes an equal amount of traffic to both the baseline running on 4xl and the canary on 12xl. What’s worse, average latency degraded by more than 50%, with both CPU and latency patterns becoming more “choppy.”

Hardware 363