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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience. This approach has a handful of benefits.

Traffic 339
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Example use case: Content Knowledge Graph Our knowledge graph of the entertainment world encodes relationships between titles, actors and other attributes of a film or series, supporting all aspects of business at Netflix. In other cases, it is more convenient to share the results via a low-latency API.

Systems 226
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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

This allows the app to query a list of “paths” in each HTTP request, and get specially formatted JSON (jsonGraph) that we use to cache the data and hydrate the UI. For example, the artwork service is separate from the video metadata service, but we need the data from both in the detail key. Replay Testing Enter replay testing.

Latency 233
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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

Cache 251
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Dynamic Content Vs. Static Content: What Are the Main Differences

IO River

They cache static content and enable lightning-fast delivery around the globe.This symbiosis reduces server load, boosts loading times, and ensures efficient content distribution. Content Delivery Networks (CDNs), web browsers, and proxy servers can store static files in their caches. For example, consider tools like ChatGPT.

Cache 52
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Optimizing CDN Architecture: Enhancing Performance and User Experience

IO River

CDNs cache content on edge servers distributed globally, reducing the distance between users and the content they want.‍CDNs use load-balancing techniques to distribute incoming traffic across multiple servers called Points of Presence (PoPs) which distribute content closer to end-users and improve overall performance.