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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.

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Black Friday traffic exposes gaps in observability strategies

Dynatrace

What’s the problem with Black Friday traffic? But that’s difficult when Black Friday traffic brings overwhelming and unpredictable peak loads to retailer websites and exposes the weakest points in a company’s infrastructure, threatening application performance and user experience. Why Black Friday traffic threatens customer experience.

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Better dashboarding with Dynatrace Davis AI: Instant meaningful insights

Dynatrace

The market is saturated with tools for building eye-catching dashboards, but ultimately, it comes down to interpreting the presented information. For example, if you’re monitoring network traffic and the average over the past 7 days is 500 Mbps, the threshold will adapt to this baseline.

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Title Launch Observability at Netflix Scale

The Netflix TechBlog

Accurately Reflecting Production Behavior A key part of our solution is insights into production behavior, which necessitates our requests to the endpoint result in traffic to the real service functions that mimics the same pathways the traffic would take if it came from the usualcallers. We call this capability TimeTravel.

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Title Launch Observability at Netflix Scale

The Netflix TechBlog

They allow us to verify whether titles are presented as intended and investigate any discrepancies. However, taking this approach also presents several challenges: Catching Issues Ahead of Time: Logging primarily addresses post-launch scenarios, as logs are generated only after titles are shown to members.

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How To Implement Video Information and Editing APIs in Java

DZone

In the past 15+ years, online video traffic has experienced a dramatic boom utterly unmatched by any other form of content. It must be said that this video traffic phenomenon primarily owes itself to modernizations in the scalability of streaming infrastructure, which simply weren’t present fifteen years ago.

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Introducing Impressions at Netflix

The Netflix TechBlog

It filters out any invalid entries and enriches the valid ones with additional metadata, such as show or movie title details, and the specific page and row location where each impression was presented to users. This refined output is then structured using an Avro schema, establishing a definitive source of truth for Netflixs impression data.

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