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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.

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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

For each route we migrated, we wanted to make sure we were not introducing any regressions: either in the form of missing (or worse, wrong) data, or by increasing the latency of each endpoint. If we pare down the problem to absolute basics, we essentially have two services returning JSON. Replay Testing Enter replay testing.

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Service level objective examples: 5 SLO examples for faster, more reliable apps

Dynatrace

Response time Response time refers to the total time it takes for a system to process a request or complete an operation. This ensures that customers can quickly navigate through product listings, add items to their cart, and complete the checkout process without experiencing noticeable delays. or above for the checkout process.

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Service level objectives: 5 SLOs to get started

Dynatrace

Response time Response time refers to the total time it takes for a system to process a request or complete an operation. This ensures that customers can quickly navigate through product listings, add items to their cart, and complete the checkout process without experiencing noticeable delays. or above for the checkout process.

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Real user monitoring vs. synthetic monitoring: Understanding best practices

Dynatrace

Real user monitoring (RUM) is a performance monitoring process that collects detailed data about users’ interactions with an application. RUM, however, has some limitations, including the following: RUM requires traffic to be useful. Complex transaction and process monitoring that might have deeper dependencies.

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Taiji: managing global user traffic for large-scale Internet services at the edge

The Morning Paper

Taiji: managing global user traffic for large-scale internet services at the edge Xu et al., It’s another networking paper to close out the week (and our coverage of SOSP’19), but whereas Snap looked at traffic routing within the datacenter, Taiji is concerned with routing traffic from the edge to a datacenter. SOSP’19.

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Automating chaos experiments in production

The Morning Paper

They use a combination of timeouts, retries, and fallbacks to try to mitigate the effects of these failures, but these don’t get exercised as often as the happy path, so how can we be confident they’ll work as intended when called upon? If ChAP detects excessive customer impact during an experiment, the experiment is stopped immediately.

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