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SLOs done right: how DevOps teams can build better service-level objectives

Dynatrace

So how do development and operations (DevOps) teams and site reliability engineers (SREs) distinguish among good, great, and suboptimal SLOs? Monitors signals The first attribute of a good SLO is the ability to monitor the four “golden signals”: latency, traffic, error rates, and resource saturation.

DevOps 211
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Since its inception , Metaflow has been designed to provide a human-friendly API for building data and ML (and today AI) applications and deploying them in our production infrastructure frictionlessly. Importantly, all the use cases were engineered by practitioners themselves.

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

The Netflix TechBlog

This allowed Android engineers to have much more control and observability over how we get our data. 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. Replay Testing Enter replay testing.

Latency 233
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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 279
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Towards a Unified Theory of Web Performance

Alex Russell

The chief effect of the architectural difference is to shift the distribution of latency within the loop. Herein lies the source of our collective anxiety about front-end architectures: traversing networks is always fraught, but the costs to deliver client-side logic to cushion users from variable network latency remain stubbornly high.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

a Netflix member via Twitter This is an example of a question our on-call engineers need to answer to help resolve a member issue?—?which Now let’s look at how we designed the tracing infrastructure that powers Edgar. Now let’s look at how we designed the tracing infrastructure that powers Edgar.

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How LinkedIn Serves Over 4.8 Million Member Profiles per Second

InfoQ

LinkedIn introduced Couchbase as a centralized caching tier for scaling member profile reads to handle increasing traffic that has outgrown their existing database cluster. The new solution achieved over 99% hit rate, helped reduce tail latencies by more than 60% and costs by 10% annually. By Rafal Gancarz

Cache 83