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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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Service level objectives: 5 SLOs to get started

Dynatrace

Certain SLOs can help organizations get started on measuring and delivering metrics that matter. Fitness app : The fitness app should offer a response time of less than 500 milliseconds for exercise tracking and data recording. This SLO enables a smooth and uninterrupted exercise-tracking experience. The Apdex score of 0.85

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

Dynatrace

Certain service-level objective examples can help organizations get started on measuring and delivering metrics that matter. Fitness app : The fitness app should offer a response time of less than 500 milliseconds for exercise tracking and data recording. This SLO enables a smooth and uninterrupted exercise-tracking experience.

Traffic 173
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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

To prepare ourselves for a big change in the tech stack of our endpoint, we decided to track metrics around the time taken to respond to queries. After some consultation with our backend teams, we determined the most effective way to group these metrics were by UI screen. Replay Testing Enter replay testing.

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Real user monitoring vs. synthetic monitoring: Understanding best practices

Dynatrace

RUM gathers information on a variety of performance metrics. Data collected on page load events, for example, can include navigation start (when performance begins to be measured), request start (right before the user makes a request from the server), and speed index metrics (measure page load speed). Real user monitoring limitations.

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Bring Your Own Cloud (BYOC) vs. Dedicated Hosting at ScaleGrid

Scalegrid

Each of these models is suitable for production deployments and high traffic applications, and are available for all of our supported databases, including MySQL , PostgreSQL , Redis™ and MongoDB® database ( Greenplum® database coming soon). This can result in significant cost savings for high traffic applications. No problem.

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Automating chaos experiments in production

The Morning Paper

Moreover, just like an A/B test, we’ll be collecting metrics while the experiment is underway and performing statistical analysis at the end to interpret the results. Two failure modes we focus on are a service becoming slower (increase in response latency) or a service failing outright (returning errors).

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