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Service level objectives: 5 SLOs to get started

Dynatrace

Service level objectives (SLOs) provide a powerful framework for measuring and maintaining software performance, reliability, and user satisfaction. SLOs are a valuable tool for organizations to ensure the health and performance of their applications. This SLO enables a smooth and uninterrupted exercise-tracking experience.

Latency 174
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Service level objective examples: 5 SLO examples for faster, more reliable apps

Dynatrace

Service level objectives (SLOs) provide a powerful framework for measuring and maintaining software performance, reliability, and user satisfaction. Teams can build on these SLO examples to improve application performance and reliability. 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

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. Being able to canary a new route let us verify latency and error rates were within acceptable limits. This meant that data that was static (e.g.

Latency 233
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Real user monitoring vs. synthetic monitoring: Understanding best practices

Dynatrace

These development and testing practices ensure the performance of critical applications and resources to deliver loyalty-building user experiences. Real user monitoring (RUM) is a performance monitoring process that collects detailed data about users’ interactions with an application. What is real user monitoring?

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

Scalegrid

While this is a good way to get a rough estimate, your monthly cloud costs will indeed vary based on the amount of backups performed and your data transfer activity. A vast majority of the features are the same, outside of these advanced features available through the BYOC model: Virtual Private Clouds / Virtual Networks. No problem.

Cloud 242
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Why I hate MPI (from a performance analysis perspective)

John McCalpin

Bandwidth, performance analysis has two recurring themes: How fast should this code (or “simple” variations on this code) run on this hardware? If I am analyzing (apparent) performance shortfalls, how can I distinguish between cause and effect ? The MPI runtime library. in ways that are seldom transparent.

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Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

A co-worker introduced me to Craig Hanson and Pat Crain's performance mantras, which neatly summarize much of what we do in performance analysis and tuning. They are: **Performance mantras**. These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Don't do it. Do it less.