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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.

Traffic 181
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What are quality gates? How to use quality gates to deliver better software at speed and scale

Dynatrace

This approach supports innovation, ambitious SLOs, DevOps scalability, and competitiveness. Quality gates after load/performance testing Teams can use quality gates to evaluate performance metrics. Several tools can be used to collect metrics in load/performance testing.

Speed 196
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Netflix: A Culture of Learning

The Netflix TechBlog

Earlier posts covered the basics of A/B tests ( Part 1 and Part 2 ), core statistical concepts ( Part 3 and Part 4 ), how to build confidence in a decision ( Part 5 ), and the the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix ( Part 6 ).

Education 238
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The future of synthetic testing is in the cloud

Dynatrace

I’ve been speaking to customers over the last few months about our new cloud architecture for Synthetic testing locations and their confusion is clear. And the last thing you want to do with synthetic is introduce false positives (the bane of all synthetic testing) into the system, and yet this was happening too often.

Cloud 199
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Responsible AI must-haves for unified observability and security

Dynatrace

Dynatrace makes sure that we continually test Davis AI to ensure repeatability and ability to deliver deterministic results. Davis AI uses multidimensional baselining to automatically detect anomalies in the response times and error rates of applications and predictive AI to detect abnormalities in application traffic and service load.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

We rolled out encoding innovations such as per-title and per-shot optimizations, which provided significant quality-of-experience (QoE) improvement to Netflix members. It served as the foundation for numerous encoding innovations developed by our team. This testing stage took about two weeks. 264, AV1, etc.).

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Experimentation is a major focus of Data Science across Netflix

The Netflix TechBlog

Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix, including how our platform investments support running tests at scale while enabling innovation. What more can we learn from this test, to inform the next one?” Curious to learn more?