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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226
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Trace, diagnose, resolve: Introducing the Infrastructure & Operations app for streamlined troubleshooting

Dynatrace

Infrastructure and operations teams must maintain infrastructure health for IT environments. The complex interconnections in cloud-based systems make it crucial to always have a topological overview to understand dependencies. Traditional tools struggle with the intricacy of modern cloud services and containerized applications.

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Best practices and key metrics for improving mobile app performance

Dynatrace

As a result, organizations need to monitor mobile app performance metrics that are meaningful and actionable by gaining adequate observability of mobile app performance. There are many common mobile app performance metrics that are used to measure key performance indicators (KPIs) related to user experience and satisfaction.

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Observability engineering: Getting Prometheus metrics right for Kubernetes with Dynatrace and Kepler

Dynatrace

For busy site reliability engineers, ensuring system reliability, scalability, and overall health is an imperative that’s getting harder to achieve in ever-expanding, cloud-native, container-based environments. To get a more granular look into telemetry data, many analysts rely on custom metrics using Prometheus.

Metrics 175
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Measuring the importance of data quality to causal AI success

Dynatrace

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

which is difficult when troubleshooting distributed systems. Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Stream Processing: to sample or not to sample trace data?

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What is predictive AI? How this data-driven technique gives foresight to IT teams

Dynatrace

Technology and operations teams work to ensure that applications and digital systems work seamlessly and securely. They handle complex infrastructure, maintain service availability, and respond swiftly to incidents. Through predictive analytics, SREs and DevOps engineers can accurately forecast resource needs based on historical data.