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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. ETL workflows), as well as downstream (e.g.

Systems 226
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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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What is observability? Not just logs, metrics and traces

Dynatrace

As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their multi-cloud environments. Dynatrace news. To get an analyst’s perspective, you can hear how Nancy Gohring from 451 Research defines observability: Why is observability important?

Metrics 363
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Cloud infrastructure monitoring in action: Dynatrace on Dynatrace

Dynatrace

A critical component to this success was that the Dynatrace Team itself uses the Dynatrace Platform to monitor every single Dynatrace cluster in the cloud and trusts the Dynatrace Davis AI to alert in case there are any issues, either with a new feature, a configuration change or with the infrastructure our servers are running on.

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Who will watch the watchers? Extended infrastructure observability for WSO2 API Manager

Dynatrace

Sure, cloud infrastructure requires comprehensive performance visibility, as Dynatrace provides , but the services that leverage cloud infrastructures also require close attention. Extend infrastructure observability to WSO2 API Manager. High latency or lack of responses. Soaring number of active connections.

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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. Investigating a video streaming failure consists of inspecting all aspects of a member account.

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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. This significantly increases event latency.