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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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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. The process started with manual pull of member account information that was part of the session. Stream Processing: to sample or not to sample trace data?

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Scalability Testing Tutorial: A Comprehensive Guide With Examples and Best Practices

DZone

Scalability testing is an approach to non-functional software testing that checks how well applications and infrastructure perform under increased or decreased workload conditions. The organization can optimize infrastructure costs and create the best user experience by determining server-side robustness and client-side degradation.

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

Central engineering teams enable this operational model by reducing the cognitive burden on innovation teams through solutions related to securing, scaling and strengthening (resilience) the infrastructure. All these micro-services are currently operated in AWS cloud infrastructure.

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Path to NoOps part 2: How infrastructure as code makes cloud automation attainable—and repeatable—at scale

Dynatrace

Infrastructure as code is a way to automate infrastructure provisioning and management. In this blog, I explore how Dynatrace has made cloud automation attainable—and repeatable—at scale by embracing the principles of infrastructure as code. Transparency and scalability. Infrastructure-as-code.

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What is log management? How to tame distributed cloud system complexities

Dynatrace

Log management is an organization’s rules and policies for managing and enabling the creation, transmission, analysis, storage, and other tasks related to IT systems’ and applications’ log data. Most infrastructure and applications generate logs. These two processes feed into one another.

Systems 187
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How observability, application security, and AI enhance DevOps and platform engineering maturity

Dynatrace

Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior. AI helps provide in-depth context around system issues, anomalies, and other events instead of merely identifying them.

DevOps 192