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Title Launch Observability at Netflix Scale

The Netflix TechBlog

Accurately Reflecting Production Behavior A key part of our solution is insights into production behavior, which necessitates our requests to the endpoint result in traffic to the real service functions that mimics the same pathways the traffic would take if it came from the usualcallers. We call this capability TimeTravel.

Traffic 180
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Protect your organization against zero-day vulnerabilities

Dynatrace

Typically, organizations might experience abnormal scanning activity or an unexpected traffic influx that is coming from one specific client. One way to detect zero-day attacks is by observing software behavior and identifying whether any actions are malicious.

Java 261
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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

We started seeing signs of scale issues, like: Slowness during peak traffic moments like 12 AM UTC, leading to increased operational burden. At Netflix, the peak traffic load can be a few orders of magnitude higher than the average load. Hence, the system has to withstand bursts in traffic while still maintaining the SLO requirements.

Java 211
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Evolving Regional Evacuation

The Netflix TechBlog

In the event of an isolated failure we first pre-scale microservices in the healthy regions after which we can shift traffic away from the failing one. So, if we evacuate South American traffic to North America, demand for CE and Android DRM won’t grow uniformly. evacuation traffic/nominal traffic ).

Traffic 191
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The Show Must Go On: Securing Netflix Studios At Scale

The Netflix TechBlog

Adding to the complexity, many of the checklist items themselves had a variety of different options to fulfill them (“new apps do this , but legacy apps do that”; “Java apps should use this approach , but Ruby apps should try one of these four things”… yes, there were flowcharts inside checklists.

Internet 227
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Achieving observability in async workflows

The Netflix TechBlog

Prodicle Distribution Our service is required to be elastic and handle bursty traffic. In late 2019, our team started integrating it with the rest of the ecosystem by writing a thin Java Domain graph service (DGS) to wrap the asynchronous watermarking functionality that was then in Ruby on Rails.

Traffic 166
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High Scalability

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