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Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support…

The Netflix TechBlog

Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloads by Kostas Christidis Introduction Timestone is a high-throughput, low-latency priority queueing system we built in-house to support the needs of Cosmos , our media encoding platform. Over the past 2.5

Latency 224
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Scalable Annotation Service?—?Marken

The Netflix TechBlog

The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency. Our service will be used by a lot of internal UI applications hence the latency for CRUD and search operations must be low. Teams should be able to define their data model for annotation.

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Optimize your observability pipeline for AWS Lambda serverless functions

Dynatrace

As companies accelerate digital transformation, cloud services such as AWS Lambda help companies to modernize their application architectures to quickly adapt to the needs of their customers while offloading the operational complexity to their cloud vendor.

Lambda 240
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Data ingestion pipeline with Operation Management

The Netflix TechBlog

But we cannot search or present low latency retrievals from files Etc. The solution which we present in this blog is not limited to annotations and can be used for any other domain which uses ES and Cassandra as well. Marken Architecture Marken’s architecture diagram is as follows. This is obviously very expensive.

Media 275
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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

In the time since it was first presented as an advanced Mesos framework, Titus has transparently evolved from being built on top of Mesos to Kubernetes, handling an ever-increasing volume of containers. The original assumptions and architectural choices were no longer viable.

Cache 235
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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Latency 253
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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

This architecture shift greatly reduced the processing latency and increased system resiliency. We expanded pipeline support to serve our studio/content-development use cases, which had different latency and resiliency requirements as compared to the traditional streaming use case. divide the input video into small chunks 2.