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Scalable Annotation Service?—?Marken

The Netflix TechBlog

An example for storing both time and space based data would be an ML algorithm that can identify characters in a frame and wants to store the following for a video In a particular frame (time) In some area in image (space) A character name (annotation data) Pic 1 : Editors requesting changes by drawing shapes like the blue circle shown above.

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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

Within this paradigm, it is possible to run entire architectures without touching a traditional virtual server, either locally or in the cloud. REST APIs, authentication, databases, email, and video processing all have a home on serverless platforms. Making use of serverless architecture. Services scale to meet demand.

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Designing Instagram

High Scalability

Generating machine learning based personalized recommendations to discover new people, photos, videos, and stories relevant one’s interest. Architecture. We will use a graph database such as Neo4j to store the information. Sample Queries supported by Graph Database. Sending and receiving messages from other users.

Design 334
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Dynatrace Support for AWS Lambda Functions Powered by x86 and AWS Graviton2

Dynatrace

Dynatrace’s Lambda extension fully supports Arm-based architectures. You can use Dynatrace to monitor all your AWS Lambda functions, whether they are running on x86 or Arm architecture. According to the official AWS announcement, Graviton2-based Lambda functions offer up to 34% better price-performance improvement.

Lambda 213
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Modern applications at AWS

All Things Distributed

Still, we knew that if we wanted to expand the products and services we offered, we had to change the way we approached application architecture. The giant, monolithic "bookstore" application and giant database that we used to power Amazon.com limited our speed and agility.

AWS 164
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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. This architecture shift greatly reduced the processing latency and increased system resiliency. For example, in Reloaded the video quality calculation was implemented inside the video encoder module.

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Trends and Topics for 2022

Adrian Cockcroft

photo taken by Adrian Cockcroft A year ago I did a talk at re:Invent called Architecture Trends and Topics for 2021 , so I thought it was worth seeing how they played out and updating them for the coming year. As well as the video, there’s a long podcast where I discuss them with Mik Kersten. Sunset over Laureles Grade?—?December