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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

This introductory blog focuses on an overview of our journey. Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process.

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

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Data Mesh?—?A Data Movement and Processing Platform @ Netflix

The Netflix TechBlog

A Data Movement and Processing Platform @ Netflix By Bo Lei , Guilherme Pires , James Shao , Kasturi Chatterjee , Sujay Jain , Vlad Sydorenko Background Realtime processing technologies (A.K.A stream processing) is one of the key factors that enable Netflix to maintain its leading position in the competition of entertaining our users.

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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

These are the goals of AI observability and data observability, a key theme at Dynatrace Perform 2024 , the observability provider’s annual conference, which takes place in Las Vegas from January 29 to February 1, 2024. Join us at Dynatrace Perform 2024 , either on-site or virtuall y, to explore these themes further.

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Perform 2023 Guide: Organizations mine efficiencies with automation, causal AI

Dynatrace

These are just some of the topics being showcased at Perform 2023 in Las Vegas. Perform 2023 news At Perform 2023 in Las Vegas, the headliner theme is IT automation. How a data lakehouse brings data insights to life — blog While logs create yet another silo for IT managers, they also provide a goldmine of data.

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Debugging Apache Spark Performance Using Explain Plan

DZone

In the world of data processing, Apache Spark has established itself as a powerful and versatile framework. However, as the volume and complexity of data continue to grow, ensuring optimal performance becomes paramount.

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Unlock the observability value of log data with processing at scale

Dynatrace

Log files provide an unparalleled level of detail about the performance of your software. Advanced processing on your observability platform unlocks the full value of log data. Dynatrace now includes powerful log-processing capabilities for all types of log data. Perform basic calculations on log attributes.