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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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Performance Tuning Java Applications in Linux

DZone

You may also like: How to Properly Plan JVM Performance Tuning. While Performance Tuning an application both Code and Hardware running the code should be accounted for. In this blog post, we shall go over various aspects that have to be taken care of to extract maximum performance out of a Java Application running on Linux.

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Privacy spotlight: Control compliance in Dynatrace with multiple layers of sensitive data masking

Dynatrace

This includes digging through each monitored data source and adding tags to the sensitive data points; this process is usually expensive, exhausting, error-prone, and unscalable. The selected rules can be configured for a whole environment or, more granularly, for specific process groups.

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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

This blog was originally published in August 2018 and was updated in May 2023. Out of the box, the default PostgreSQL configuration is not tuned for any particular workload. It is primarily the responsibility of the database administrator or developer to tune PostgreSQL according to their system’s workload.

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The Dynatrace journey toward DORA compliance

Dynatrace

This blog post describes how we’re aligning our efforts with the upcoming changes. The Dynatrace data-centric approach ensures compliance isn’t a burden; it’s an opportunity to fine-tune operations. As a strong partner of European financial institutions, Dynatrace is preparing for DORA requirements.

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