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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Our tactical approach was to use Netflix-specific libraries for collecting traces from Java-based streaming services until open source tracer libraries matured.

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Data Movement in Netflix Studio via Data Mesh

The Netflix TechBlog

Data Mesh provides a drag-and-drop, self-service user interface for exploring sources and creating pipelines so that users can focus on delivering business value without having to worry about managing and scaling complex data streaming infrastructure. CDC events can also be sent to Data Mesh via a Java Client Producer Library.

Big Data 253
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DBLog: A Generic Change-Data-Capture Framework

The Netflix TechBlog

One which: interleaves log with dump events so that both can make progress allows to trigger dumps at any time does not use table locks uses standardized database features DBLog Framework DBLog is a Java-based framework, able to capture changes in real-time and to take dumps. The database is sending them to a transport that DBLog can consume.

Database 197
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DBLog: A Generic Change-Data-Capture Framework

The Netflix TechBlog

One which: interleaves log with dump events so that both can make progress allows to trigger dumps at any time does not use table locks uses commonly available database features DBLog Framework DBLog is a Java-based framework, able to capture changes in real-time and to take dumps. We use the term ‘ change log’ for that transport.

Database 212