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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Our tactical approach was to use Netflix-specific libraries for collecting traces from Java-based streaming services until open source tracer libraries matured. We chose Open-Zipkin because it had better integrations with our Spring Boot based Java runtime environment. Stream Processing: to sample or not to sample trace data?

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Scale Your Liferay Application by Clustering

Enprowess

And whenever one server isn’t sufficient to serve the high traffic needs of your portal, you can scale your Liferay portal by adding additional servers. It is mainly required for parallel processing, fault tolerance and load balancing, high traffic on the application. Users can tune these settings for their needs.

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Data Movement in Netflix Studio via Data Mesh

The Netflix TechBlog

CDC events can also be sent to Data Mesh via a Java Client Producer Library. However, it is paramount that we validate the complete set of identifiers such as a list of movie ids across producers and consumers for higher overall confidence in the data transport layer of choice. Please stay tuned! Endnotes ¹ Inmon, Bill.

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DBLog: A Generic Change-Data-Capture Framework

The Netflix TechBlog

Nonetheless, we found a number of limitations that could not satisfy our requirements e.g. stalling the processing of log events until a dump is complete, missing ability to trigger dumps on demand, or implementations that block write traffic by using table locks. Blocking write traffic by locking tables. Writing events to any output.

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DBLog: A Generic Change-Data-Capture Framework

The Netflix TechBlog

Nonetheless, we found a number of limitations that could not satisfy our requirements e.g. stalling the processing of log events until a dump is complete, missing ability to trigger dumps on demand, or implementations that block write traffic by using table locks. Blocking write traffic by locking tables. Writing events to any output.

Database 212