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The Netflix Cosmos Platform

The Netflix TechBlog

It supports both high throughput services that consume hundreds of thousands of CPUs at a time, and latency-sensitive workloads where humans are waiting for the results of a computation. The third generation, called Reloaded , has been online for about seven years and has proven to be stable and massively scalable.

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Achieving observability in async workflows

The Netflix TechBlog

We are expected to process 1,000 watermarks for a single distribution in a minute, with non-linear latency growth as the number of watermarks increases. We wanted a scalable service that was near real-time, 2. New feature requests were adding to the maintenance burden for the team.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls. Our engineering teams tuned their services for performance after factoring in increased resource utilization due to tracing.

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HammerDB MySQL and MariaDB Best Practice for Performance and Scalability

HammerDB

On the other hand if testing MySQL or MariaDB for the ability to handle a more complex workload such as the use of stored procedures and in particular if looking to compare scalability with a traditional database then HammerDB is focused more towards testing those enterprise features. cpupower frequency-info analyzing CPU 0: . perf special.

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DBLog: A Generic Change-Data-Capture Framework

The Netflix TechBlog

Passive instances across regions are also possible, though it is recommended to operate in the same region as the database host in order to keep the change capture latencies low. Stay Tuned DBLog has additional capabilities which are not covered by this blog post, such as: Ability to capture table schemas without using locks.

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DBLog: A Generic Change-Data-Capture Framework

The Netflix TechBlog

Passive instances across regions are also possible, though it is recommended to operate in the same region as the database host in order to keep the change capture latencies low. Stay Tuned DBLog has additional capabilities which are not covered by this blog post, such as: Ability to capture table schemas without using locks.

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How to maximize CPU performance for PostgreSQL 12.0 benchmarks on Linux

HammerDB

rc3-custom #1 SMP Mon Aug 12 14:07:33 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux Welcome to Ubuntu 19.04 (GNU/Linux 5.3.0-rc3-custom Instead in this case we are hitting the ceiling of PostgreSQL scalability for this type of transactional workload. uname -a Linux ubuntu19 5.3.0-rc3-custom rc3-custom x86_64).