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Frame from AWS re:Invent 2017: How Netflix Tunes Amazon EC2 Instances for Performance (CMP325) Plays via YouTube's privacy-enhanced embed

AWS re:Invent 2017: How Netflix Tunes Amazon EC2 Instances for Performance (CMP325)

11 videos recommended on HN
YouTube
Cited on HN 3 times, 2018–2022, never outright recommended score 0
Years with an HN recommendation, 2007–2026

HN cites it as an example of workload-dependent performance tuning at scale and of Netflix's AWS practices.

A Netflix performance engineer presents how Netflix tunes EC2 instances, covering instance type choice, Xen modes, SR-IOV and kernel tuning. The goal is near bare-metal performance in the cloud.

“performance tuning is an art form as it is workload dependant” (HN, 2019)

3 citations · Talks · advanced · partly dated

3 Hacker News comments

From the HN archive; up to 20 kept per video, favoring different commenters. Recommendations first.

@scarface74 May 2018 Cites it
on HN thread Show HN: Corral – A Serverless MapReduce Framework
They use a lot of AWS services - not just virtual machines - First they use Ubuntu Linux - SES (Email) - ElasticSearch (AWS has their own managed version) - SQS (queueing system) - S3 (storage) -auto scaling Most of the optimization's they do are standard things at scale where they are tuning by measuring performance. [this video] and the slide deck from the presentation. [link] But that's even more of a reason to choose AWS, Netflix has open sourced dozens of tools specifically related to AWS. You get to take advantage of their tools and knowledge.
Netflix's AWS usage and performance tuning by measurement
@ignoramous Mar 2019 Cites it
on HN thread The creation of the io.latency block I/O controller
Well, most distributions choose saner defaults. For instance, RHEL/CentOS/AmazonLinux use noop io-scheduler by default for SSD based machines. Though, I get your point: for instance, the TCP keep-alive defaults aren't suitable for all kinds of workloads: [link] I guess, that's why performance tuning is an art form as it is workload dependant: [this video]
Performance tuning is workload dependent

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