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Varun Srinivasan pfp
Varun Srinivasan
@v
Anyone here worked on an eng team that processed more than 100M background jobs /day? Starting to run into issues with our setup. Looking for ideas on what people typically turn to at this scale.
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Ethspresso ๐ŸšŒ๐Ÿ”ต๐ŸŽฉ pfp
Ethspresso ๐ŸšŒ๐Ÿ”ต๐ŸŽฉ
@ethspresso.eth
Airflow + K8s on bare metal is serving us well. At smaller scale than this though, something like 100k+ daily jobs of varying size and runtime. We use this for everything from ML training jobs to data transformations and 3rd party integrations. As @jacek mentioned, streaming is a good idea, for certain use-cases.
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Samuel ใƒ„ pfp
Samuel ใƒ„
@samuellhuber.eth
regarding Airflow in K8s at Scale here's Shopify doing it https://shopify.engineering/lessons-learned-apache-airflow-scale
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