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Meta is introducing Velox, an open source unified execution engine aimed at accelerating data management systems and streamlining their development. Velox is under active development. Experimental results from our paper published at the International Conference on Very Large Data Bases (VLDB) 2022 show how Velox improves efficiency and consistency in data management systems. Velox helps [...] Read More... The post Introducing Velox: An open source unified execution engine appeared first on Engineering at Meta. http://dlvr.it/SXXv99

When we focus on minimizing errors and downtime here at Meta, we place a lot of attention on service-level indicators (SLIs) and service-level objectives (SLOs). Consider Instagram, for example. There, SLIs represent metrics from different product surfaces, like the volume of error response codes to certain endpoints, or the number of successful media uploads. Based [...] Read More... The post Improving Meta’s SLO workflows with data annotations appeared first on Engineering at Meta. http://dlvr.it/SXR48r

A touring alien from a galaxy far, far away is an avid Instagram user. Her Instagram Feed is dominated by: Friends and family posts Some space travel magazines A few general news accounts Lots of science fiction blogs She logs in, scrolls through her feed gently — catching up with friends and family, keeping pace [...] Read More... The post How Instagram suggests new content appeared first on Engineering at Meta. http://dlvr.it/SWWyVv

Many of Meta’s products, such as search and language translations, utilize AI models to continuously improve user experiences. As the performance of hardware we use to support training infrastructure increases, we need to scale our data ingestion infrastructure accordingly to handle workloads more efficiently. GPUs, which are used for training infrastructure, tend to double in [...] Read More... The post Scaling data ingestion for machine learning training at Meta appeared first on Engineering at Meta. http://dlvr.it/SWPMWQ