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Anyscale details Ray Serve async inference for video-indexing service

Anyscale has detailed a practical implementation of its asynchronous inference feature within Ray Serve, demonstrating its use in a video-indexing service. This service leverages message queues like Redis or RabbitMQ for background processing, enabling long-running tasks such as video analysis to be handled efficiently without blocking client requests. The architecture includes separate deployments for ingress, video consumption and chunking, and GPU-based embedding, with autoscaling based on queue depth and GPU load. AI

IMPACT Demonstrates how to build robust, scalable ML inference pipelines for long-running tasks, improving efficiency and reliability.

RANK_REASON Blog post detailing a practical application of existing infrastructure (Ray Serve's async inference feature).

Read on Anyscale blog →

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Anyscale details Ray Serve async inference for video-indexing service

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  1. Anyscale blog TIER_1 English(EN) ·

    Async inference in practice: a video-indexing service on Ray Serve

    Building a real video indexing service on Ray Serve asynchronous inference, and benchmarking it against Amazon SageMaker for scaling, reliability and latency.