blog.rmhogervorst.nl/blog/2024/09/07/message-broker-pattern-for-ml-systems
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Message Broker Pattern for ML Systems
I’ve seen a pattern in different places but it is most useful for streaming data. Data that comes in over time, with quite some volume. The core of the solution is a message broker, this could be light weight like redis1, or a heavier log-like solution like kafka2. In stead of sending data from one microservice to another through API calls, we publish data to a central place, and services subscribe to data, and publish their results back (that is why it is called PubSub; publish - subscribe).
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Message Broker Pattern for ML Systems
I’ve seen a pattern in different places but it is most useful for streaming data. Data that comes in over time, with quite some volume. The core of the solution is a message broker, this could be light weight like redis1, or a heavier log-like solution like kafka2. In stead of sending data from one microservice to another through API calls, we publish data to a central place, and services subscribe to data, and publish their results back (that is why it is called PubSub; publish - subscribe).
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Message Broker Pattern for ML Systems
I’ve seen a pattern in different places but it is most useful for streaming data. Data that comes in over time, with quite some volume. The core of the solution is a message broker, this could be light weight like redis1, or a heavier log-like solution like kafka2. In stead of sending data from one microservice to another through API calls, we publish data to a central place, and services subscribe to data, and publish their results back (that is why it is called PubSub; publish - subscribe).
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10- titleMessage Broker Pattern for ML Systems - Roel's R-tefacts
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- descriptionI’ve seen a pattern in different places but it is most useful for streaming data. Data that comes in over time, with quite some volume. The core of the solution is a message broker, this could be light weight like redis1, or a heavier log-like solution like kafka2. In stead of sending data from one microservice to another through API calls, we publish data to a central place, and services subscribe to data, and publish their results back (that is why it is called PubSub; publish - subscribe).
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