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Disambiguate Agents<->Workers.
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title: Agent & Queue
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title: Workers & Queues
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Two major components of MLOps is experiment reproducibility, and the ability to scale work to multiple machines. ClearML Agent,
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Two major components of MLOps are experiment reproducibility, and the ability to scale work to multiple machines. ClearML workers,
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coupled with execution queues, addresses both these needs.
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coupled with execution queues, address both these needs.
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The ClearML Agent is the base for **Automation** in ClearML and can be leveraged to build automated pipelines, launch custom services
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A ClearML worker is instantiated by launching a ClearML Agent, which is the base for **Automation** in ClearML and can be leveraged to build automated pipelines, launch custom services
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(e.g. a [monitor and alert service](https://github.com/allegroai/clearml/tree/master/examples/services/monitoring)) and more.
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(e.g. a [monitor and alert service](https://github.com/allegroai/clearml/tree/master/examples/services/monitoring)) and more.
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## What Does a ClearML Agent Do?
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## What Does a ClearML Agent Do?
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An agent (also referred to as a worker) allows users to execute code on any machine it's installed on, thus facilitating the
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The ClearML agent allows users to execute code on any machine it's installed on, thus facilitating the
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scaling of data science work beyond one's own machine.
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scaling of data science work beyond one's own machine.
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The agent takes care of deploying the code to the target machine as well as setting up the entire execution environment:
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The agent takes care of deploying the code to the target machine as well as setting up the entire execution environment:
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