From the course: Complete Guide to Azure AI for ML Engineers by Microsoft Press
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Learn about monitoring - Azure Tutorial
From the course: Complete Guide to Azure AI for ML Engineers by Microsoft Press
Learn about monitoring
- [Instructor] The last thing that we'll cover in this lesson is monitoring. And that rounds out the whole MLOps lifecycle or the AIOps lifecycle, whichever one you want to call it. So when we think about monitoring, this is how we actually watch the behavior of the application or the model in production. So you'll have a number of tools available that will help you look for some of the things that we discussed with performance tuning, but you always want to have some type of monitoring in place for your AI applications. Monitoring is a huge part of AIOps. So when you think about AI, you might be more focused with how to get the best model, what's the best tool to use, where's your data coming from, and all of those are very important. You couldn't have the AI application without them, but there's a whole back inside of this AIOps model where you are, you're done with all of that upfront data, model, code stuff and now your application is interacting with users or users are…
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