Can AI Models Be Used for Autoscaling Instead of Just Thresholds?

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Asked By CuriousCoder42 On

I'm curious if there are any AI models designed for autoscaling in environments like Kubernetes. Typically, systems rely on straightforward thresholds, like scaling when CPU utilization hits 70%. However, I'm wondering if there are more advanced methods that use AI to determine scaling needs, potentially by analyzing patterns in usage data. I came across a concept called HPA+ but couldn't find much information. Any insights into relevant datasets, research papers, or approaches would be greatly appreciated!

1 Answer

Answered By TechExplorer99 On

What do you think AI can achieve that a set threshold can't? What's your motivation for moving away from thresholds?

ResearchNerd88 -

I believe AI can analyze usage patterns to scale resources proactively, rather than just reacting once a threshold is crossed. For instance, if CPU usage is nearing a threshold, an AI model could intervene before reaching that point, which might save on unnecessary resource allocation. I'm researching this to see if such an approach is practical.

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