National Repository of Grey Literature 1 records found  Search took 0.00 seconds. 
Support for Predictive Application Autoscaling on Kubernetes Platform
Fridrich, David ; Pavela, Jiří (referee) ; Rogalewicz, Adam (advisor)
The goal of this work is to create a new interface that will allow users to process collected metrics for scaling according to a formula (e.g. average value, mathematical equations, conditional statements) defined by a user. It also allows users to use an external interface for connecting KEDA to a component that defines its own scaling behavior, with which the user can achieve more complex solutions like automated predictive scaling of applications on Kubernetes platform. I solved the selected problems by modifying the KEDA core by implementing a new interface for scaling according to a custom formula with arithmetic and conditional expressions and the ability to connect a custom external remote method for calculating metrics using gRPC technology. The created solution provides a more flexible way to process metrics and also allows user to implement their own methods.

Interested in being notified about new results for this query?
Subscribe to the RSS feed.