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Model-based performance engineering approaches help for up-front engineering of elasticity policies that control the adjustment of resources at runtime. Specifically, the Palladio approach allows stakeholders in the development process to model the application from various viewpoints and make performance predictions. This paper demonstrates Slingshot for designing elasticity policies for cloud-native applications. We make two contributions that build upon the Palladio approach. One contribution is a separate view-point for modeling elasticity policies for cloud-native applications. 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Finally, we present the scalability of the current solution assuming a particular autoscaling policy. Results of the calibration show high variability of the ProtoCom library when executed in a cloud environment. 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