LCN 2022, 47th Annual IEEE Conference on Local Computer Networks, 26-29 September 2022, Edmonton, Canada
Cloud-native rethinks the application architecture by embracing a micro-service approach, where each microservice is packaged into containers to run in a centralized or an edge
cloud. When deploying the container running the micro-service, the tenant has to specify the amount of CPU and memory limit to run their workload. However, it is not straightforward for a tenant to know in advance the computing amount that allows
running the microservice optimally. This will impact the service performances and the infrastructure provider, particularly if the resource overprovisioning approach is used. To overcome this issue, we conduct in this paper an experimental study aiming to detect if a tenant’s configuration allows running its service optimally. We run several experiments on a cloud-native platform, using different types of applications under different resource configurations. The obtained results provide insights on how to detect and correct performance degradation due to misconfiguration of the service resource.
Type:
Conférence
City:
Edmonton
Date:
2022-09-26
Department:
Systèmes de Communication
Eurecom Ref:
6971
Copyright:
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