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Data-intensive container-based cloud applications have become popular withthe increased use cases in the Internet of Things domain. Challenges arise whenengineering such applications to meet quality requirements, both classical oneslike performance and emerging ones like elasticity and resilience. There is alack of reference use cases, applications, and experiences when prototypingsuch applications that could benefit the research community. Moreover, it ishard to generate realistic and reliable workloads that exercise the resourcesaccording to a specification. Hence, designing reference applications thatwould exhibit similar performance behavior in such environments is hard. Inthis paper, we present a work in progress towards a reference use case andapplication for data-intensive containerized cloud applications having anindustrial motivation. Moreover, to generate reliable CPU workloads we make useof ProtoCom, a well-known library for the generation of resource demands, andreport the performance under various quality requirements in a Kubernetescluster of moderate size. Finally, we present the scalability of the currentsolution assuming a particular autoscaling policy. Results of the calibrationshow high variability of the ProtoCom library when executed in a cloudenvironment. We observe a moderate association between the occupancy of nodeand the relative variability of execution time.

Beauty and the beast: A case study on performance prototyping of data-intensive containerized cloud applications