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Towards Generating Realistic Trace for Simulating Functions-as-a-Service

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Part of the Lecture Notes in Computer Science book series (LNCS,volume 13098)


Serverless computing is a step forward to provide a cloud environment that responds to user requests by mainly focusing on managing infrastructure, resources and configurations. Despite the widespread use of cloud simulators, they are still mainly focused on supporting more traditional Infrastructure-as-a-Service scenarios and this reduces their applicability in the serverless and function as a service domains. Moreover, workload traces typically employed by IaaS simulators to represent user behaviour, are not well adoptable for serverless model. More realistic and serverless-like traces are essential to simulate and predict the behaviour of functions in serverless systems. Therefore, this paper focuses on generating realistic traces for simulating serverless computing platforms. The generated traces produced by our approach are based on the Azure Functions dataset and they are readily applicable in an already available versatile and high performance simulator (DISSECT-CF). We validated the generated approach using the coefficient of determination (\(R^2\)), which shows very good values for the average and percentiles of the execution time and memory. To demonstrate the benefits of the generated traces we introduced a rudimentary model for serverless systems to DISSECT-CF. Our evaluation shows that our workloads are realistic and closely follow the behaviour of Azure’s function as a service component.


  • Serverless computing
  • Serverless workload
  • Serverless trace
  • FaaS

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  • DOI: 10.1007/978-3-031-06156-1_34
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This research was supported by the Hungarian Scientific Research Fund under the grant number OTKA FK 131793.

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Correspondence to Dilshad Hassan Sallo .

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Sallo, D.H., Kecskemeti, G. (2022). Towards Generating Realistic Trace for Simulating Functions-as-a-Service. In: , et al. Euro-Par 2021: Parallel Processing Workshops. Euro-Par 2021. Lecture Notes in Computer Science, vol 13098. Springer, Cham.

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