Abstract
Today, serverless computing or Function-as-a-Service (FaaS) is an excellent way to exploit cloud computing benefits due to its simplicity, billing, and innate elasticity. FaaS providers own the responsibility of server provisioning, administration, management and patching thus making developers less burdened and more productive. Serverless applications based on complex workflows involve multiple functions which have data dependencies on each other. This brings the concept of function orchestration in picture and makes it important in implementing any serverless application. In this context Amazon Web Services (AWS Step Function), International Business Machines (IBM) Cloud Function Sequences and Azure Durable Functions are currently available in market. In this paper, different sequential composition workflows like Reflexive, Fusion, Chaining, and Client Scheduled are implemented in AWS serverless platform and compared their performance in terms of execution duration. Successively, sequential workflows in different language runtime environments in AWS Step function and IBM Cloud Function Sequences are also analyzed. Experiments are also performed to observe the cold start behavior in AWS Lambda and (IBM) Cloud functions.
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Bharti, U., Bajaj, D., Goel, A., Gupta, S.C. (2021). Sequential Workflow in Production Serverless FaaS Orchestration Platform. In: Pandian, A.P., Palanisamy, R., Ntalianis, K. (eds) Proceedings of International Conference on Intelligent Computing, Information and Control Systems. Advances in Intelligent Systems and Computing, vol 1272. Springer, Singapore. https://doi.org/10.1007/978-981-15-8443-5_58
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DOI: https://doi.org/10.1007/978-981-15-8443-5_58
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