Abstract

Several providers in the cloud provide server-less solutions that claim to be highly available, scalable, and low-maintenance. To that end, serverless computing using Azure Kubernetes Service (AKS) and Dockers is promoted as a feasible choice for pay-per-use Web API, data processing, and backend services. They offer elastic and automated scalability, in contrast to VMs, by automatically provisioning and allocating resources. We provide our findings from analyzing the Data Wizard application running on AKS and as Function(s)-as-a-Service, a serverless solution (FaaS). We compare these rollouts by moving data between generations of Azure to track latencies and costs. When VMs are prepared for the anticipated load, and test scenarios are within the FaaS hardware constraints, we discovered no major changes in response time between deployments. FaaS easily manages larger data migration volumes, but VMs require more man hours to get the same outcomes. The benefits of serverless computing, as we've seen them, make it easy to decide between serverless and virtual machines for a Data Wizard (DW) programme.

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