Abstract
The current computing trend towards cloud-based Database-as-a-Service (DaaS) as an alternative to traditional on-site relational database management systems (RDBMSs) has largely been driven by the perceived simplicity and cost-effectiveness of migrating to a DaaS. However, customers that are attracted to these DaaS alternatives may find that the range of different services and pricing options available to them add an unexpected level of complexity to their decision making. Cloud service pricing models are typically ‘pay-as-you-go’ in which the customer is charged based on resource usage such as CPU and memory utilization. Thus, customers considering different DaaS options must take into account how the performance and efficiency of the DaaS will ultimately impact their monthly bill. In this paper, we show that the current DaaS model can produce unpleasant surprises – for example, the case study that we present in this paper illustrates a scenario in which a DaaS service powered by a DBMS that has a lower hourly rate actually costs more to the end user than a DaaS service that is powered by another DBMS that charges a higher hourly rate. Thus, what we need is a method for the end-user to get an accurate estimate of the true costs that will be incurred without worrying about the nuances of how the DaaS operates. One potential solution to this problem is for DaaS providers to offer a new service called Benchmark as a Service (BaaS) where in the user provides the parameters of their workload and SLA requirements, and get a price quote.
Keywords
- Cloud Computing
- Cloud Service
- Price Model
- Service Level Agreement
- Price Quote
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Floratou, A., Patel, J.M., Lang, W., Halverson, A. (2012). When Free Is Not Really Free: What Does It Cost to Run a Database Workload in the Cloud?. In: Nambiar, R., Poess, M. (eds) Topics in Performance Evaluation, Measurement and Characterization. TPCTC 2011. Lecture Notes in Computer Science, vol 7144. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32627-1_12
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DOI: https://doi.org/10.1007/978-3-642-32627-1_12
Publisher Name: Springer, Berlin, Heidelberg
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