# Comparison of Cloud-Computing Providers for Deployment of Object-Detection Deep Learning Models
## 4 Results and Discussion
### Monetary Cost Analysis  
AWS and Azure follow the industry standard pay-as-you-go pricing model, where users are billed based on their actual consumption of the various cloud resources. The pricing for compute instances on both platforms depends on factors such as instance type, operating system, region, and usage time. However, instances can be reserved for periods of either 1 year or 3 years because deployment can be availed at a much lower cost. Nevertheless, the costs presented in this paper are for standard pay-as-you-go pricing. Furthermore, the costs for Azure are presented in a range because of the Azure App Services autoscaling plan, and they can range between 1 and 10 instances based on the workload for the endpoint. The cost breakdown for each microservice in both platforms is given in Tables 6 and 7.  
The cost summaries provided for Amazon Web Services (AWS) and Microsoft Azure reveal some key differences in the pricing structures of these two cloud platforms. Notably, for a single CPU instance Azure appears to offer more competitive pricing, with a daily cost  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Service** & **Instance Type or Storage Capacity** & **Associated Cost (per h)** \\ \hline Amazon S3 & 18 GB & Free tier \\ Amazon EC2 & t3.micro & USD 0.0104 \\ Amazon SageMaker Model Endpoint & ml.g4 dn.xlarge & USD 0.526 \\ Hourly cost & & USD 0.5364 \\ Daily cost & & USD 12.8736 \\ \hline \hline \end{tabular}
\end{table}
Table 6: AWS cost summary.  
Figure 16: Boxplot of normalized throughput for each platform.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Service** & **Instance Type or Storage Capacity** & **Associated Cost (per h)** \\ \hline Azure Blob Storage & 18 GB & Free Tier \\ Azure Virtual Machine & Basic B1 & USD 0.0115 \\ Azure web app & Standard S1 & USD 0.184–USD 1.84 \\ Hourly cost & & USD 0.1955–USD 1.955 \\ Daily cost & & USD 4.692–USD 46.92 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Azure cost summary.  
of USD 4.692 compared to USD 12.8736 for AWS. However, this lower cost may come at the expense of performance since a single CPU instance would produce inferior inference times and throughput to that of a GPU. Furthermore, we observe that Amazon EC2 offers a slightly lower hourly cost of USD 0.0104, whereas the Azure Virtual Machine offers an hourly cost of USD 0.0115. This disparity can be partially attributed to economies of scale, where AWS, being the larger and more established cloud provider, can leverage its extensive infrastructure and customer base to offer lower prices for compute resources. Finally, because of the autoscaling plan on Azure, the costs can reach up to USD 46.92 per day in order to achieve comparable inference times, but it has a higher throughput than AWS. This result implies that the cost behind availing high-performance computing is far higher in Azure, which may not be suitable for machine learning workloads that require strong computing capabilities. Overall, AWS seems to have a net cost advantage for high-performance workloads, which makes it a more cost-effective choice for many organizations.