# Applying Machine Learning in Cloud Service Price Prediction: The Case of Amazon IaaS
## 3 IaaS Pricing Historical Data and Analysis
### Price Evolution  
To gain further insight into the price evolution, we plot the yearly median offer price for each family in Figure 2. We have chosen the median rather than the mean price because mean values are significantly affected by extreme values and outliers. Median values are more resistant to such effects and are considered a more accurate measure for evaluating tendencies in general statistical data that can be asymmetrical and non-normally distributed [34]. The evolution of the median price value provides valuable insights into the dynamics of the cloud service market and its relationship to the larger global and social environment during that time period. With respect to Figure 1, we note that, in 2016, the prices for all families ranged from $0.21 to $1.14 per hour, the lowest being the general-purpose category and the highest being the storage-optimized category. This reflects the fact that, back in 2016, the market was still emerging with a limited range of specialized products. Following that, in 2017 and 2018, the median prices of some instance families fluctuated, and for memory-optimized instances, they increased by five times, reaching $3.9 per hour in 2017, indicating an increase in demand or a change in the market dynamics for memory-intensive applications. In 2018, GPU instances experienced a significant price increase to $4.30 per hour, indicating an increasing demand for specialized computational duties requiring high-performance graphics processing capabilities.  
In 2019, the median hourly costs of GPU instances experienced a significant decline, dropping from $4.33 to $1.04, which represents a more than fourfold reduction. On the other hand, compute-optimized instances saw a 70% price increase, indicating a higher demand for computational capacity and high-performance computing resources. This suggests that users were opting for more cost-effective GPU instances while seeking greater computing power. In 2020, the median prices of GPU instances aligned with those of other instance families, ranging from $1.5 to $2.1 per hour. This convergence implies a potential  
Figure 1: Density of RI price per year.  
Furthermore, there was a general decline in median prices across all instance families of 10% compared to the previous year, likely due to intensified competition, economies of scale, and improvements in infrastructure efficiency. However, in 2022, median prices experienced a significant increase of approximately 35% across all instance families. Memory-optimized instances stood out with a substantial 70% price increase, indicating a growing demand for memory-intensive applications and potentially reflecting increased costs associated with memory resources. These price trends demonstrate the influence of various factors on cloud service providers' pricing strategies, including inflation, market dynamics, resource requirements, and technological advancements. The popularity of specialized instance families underscores the widespread adoption of cloud services across different industries. Additionally, a combination of technological advancements, market competition, customer preferences, and resource availability affect the observed price patterns.  
It is crucial to consider the broader socioeconomic factors that may have influenced the cloud services market during this period. Economic fluctuations, geopolitical events, and advancements in related industries such as artificial intelligence, big data analytics, and machine learning can impact pricing strategies and market dynamics. Changes in user preferences, emerging industry trends, and regulatory adjustments may also contribute to the observed price patterns. These multifaceted interactions highlight the dynamic nature of the cloud services market and emphasize the importance of ongoing monitoring and analysis.