What pricing models Cloud Providers are use?

There are several pricing models of Cloud providers:

Reserved Instances: This model allows customers to commit to using a certain amount of resources (e.g., virtual machines) for a set period of time, most often used period is month. Customer can chose needed configuration of Infrastructure or Services at the beginning of period and can make few changes monthly. This model is best suited for workloads that have predictable usage patterns and long-term resource requirements.

Prepaid Capacity: The same as “Reserved Instance” model but this model allows customers to pre-pay for a certain amount of resources upfront in exchange for a discounted monthly rate and use them over a set period of time, usually, 12 month. No changes or few changes can be applied.

The pay-as-you-go cloud model is a pricing and billing approach used by Cloudsy. Customers, who use this model, pay only for the resources they consume on a per-minute basis. In other words, you pay only for what you use. It allows users to easily and quickly scale their resources up or down according to their needs, without the need for upfront investments in hardware or infrastructure. That is why Cloudsy named their IaaS/PaaS services as “Elastic cloud”

For example, if you were to use a Cloudsy IaaS/PaaS service to run a website, you would pay for the time that the virtual machine was running, plus any additional storage and data transfer fees that may apply. On high demand period (for example “Easter”, “Black Friday” or else) your website needed more resources, you could simply spin up additional virtual machines or add RAM/CPU/SSD for exist ones and pay for their usage only when you need them. Conversely, at low demand time, if you no longer require a resource, you can shut it down and simply decrease virtual machines parameters.

This model offers flexibility and cost-efficiency for start-up businesses and individuals in AI/ML/Data Science, because they require High Load computing resources with expensive GPU on board and do not want to commit to long-term contracts or high investments in expensive hardware. Moreover, Elastic Cloudsy VMs with vGPU allows such users to experiment from time to time and test out different configurations and AI/ML models without incurring significant costs.