Post by rahim on Jan 31, 2024 9:59:23 GMT
Can only be used to its full potential sporadically. And this is exactly where public cloud services come to the rescue!With cloud computing, the service provider provides various resources such as applications (Software-as-a-Service, SaaS), computing platforms (Platform-as-a-Service, Paas) or a complete IT infrastructure such as storage or servers ( Infrastructure-as-a-Service (IaaS) is available to the general public via the Internet.Companies can therefore rent these IT resources directly over the Internet (i.e. without local installation),
paying only for what was actually used. The DB to Data cloud provider operates the servers on which customer data is stored.The biggest advantages of using public clouds are:Simple and cost-effective setup because the respective provider takes care of the hardware, applications and bandwidth costs themselves.Any scalability , i.e. computing and storage capacities can be added (scale in) or deleted (scale out) or increased (scale up) or reduced (scale down) at any time.No unused resources because only what was actually needed is requested and paid for.
No long-term contracts . Especially in the area of machine learning, it is often difficult to decide on a specific computing capacity from the outset, as the actual requirements and required resources often cannot be estimated. In such situations, public cloud hosting works very well as it does not require long-term commitment or investment. The cloud providers usually offer pay-as-you-grow models, which make the entire engagement extremely simple and straightforward.In addition, all major public cloud providers follow an API-first approach.
paying only for what was actually used. The DB to Data cloud provider operates the servers on which customer data is stored.The biggest advantages of using public clouds are:Simple and cost-effective setup because the respective provider takes care of the hardware, applications and bandwidth costs themselves.Any scalability , i.e. computing and storage capacities can be added (scale in) or deleted (scale out) or increased (scale up) or reduced (scale down) at any time.No unused resources because only what was actually needed is requested and paid for.
No long-term contracts . Especially in the area of machine learning, it is often difficult to decide on a specific computing capacity from the outset, as the actual requirements and required resources often cannot be estimated. In such situations, public cloud hosting works very well as it does not require long-term commitment or investment. The cloud providers usually offer pay-as-you-grow models, which make the entire engagement extremely simple and straightforward.In addition, all major public cloud providers follow an API-first approach.