Introduction
Cloud engines are a specialization of aspect engine where the processing is handed off to a cloud service. This is in contrast to an on-premise engine where processing occurs locally to the engine. Having data which does not reside in the engine itself means that the same engine can be used with multiple data sets.
Use Cases
A cloud engine is very lightweight compared to an on-premise engine both in terms of memory and CPU usage. This is because all the complex processing and any data that is required for that processing to occur are handled by the associated cloud service. The trade-off is that a cloud engine cannot provide the same performance as an on-premise engine.
For many cases, a cloud engine's performance is sufficient, and is ideal for small environments where memory is in short supply. On small services such as a cloud Lambda function where there are low limits to the size of the services, cloud engines are a perfect fit.
As cloud engines typically offload the actual processing onto a cloud service, this also makes them a good choice for environments which lack processing power. By letting a cloud service do all the work, CPU cycles are freed up on the low power device for other tasks.
Internals
All the data for a cloud engine is accessed through a cloud service, any data or processing needed by the engine is serviced through HTTP requests. This means the engine itself has limited knowledge of its capabilities, for example, the properties available in a cloud engine may be populated from a request to the cloud service.
Typically a cloud engine does not carry out processing itself. Instead, its processing consists of sending a call to a cloud service and interpreting the result.
51Degrees Cloud Engines
The functionality of all aspect engines that make use of the 51Degrees cloud is actually split into two separate aspect engines. The 'cloud request engine' marshals the evidence and makes a request to the cloud service. The resulting raw JSON string is stored in the request engine's associated element data.
There are then individual cloud engines that can be added to the Pipeline for each aspect. These will take the part of the raw JSON string which is relevant to them and transform it into something with the same interface as the associated on-premise engine.
This splitting thus allows a single request to be made even if the details of multiple aspects need to be populated while also allowing the ability to easily swap between a cloud engine and the on-premise engine concerned with the same aspect.