Abstract: Examples of the present disclosure relate to artificial intelligence log processing and CDN optimization. In examples, log data is processed at a node of the CDN rather than transmitting all of the log data for remote processing. The log data may be processed by a model processing engine according to a model, thereby generating model processing results. Model processing results are communicated to a parent node, thereby providing insight into the state of the node without requiring transmission of the full set of log data. Model processing results and associated information may be used to alter the configuration of the CDN. For example, a model processing engine may be added or removed from a node based on a forecasted amount of log data. As another example, edge servers of a node may be added or removed based on expected computing demand.

Abstract: Examples of the present disclosure relate to an AI-supported CDN. In examples, a data processing engine processes log data of a CDN node according to a model to identify an issue. An issue indication is provided to a solution generation engine, which generates a set of solutions to automatically resolve the issue. The set of solutions is provided to a solution implementation engine, which iteratively implements solutions to resolve the issue using solution implementation information associated with a given solution. Thus, the data processing engine need not have knowledge regarding the specific hardware and/or software used within the CDN. Similarly, the solution generation engine need not have knowledge of the structure of the CDN and/or configuration of devices associated with the identified issue, such that the solution implementation engine provides a layer of abstraction between a solution and the implementation-specific details used to implement the solution within the CDN.

Abstract: Examples of the present disclosure relate to an AI-supported CDN. In examples, a data processing engine processes log data of a CDN node according to a model to identify an issue. An issue indication is provided to a solution generation engine, which generates a set of solutions to automatically resolve the issue. The set of solutions is provided to a solution implementation engine, which iteratively implements solutions to resolve the issue using solution implementation information associated with a given solution. Thus, the data processing engine need not have knowledge regarding the specific hardware and/or software used within the CDN. Similarly, the solution generation engine need not have knowledge of the structure of the CDN and/or configuration of devices associated with the identified issue, such that the solution implementation engine provides a layer of abstraction between a solution and the implementation-specific details used to implement the solution within the CDN.

Abstract: Examples of the present disclosure relate to artificial intelligence log processing and CDN optimization. In examples, log data is processed at a node of the CDN rather than transmitting all of the log data for remote processing. The log data may be processed by a model processing engine according to a model, thereby generating model processing results. Model processing results are communicated to a parent node, thereby providing insight into the state of the node without requiring transmission of the full set of log data. Model processing results and associated information may be used to alter the configuration of the CDN. For example, a model processing engine may be added or removed from a node based on a forecasted amount of log data. As another example, edge servers of a node may be added or removed based on expected computing demand.