System and method for remote assisted optimization of native services
Embodiments of systems and methods for remote assisted optimization of applications executed by an Information Handling System (IHS) are described. In an illustrative, non-limiting embodiment, an IHS may include computer-executable instructions for determining one or more application performance features of a target application using an application machine learning (ML) engine, and generating one or more application profile recommendations for the target application according to the determined application performance features. Using the profile recommendations, the instructions adjust one or more settings of the IHS to optimize a performance of the target application, and transmit the application profile recommendations to a server that is configured to provide a service for the target application. The server then uses the one or more application profile recommendations to provision the service for use by the target application.
1. An Information Handling System (IHS), comprising:
at least one processor; and
at least one memory coupled to the at least one processor, the at least one memory having program instructions stored thereon that, upon execution by the at least one processor, cause the IHS to:
determine one or more application performance features of a target application using an application machine learning (ML) engine;
generate one or more application profile recommendations for the target application according to the determined application performance features;
adjust one or more settings of the IHS to optimize a performance of the target application; and
transmit the one or more application profile recommendations to a cloud server that is configured to provide a cloud service for the target application, wherein the server is configured to use the one or more application profile recommendations to provision a communication link between the IHS and the server to provide the service for use by the target application.
2. The IHS of claim 1 , wherein the communication link comprises a slice of a fifth generation (5G) technology cellular network.
3. The IHS of claim 1 , wherein the instructions are further executed to provision the communication link by generating a container comprising one or more network functions (NFs).
4. The IHS of claim 1 , wherein the server is configured to provision the service by:
determining one or more service performance features of the service using a service ML engine;
generate one or more service profile recommendations for the service according to the determined service performance features; and
adjust, using the service profile recommendations, one or more settings of the service to optimize a performance of the service.
5. The IHS of claim 4 , wherein the server is further configured to:
store the service profile recommendations in a server memory; and
at a later point in time when a communication link between the IHS and the server is deleted and then re-established, adjust one or more settings of the service to optimize the performance of the service using the service profile recommendations.
6. The IHS of claim 4 , wherein the instructions are further executed to:
receive the service profile recommendations from the server;
augment the application profile recommendations according to the received service profile recommendations; and
adjust the settings of the IHS to further optimize the performance of the target application.
7. The IHS of claim 1 , wherein the instructions are further executed to:
repeat the actions of determining the application profile recommendations, generating the profile recommendations, adjusting the settings, and transmitting the application profile recommendations to the server at ongoing intervals.
8. The IHS of claim 1 , wherein the instructions are further executed to:
repeat the actions of determining the application profile recommendations, generating the profile recommendations, adjusting the settings, and transmitting the application profile recommendations to the server when a specified threshold of at least one of the application performance features telemetry data element has been triggered.
9. The IHS of claim 1 , wherein the instructions are further executed to transmit the application profile recommendations to the server using a ML hinting technique.
10. A method comprising:
determining, using instructions stored in at least one memory and executed by at least one processor, one or more application performance features of a target application using an application machine learning (ML) engine;
generating, using the instructions, one or more application profile recommendations for the target application according to the determined application performance features;
adjusting, using the instructions, one or more settings of an information handling system (IHS) to optimize a performance of the target application; and
transmitting, using the instructions, the one or more application profile recommendations to a server that is configured to provide a service for the target application, wherein the server uses the one or more application profile recommendations to provision a communication link between the IHS and the server to provide the service for use by the target application.
11. The method of claim 10 , further comprising provisioning the communication link by generating a container comprising one or more network functions (NFs).
12. The method of claim 10 , further comprising:
determining one or more service performance features of the service using a service ML engine;
generating one or more service profile recommendations for the service according to the determined service performance features; and
adjusting, using the service profile recommendations, one or more settings of the service to optimize a performance of the service.
13. The method of claim 12 , further comprising:
storing the service profile recommendations in a server memory; and
at a later point in time when a communication link between the IHS and the server is deleted and then re-established, adjusting one or more settings of the service to optimize a performance of the service using the service profile recommendations.
14. The method of claim 12 , further comprising:
receiving the service profile recommendations from the server;
augmenting the application profile recommendations according to the received service profile recommendations; and
adjusting the settings of the IHS to further optimize the performance of the target application.
15. The method of claim 10 , further comprising:
repeating the actions of determining the application profile recommendations, generating the profile recommendations, adjusting the settings, and transmitting the application profile recommendations to the server at ongoing intervals.
16. The method of claim 10 , further comprising:
repeating the actions of determining the application profile recommendations, generating the profile recommendations, adjusting the settings, and transmitting the application profile recommendations to the server when a specified threshold of at least one of the application performance features telemetry data element has been triggered.
17. The method of claim 10 , further comprising transmitting the application profile recommendations to the server using a ML hinting technique.
18. A memory storage device having program instructions stored thereon that, upon execution by one or more processors of an Information Handling System (IHS), cause the IHS to:
determine one or more application performance features of a target application using an application machine learning (ML) engine;
generate one or more application profile recommendations for the target application according to the determined application performance features;
adjust one or more settings of the IHS to optimize a performance of the target application; and
transmit the one or more application profile recommendations to a server that is configured to provide a service for the target application, wherein the server is configured to use the one or more application profile recommendations to provision a communication link between the IHS and the server to provide the service for use by the target application.