Providing anonymous network data to an artificial intelligence model for processing in near-real time

1. A method, comprising:

receiving, by a device and from a network device in near-real time, a packet of data associated with network traffic of a network,

wherein the packet includes privacy-related data and network-related data;

reading, by the device, the privacy-related data from the packet;

generating, by the device, anonymous data based on the privacy-related data of the packet,

wherein the anonymous data obscures the privacy-related data;

generating, by the device, a mapping between the anonymous data and the privacy-related data;

combining, by the device, the anonymous data and the network-related data of the packet to generate a masked packet;

providing, by the device, the masked packet to a server device;

receiving, by the device and from the server device, data identifying a recommendation that is generated by processing the masked packet with an artificial intelligence model; and

performing, by the device, one or more actions based on the data identifying the recommendation.

2. The method of claim 1 , wherein performing the one or more actions comprises:

correlating the data identifying the recommendation with data identifying the network device based on the mapping between the anonymous data and the privacy-related data; and

causing the recommendation to be implemented for the network device or the network based on correlating the data identifying the recommendation with the data identifying the network device.

3. The method of claim 1 , wherein performing the one or more actions comprises:

correlating the data identifying the recommendation with data identifying the network device based on the mapping between the anonymous data and the privacy-related data; and

providing the data identifying the recommendation to a network management system associated with the network device, based on correlating the data identifying the recommendation with the data identifying the network device, to permit the network management system to implement the recommendation for the network device or the network.

4. The method of claim 1 , wherein the data identifying the recommendation includes the anonymous data of the masked packet.

5. The method of claim 1 , wherein the privacy-related data includes data identifying one or more of:

an interface name associated with the network device,

an identifier associated with the network device,

a network address associated with the network device,

a source port associated with the network device, or

a destination port associated with the network device.

6. The method of claim 1 , wherein the network-related data includes data identifying one or more of:

processor usage associated with the network device,

a temperature of the network device,

memory usage associated with the network device,

an error associated with the network device,

queue usage associated with the network device, or

virtual interface usage associated with the network device.

7. The method of claim 1 , wherein the device receives the packet concurrently with the network device processing the packet to forward toward a destination of the packet.

8. A device, comprising:

one or more memories; and

one or more processors, communicatively coupled to the one or more memories, to:

receive, from a network device in near-real time, a packet of data associated with network traffic of a network,

wherein the packet includes privacy-related data and network-related data;

read the privacy-related data from the packet;

generate anonymous data based on the privacy-related data of the packet;

generate a mapping between the anonymous data and the privacy-related data;

combine the anonymous data and the network-related data of the packet to generate a masked packet;

provide the masked packet to a server device;

receive, from the server device, data identifying a recommendation that is based on processing of the masked packet by an artificial intelligence model; and

correlate the data identifying the recommendation with data identifying the network device based on the mapping between the anonymous data and the privacy-related data; and

perform one or more actions based on correlating the data identifying the recommendation with data identifying the network device.

9. The device of claim 8 , wherein the network device is associated with a data center and the packet includes data associated with the data center.

10. The device of claim 8 , wherein the recommendation is associated with one or more of:

reduce processor usage associated with the network device,

reduce a temperature of the network device,

reduce memory usage associated with the network device,

correct an error associated with the network device,

reduce queue usage associated with the network device, or

reduce virtual interface usage associated with the network device.

11. The device of claim 8 , wherein the one or more processors, when performing the one or more actions, are to:

cause the recommendation to be implemented for the network device or the network.

12. The device of claim 8 , wherein the one or more processors are further to:

store the mapping in a data structure associated with the device.

13. The device of claim 8 , wherein the recommendation is based on historical network traffic data associated with network devices of the network, other than the network device.

14. The device of claim 8 , wherein the artificial intelligence model includes a machine learning model.

15. A non-transitory computer-readable medium storing instructions, the instructions comprising:

one or more instructions that, when executed by one or more processors, cause the one or more processors to:

receive, from a plurality of network devices in near-real time, a plurality of packets of data associated with network traffic of a network,

wherein the plurality of packets includes privacy-related data and network-related data;

read the privacy-related data from the plurality of packets;

generate anonymous data based on the privacy-related data of the plurality of packets;

generate a mapping between the anonymous data and the privacy-related data;

combine the anonymous data and the network-related data of the plurality of packets to generate a plurality of masked packets;

provide the plurality of masked packets to a server device;

receive, from the server device, data identifying one or more recommendations that are based on the plurality of masked packets being processed by an artificial intelligence model; and

perform one or more actions based on the data identifying the one or more recommendations.

16. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the one or more processors to perform the one or more actions, cause the one or more processors to:

correlate the data identifying the one or more recommendations with data identifying the plurality of networks devices based on the mapping between the anonymous data and the privacy-related data; and

cause the one or more recommendations to be implemented for one or more of the plurality of network devices based on correlating the data identifying the one or more recommendations with the data identifying the plurality of networks devices.

17. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the one or more processors to perform the one or more actions, cause the one or more processors to:

correlate the data identifying the one or more recommendations with data identifying the plurality of network devices based on the mapping between the anonymous data and the privacy-related data; and

provide the data identifying the one or more recommendations to a network management system associated with the plurality of network devices, based on correlating the data identifying the one or more recommendations with the data identifying the plurality of network devices, to permit the network management system to implement the one or more recommendations for one or more of the plurality of network devices.

18. The non-transitory computer-readable medium of claim 15 , wherein the data identifying the one or more recommendations includes the anonymous data of the plurality of masked packets.

19. The non-transitory computer-readable medium of claim 15 , wherein the privacy-related data includes data identifying one or more of:

a plurality of interfaces associated with the plurality of network devices,

a plurality of identifiers associated with the plurality of network devices,

a plurality of network addresses associated with the plurality of network devices,

a plurality of source ports associated with the plurality of network devices, or

a plurality of destination ports associated with the plurality of network devices.

20. The non-transitory computer-readable medium of claim 15 , wherein the network-related data includes data identifying one or more of:

processor usage associated with the plurality of network devices,

a plurality of temperatures of the plurality of network devices,

memory usage associated with the plurality of network devices,

one or more errors associated with one or more of the plurality of network devices, queue usage associated with the plurality of network devices, or

virtual interface usage associated with the plurality of network devices.