Selection of virtual private network profiles

1. A device comprising:

a processing resource;

a machine-readable medium storing instructions that, when executed by the processing resource, cause the processing resource to:

obtain virtual private network (VPN) metrics associated with a plurality of VPN server nodes;

monitor device usage metrics associated with the device configured with a first VPN profile, wherein the first VPN profile indicates that a first VPN tunnel connection is associated with a first VPN server node of the plurality of VPN server nodes;

determine a latency associated with each of the plurality of VPN server nodes based on the VPN metrics and the device usage metrics;

select a second VPN server node from the plurality of VPN server nodes, wherein the second VPN server node is associated with a least latency, high throughput, and low server load among the plurality of VPN server nodes;

determine a second VPN tunnel connection associated with the second VPN server node based on historical web traffic, tunnel connection traffic, and user specific metrics;

display, to the user, a recommendation to configure the device with one or more recommended VPN profiles for a determined period of time, wherein the recommended VPN profiles includes at least a second VPN profile, and wherein the second VPN profile indicates that the second VPN tunnel connection is associated with the second VPN server node; and

if the user does not select any of the recommended VPN profiles before the expiry of the determined period of time, then automatically switch the device's configuration from the first VPN profile to the second VPN profile.

2. The device of claim 1 , wherein to automatically switch from the first VPN profile to the second VPN profile, the processing resource executes one or more of the instructions to:

disconnect from the first VPN server node and the first VPN tunnel connection; and

establish a connection with the second VPN server node and the second VPN tunnel connection.

3. The device of claim 1 , wherein the VPN metrics include one or more of a roundtrip time, server load, bandwidth, routing hops, and geographical distance, number of disconnections, and wherein the device usage metrics include one or more of historical web traffic, tunnel connection traffic, user specific metrics, workload profiles, and device resources.

4. The device of claim 3 , wherein to select the second VPN server node, the processing resource executes one or more of the instructions to:

provide the VPN metrics and the device usage metrics as an input to a machine learning model; and

predict a VPN server node associated with a least latency using the machine learning model.

5. The device of claim 1 , wherein the processing resource executes one or more of the instructions to: identify a device profile of the device, wherein the device profile indicates whether the device is a greenfield device or a non-greenfield device.

6. The device of claim 1 , wherein the processing resource executes one or more of the instructions to: disconnect a connection to the second VPN server node based on device inactivity.

7. The device of claim 1 , further comprising: a display unit for displaying a user interface for rendering a plurality of options for selection, wherein the plurality of options indicate VPN profiles.

8. The device of claim 1 , wherein the first VPN tunnel connection and the second VPN tunnel connection are one of a full VPN tunnel connection or a split VPN tunnel connection.

9. A method comprising:

obtaining, by a processor, virtual private network (VPN) metrics associated with a plurality of VPN server nodes;

monitoring, by the processor, device usage metrics associated with a device configured with a first VPN profile, wherein the first VPN profile indicates that a first VPN tunnel connection is associated with a first VPN server node of the plurality of VPN server nodes;

determining, by the processor, a latency associated with each of the plurality of VPN server nodes based on the VPN metrics and the device usage metrics

selecting, by the processor, a second VPN server node from the plurality of VPN server nodes, wherein the second VPN server node is associated with a least latency, high throughput, and low server load among the plurality of VPN server nodes;

determining, by the processor, a second VPN tunnel connection associated with the second VPN server node based on the historical web traffic, tunnel connection traffic, and user specific metrics;

displaying, by the processor to the user, a recommendation to configure the device with one or more recommended VPN profiles for a determined period of time, wherein the recommended VPN profiles includes at least a second VPN profile, and wherein the second VPN profile indicates that the second VPN tunnel connection is associated with the second VPN server node; and

if the user does not select any of the recommended VPN profiles before the expiry of the determined period of time, then automatically switch the device's configuration from the first VPN profile to the second VPN profile.

10. The method of claim 9 , wherein selecting the second VPN server node comprises:

providing, by the processor, the VPN metrics and the device usage metrics as an input to a machine learning model; and

predicting, by the processor, a VPN server node associated with a least latency using the machine learning model.

11. The method of claim 10 , wherein the machine learning model is trained using a supervised learning method or an unsupervised learning method.

12. The method of claim 9 , further comprising: disconnecting a connection to the second VPN server node based on device inactivity.

13. The method of claim 9 , wherein the first VPN tunnel connection and the second VPN tunnel connection are one of a full VPN tunnel connection or a split VPN tunnel connection.

14. A non-transitory machine-readable medium storing instructions executable by a processing resource, the instructions comprising:

instructions to obtain virtual private network (VPN) metrics associated with a plurality of VPN server nodes;

instructions to monitor device usage metrics associated with a device configured with a first VPN profile, wherein the first VPN profile indicates that a first VPN tunnel connection is associated with a first VPN server node of the plurality of VPN server nodes;

instructions to determine a latency associated with each of the plurality of VPN server nodes based on the VPN metrics and the device usage metrics;

instructions to select a second VPN server node from the plurality of VPN server nodes, wherein the second VPN server node is associated with a least latency, high throughput, and low server load among the plurality of VPN server nodes;

instructions to determine a second VPN tunnel connection associated with the second VPN server node based on historical web traffic, tunnel connection traffic, and user specific metrics;

instructions to display a recommendation to the user for a determined period of time to configure the device with one or more recommended VPN profiles, wherein the recommended VPN profiles includes at least a second VPN profile, and wherein the second VPN profile indicates that the second VPN tunnel connection is associated with the second VPN server node; and

instructions to, if the user does not select any of the recommended VPN before the expiry of the determined period of time, automatically switch the device's configuration from the first VPN profile to the second VPN profile.

15. The non-transitory machine-readable medium of claim 14 , wherein the instructions to select the second VPN server node further comprising instructions to:

provide the VPN metrics and the device usage metrics as an input to a machine learning model; and

predict a VPN server node associated with a least latency using the machine learning model.

16. The non-transitory machine-readable medium of claim 14 , further comprising instructions to: identify a device profile of the device, wherein the device profile indicates whether the device is a greenfield device or a non-greenfield device.

17. The non-transitory machine-readable medium of claim 14 , further comprising instructions to: disconnect a connection to the second VPN server node based on device inactivity.

18. The device of claim 1 , wherein the processing resource executes one or more of the instructions to determine if the device is a new device for the VPN.

19. The device of claim 1 , wherein the processing resource executes one or more of the instructions to disconnect a connection to the VPN if the device is inactive.

20. The device of claim 19 , wherein disconnecting the connection to the VPN comprises disconnecting a VPN tunnel connection and preserving a connection to the VPN server.