IoT endpoint metrics
Disclosed are various embodiments for collecting and presenting IoT metrics. A software update package can be deployed to an IoT gateway. A device template used to register an IoT endpoint with an IoT management service can also define metrics that can be collected regarding the performance of the IoT endpoints.
1. A system, comprising:
a computing device comprising a processor and a memory;
machine readable instructions stored in the memory that, when executed by the processor, cause the computing device to at least:
obtain a device template specifying at least one device property associated with a plurality of Internet-of-Things (IoT) endpoints, the device template specifying at least one metric associated with at least one IoT endpoint;
collect metric data associated with the at least one metric;
cause the metric data to be stored in a data store associated with a deployment of the IoT endpoints;
cause a software update to be installed on at least a subset of the IoT endpoints;
collect updated metric data associated with the at least one metric after the software update;
cause the updated metric data to be stored in the data store; and
generate a comparison of the metric data and the updated metric data.
2. The system of claim 1 , wherein the comparison comprises a relative efficiency of the IoT endpoints from before installation of the software update and after installation of the software update.
3. The system of claim 1 , wherein the at least one metric comprises a processor usage, a memory usage, or a disk usage of the IoT endpoints.
4. The system of claim 1 , wherein the at least one metric is a time-based interval.
5. The system of claim 1 , wherein the metric data and the updated metric data are obtained from the IoT endpoints upon a respective sample size reaching a threshold size.
6. The system of claim 1 , wherein the metric data and the updated metric data are transmitted to the data store by batch transmission.
7. The system of claim 1 , wherein the software update is associated with a device campaign linking together IoT endpoints that are enrolled with an IoT gateway.
8. A method, comprising:
obtaining a device template specifying at least one device property associated with a plurality of Internet-of-Things (IoT) endpoints, the device template specifying at least one metric associated with at least one IoT endpoint;
collecting metric data associated with the at least one metric;
causing the metric data to be stored in a data store associated with a deployment of the IoT endpoints;
causing a software update to be installed on at least a subset of the IoT endpoints;
collecting updated metric data associated with the at least one metric after the software update;
causing the updated metric data to be stored in the data store; and
generate a comparison of the metric data and the updated metric data.
9. The method of claim 8 , wherein the comparison comprises a relative efficiency of the IoT endpoints from before installation of the software update and after installation of the software update.
10. The method of claim 8 , wherein the at least one metric comprises a processor usage, a memory usage, or a disk usage of the IoT endpoints.
11. The method of claim 8 , wherein the at least one metric is a time-based interval.
12. The method of claim 8 , wherein the metric data and the updated metric data are obtained from the IoT endpoints upon a respective sample size reaching a threshold size.
13. The method of claim 8 , wherein the metric data and the updated metric data are transmitted to the data store by batch transmission.
14. The method of claim 8 , wherein the software update is associated with a device campaign linking together IoT endpoints that are enrolled with an IoT gateway.
15. A non-transitory, computer-readable medium, comprising machine readable instructions that, when executed by a processor, cause a computing device to at least:
obtain a device template specifying at least one device property associated with a plurality of Internet-of-Things (IoT) endpoints, the device template specifying at least one metric associated with at least one IoT endpoint;
collect metric data associated with the at least one metric;
cause the metric data to be stored in a data store associated with a deployment of the IoT endpoints;
cause a software update to be installed on at least a subset of the IoT endpoints;
collect updated metric data associated with the at least one metric after the software update;
cause the updated metric data to be stored in the data store; and
generate a comparison of the metric data and the updated metric data.
16. The non-transitory, computer-readable medium of claim 15 , wherein the comparison comprises a relative efficiency of the IoT endpoints from before installation of the software update and after installation of the software update.
17. The non-transitory, computer-readable medium of claim 15 , wherein the at least one metric comprises a processor usage, a memory usage, or a disk usage of the IoT endpoints.
18. The non-transitory, computer-readable medium of claim 15 , wherein the at least one metric is a time-based interval.
19. The non-transitory, computer-readable medium of claim 15 , wherein the metric data and the updated metric data are obtained from the IoT endpoints upon a respective sample size reaching a threshold size.
20. The non-transitory, computer-readable medium of claim 15 , wherein the metric data and the updated metric data are transmitted to the data store by batch transmission.