Distributed tool for detecting states and state transitions in remote network management platforms

Patent metadata

Field	Value
Publication number	US-10630546-B2
Application number	US-201715713089-A
Country	US
Kind code	B2
Filing date	Sep 22, 2017
Priority date	Sep 22, 2017
Publication date	Apr 21, 2020
Grant date	Apr 21, 2020

Abstract

A computing system may involve a time-series server device and computing devices. The time-series server device may be configured to: receive and store pre-defined trigger configurations; receive and store time-series data, wherein the pre-defined trigger configurations define states and/or state transitions for the received time-series data; apply, by way of a trigger engine, the pre-defined trigger configurations to the received time-series data to determine observed states and/or state transitions in the time-series data; and store, in transition storage, representations of the observed states and/or state transitions. One or more applications operating on computing devices may be configured to: transmit the pre-defined trigger configurations to the time-series server; transmit a stream of the time-series data to the time-series server; and repeatedly poll and receive, by way of a plurality of worker threads, the representations of the observed states and/or state transitions from the transition storage.

First claim

What is claimed is:

1. A computing system comprising:
a time-series server device disposed within the computing system, wherein the time-series server device is configured to:
receive and store pre-defined trigger configurations,
receive and store time-series data, wherein the pre-defined trigger configurations define states and state transitions for the received time-series data,
apply, by way of a trigger engine, the pre-defined trigger configurations to the received time-series data to determine observed states and state transitions in the time-series data, comprising:
synchronously applying, by way of a trigger engine, a first set of the pre-defined trigger configurations to the received time-series data to determine observed states and state transitions in the time-series data, wherein the first set of the pre-defined trigger configurations can be applied using the received time-series data and thresholds defined in the first set of the pre-defined trigger configurations, and
asynchronously applying, by way of the trigger engine, a second set of the pre-defined trigger configurations to the received time-series data to determine observed states and state transitions in the time-series data, wherein the second set of the pre-defined trigger configurations uses information available to the time-series server device but not available in the time-series data nor the second set of the pre-defined trigger configurations, and

store, in transition storage, representations of the observed states and state transitions; and

one or more applications operating on computing devices disposed within the computing system, wherein the one or more applications are configured to:
transmit the pre-defined trigger configurations to the time-series server,
transmit a stream of the time-series data to the time-series server, and
repeatedly poll and receive, by way of a plurality of worker threads, the representations of the observed states and state transitions from the transition storage.

2. The computing system of claim 1 , wherein the time-series server device is part of a remote network management platform that manages a managed network.

3. The computing system of claim 2 , wherein at least some of the computing devices are disposed within the remote network management platform.

4. The computing system of claim 2 , wherein at least some of the computing devices are disposed within the managed network.

5. The computing system of claim 1 , wherein the time-series data includes, for a particular computing device of the computing devices, measurements of a performance indicator, and wherein a particular trigger configuration of the pre-defined trigger configurations defines a state transition in which the performance indicator crosses a threshold value.

6. The computing system of claim 1 , wherein the time-series data includes, for a particular computing device of the computing devices, measurements of a performance indicator, and wherein a particular trigger configuration of the pre-defined trigger configurations defines a state transition in which the performance indicator is on one side of a threshold value for m measurements out of a previous n consecutive measurements.

7. The computing system of claim 1 , wherein the time-series data includes, for a particular computing device of the computing devices, measurements of a performance indicator, and wherein the performance indicator represents one of processor utilization, memory utilization, or network capacity utilization of the particular computing device.

8. The computing system of claim 1 ,
wherein the first set of the pre-defined trigger configurations can be applied using respective individual measurements in the received time-series data; and
wherein the second set of the pre-defined trigger configurations respectively use a plurality of individual measurements in the received time-series data.

9. The computing system of claim 1 , wherein each of the pre-defined trigger configurations is respectively associated with a callback function, and wherein applying the pre-defined trigger configurations to the received time-series data comprises calling the callback function associated with a particular trigger configuration of the pre-defined trigger configurations as a result of the state or state transition of the particular trigger configuration being observed.

10. The computing system of claim 1 , wherein a particular trigger configuration of the pre-defined trigger configurations is based on a linear prediction of a trend in the time-series data, wherein the linear prediction estimates a future time at which values of the time series data is expected to cross a pre-determined threshold.

11. A method comprising:
receiving and storing, by a time-series server device disposed within a remote network management platform, pre-defined trigger configurations;
receiving and storing, by the time-series server device, a stream of time-series data, wherein the pre-defined trigger configurations define states and state transitions for the received time-series data;
applying, by way of a trigger engine of the time-series server device, the pre-defined trigger configurations to the received time-series data to determine observed states and state transitions in the time-series data comprising:
synchronously applying, by way of a trigger engine, a first set of the pre-defined trigger configurations to the received time-series data to determine observed states and state transitions in the time-series data, wherein the first set of the pre-defined trigger configurations can be applied using the received time-series data and thresholds defined in the first set of the pre-defined trigger configurations; and
asynchronously applying, by way of the trigger engine, a second set of the pre-defined trigger configurations to the received time-series data to determine observed states and state transitions in the time-series data, wherein the second set of the pre-defined trigger configurations uses information available to the time-series server device but not available in the time-series data nor the second set of the pre-defined trigger configurations;

storing, in transition storage of the time-series server device, representations of the observed states and state transitions;
receiving, by the time-series server device and from a client device, a request for the observed states and state transitions; and
transmitting, by the time-series server device and to the client device, a representation of the observed states and state transitions.

12. The method of claim 11 , wherein the pre-defined trigger configurations and the stream of time-series data are received from the client device.

13. The method of claim 11 , wherein the time-series data includes, for a particular computing device of the computing devices, measurements of a performance indicator, and wherein a particular trigger configuration of the pre-defined trigger configurations defines a state transition in which the performance indicator crosses a threshold value.

14. The method of claim 11 , wherein the time-series data includes, for a particular computing device of the computing devices, measurements of a performance indicator, and wherein a particular trigger configuration of the pre-defined trigger configurations defines a state transition in which the performance indicator is on one side of a threshold value for m measurements out of a previous n consecutive measurements.

15. The method of claim 11 ,
wherein the first set of the pre-defined trigger configurations can be applied using respective individual measurements i

Assignees

• Servicenow Inc

Inventors

• Baxa Olivier
• Wang Paul
• Seguin Vincent

Classifications

• H04L41/0853

  by actively collecting configuration information or by backing up configuration information · CPC title

• H04L41/0843

  based on generic templates · CPC title

• H04L41/0695

  the faulty arrangement being the maintenance, administration or management system · CPC title

• H04L41/082

  the condition being updates or upgrades of network functionality · CPC title

• H04L41/0893

  Assignment of logical groups to network elements · CPC title