US 12,008,418 B2Granted

Automated causal analysis of issues affecting workloads executing in an information technology infrastructure

AssigneeDell Products L.P.

InventorsVindhya Gangaraju, Vinay Sawal, Jayanth Kumar Reddy Perneti

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Abstract

An apparatus comprises a processing device configured to obtain workload traces characterizing resource execution metrics associated with workloads executing in an information technology infrastructure and to generate sets of workload causality profiles characterizing relationships between the resource execution metrics, the sets of workload causality profiles comprising first and at least second sets of workload causality profiles generated using first and at least second different types of models. The processing device is also configured to determine sets of causal topics comprising recurring patterns of the relationships between different ones of the resource execution metrics found in each of the sets of workload causality profiles. The processing device is further configured to identify clusters of causal topics each comprising at least one causal topic that is part of the first and second sets of causal topics, and to perform diagnosis of issues affecting the workloads based on the identified clusters.

Claims20

Dependent claims

An apparatus comprising:

at least one processing device comprising a processor coupled to a memory;
the at least one processing device being configured:
to execute a first set of a plurality of workloads on a set of storage systems of an information technology infrastructure, wherein executing the first set of the plurality of workloads produces a plurality of workload traces characterizing resource execution metrics associated with the execution of the first set of the plurality of workloads, wherein one of the resource execution metrics comprises an execution time of at least a subset of the first set of the plurality of workloads;
responsive to an occurrence of one or more issues causing the execution time of the subset of the first set of the plurality of workloads to exceed an expected execution time, to at least one of (i) expand at least one storage system in the set of storage systems of the information technology infrastructure, and (ii) deploy one or more additional storage systems in the set of storage systems of the information technology infrastructure;
and
to execute a second set of the plurality of workloads on the set of storage systems in the information technology infrastructure;
wherein the occurrence of the one or more issues is based at least in part on one or more clusters of causal topics that comprise at least one causal topic that is part of a first set of causal topics and a second set of causal topics, the first set of causal topics being based at least in part on a first set of recurring patterns of relationships between different ones of the resource execution metrics in a first set of workload causality profiles, the first set of workload causality profiles being based at least in part on a dependence measurement model and the plurality of workload traces, the second set of causal topics being based at least in part on a second set of recurring patterns of relationships between different ones of the resource execution metrics in a second set of workload causality profiles, and the second set of workload causality profiles being based at least in part on a causal model and the plurality of workload traces.

4 more elements

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:

to execute a first set of a plurality of workloads on a set of storage systems of an information technology infrastructure, wherein executing the first set of the plurality of workloads produces a plurality of workload traces characterizing resource execution metrics associated with the execution of the first set of the plurality of workloads, wherein one of the resource execution metrics comprises an execution time of at least a subset of the first set of the plurality of workloads;
responsive to an occurrence of one or more issues causing the execution time of the subset of the first set of the plurality of workloads to exceed an expected execution time, to at least one of (i) expand at least one storage system in the set of storage systems of the information technology infrastructure, and (ii) deploy one or more additional storage systems in the set of storage systems of the information technology infrastructure;
and
to execute a second set of the plurality of workloads on the set of storage systems of the information technology infrastructure;
wherein the occurrence of the one or more issues is based at least in part on one or more clusters of causal topics that comprise at least one causal topic that is part of a first set of causal topics and a second set of causal topics, the first set of causal topics being based at least in part on a first set of recurring patterns of relationships between different ones of the resource execution metrics in a first set of workload causality profiles, the first set of workload causality profiles being based at least in part on a dependence measurement model and the plurality of workload traces, the second set of causal topics being based at least in part on a second set of recurring patterns of relationships between different ones of the resource execution metrics in a second set of workload causality profiles, and the second set of workload causality profiles being based at least in part on a causal model and the plurality of workload traces.

2 more elements

A method comprising:

executing a first set of a plurality of workloads on a set of storage systems of an information technology infrastructure, wherein executing the first set of the plurality of workloads produces a plurality of workload traces characterizing resource execution metrics associated with the execution of the first set of the plurality of workloads, wherein one of the resource execution metrics comprises an execution time of at least a subset of the first set of the plurality of workloads;
responsive to an occurrence of one or more issues causing the execution time of the subset of the first set of the plurality of workloads to exceed an expected execution time, at least one of (i) expanding at least one storage system in the set of storage systems of the information technology infrastructure, and (ii) deploying one or more additional storage systems in the set of storage systems of the information technology infrastructure;
executing a second set of the plurality of workloads on the set of storage systems in the information technology infrastructure;
wherein the occurrence of the one or more issues is based at least in part on one or more clusters of causal topics that comprise at least one causal topic that is part of a first set of causal topics and a second set of causal topics, the first set of causal topics being based at least in part on a first set of recurring patterns of relationships between different ones of the resource execution metrics in a first set of workload causality profiles, the first set of workload causality profiles being based at least in part on a dependence measurement model and the plurality of workload traces, the second set of causal topics being based at least in part on a second set of recurring patterns of relationships between different ones of the resource execution metrics in a second set of workload causality profiles, and the second set of workload causality profiles being based at least in part on a causal model and the plurality of workload traces;
and
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.

3 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/462,710Filed 31 Aug 2021
Published: US 2023/0066843 A12 Mar 2023
Granted: 11 Jun 2024
Term ends: Not estimatedThe source records don’t support an estimate.

Classification5 codes

G06F 9/5083
Allocation of resources, e.g. of the central processing unit [CPU]: techniques for rebalancing the load in a distributed system
G06F 11/1446
Error detection or correction of the data by redundancy in operations: point-in-time backing up or restoration of persistent data
G06F 11/1448
Point-in-time backing up or restoration of persistent data: management of the data involved in backup or backup restore
G06F 2201/805
Indexing scheme relating to error detection, to error correction, and to monitoring: real-time

Family

US 2023/0066843 A1Pre-grant publication · published 2 Mar 2023
US 12,008,418 B2This patent

From the US filing history. Foreign family members aren’t listed.

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