IP Library › Granted Patent US 12,250,129
Granted Patent B2
US 12,250,129 · App. 17/549,417 · Granted Mar 11, 2025

Proportional quality of service based on client usage and system metrics

Inventors: David D. Wright (Dacula, GA); Michael Xu (Boulder, CO)
Assignee: NetApp, Inc.
H04L41/5022G06F3/061G06F3/0659G06F3/067G06F11/3433G06F11/3485H04L41/50H04L41/5009H04L41/5067H04L67/1008H04L67/1097G06F2201/81
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Quick Facts
Patent No.
US 12,250,129
App. No.
17/549,417
Granted
Mar 11, 2025
Kind
B2
Abstract

Examples described herein are generally directed to providing a fair amount of throughput to multiple clients of a storage system. According to one example, the storage system determines system metrics based upon use of the storage system by the clients. A system load value is calculated based upon the system metrics. The system load value quantifies a load on the storage system by the clients. Client loads, each representing a contribution to the use of the storage system by an individual client, are calculated and expressed as a relative degree or amount of the system load value. A target performance value for a client is calculated based on the client load for the client and a quality of service parameter value provisioned for the client to access the storage system. Based on the target performance value, latency for the client is introduced or removed.

Claims (37)

1. A distributed storage system comprising:

a processing resource; and

a non-transitory computer-readable medium, coupled to the processing resource, having stored therein instructions that when executed by the processing resource cause the distributed storage system to:

determine system metrics of the distributed storage system based upon use of the distributed storage system by a plurality of clients;

calculate a system load value based upon the system metrics, wherein the system load value quantifies a load on the distributed storage system by the plurality of clients;

calculate client loads for the plurality of clients, wherein each client load of the client loads represents a contribution to the use of the distributed storage system by an individual client of the plurality of clients and is expressed as a relative degree or amount of the system load value;

calculate a target performance value for a first client of the plurality of clients based on the calculated client load corresponding to the first client, and based on a quality of service parameter value provisioned for the first client to access the distributed storage system; and

adjust a level of performance provided by the distributed storage system to the first client by introducing or removing a latency for the first client based upon the target performance value.

2. The distributed storage system of claim 1 , wherein service load values are calculated based on read latency or write latency relating to read operations or write operations, respectively, associated with a plurality of services, and wherein the service load values are used as input to quality of service functionality.

3. The distributed storage system of claim 1 , wherein each of the client loads is calculated based on a measured amount of read latency or write latency relating to services that have been assigned to handle read, write or replication operations for the clients.

4. The distributed storage system of claim 1 , wherein the system metrics are calculated at a system level, a cluster level, a node level, a service level, or a drive level.

5. The distributed storage system of claim 4 , wherein the distributed storage system includes a plurality of nodes and the system metrics are calculated at the node level.

6. The distributed storage system of claim 5 , wherein the relative degree or amount of the system load value for the first client comprises a maximum of write latency load values associated with two different nodes of the plurality of nodes associated with the first client.

7. The distributed storage system of claim 1 , wherein the system metrics include measured or aggregated metrics including one or more of read latency, write latency, input/output (I/O) operations per second (IOPS), read IOPS, write IOPS, I/O size, write cache capacity, dedupeability, compressibility, total bandwidth, read bandwidth, write bandwidth, read/write ratio, workload type, data content, and data type.

8. The distributed storage system of claim 1 , wherein introduction of the latency for the first client is based on the target performance value and determining that the system load value is above a predefined threshold.

9. The distributed storage system of claim 1 , wherein the system load value is determined based upon a plurality of load values associated with the first client, wherein the system load value comprises a maximum value of write latency load values associated with two different servers of the distributed storage system, and wherein the two different servers are both associated with the first client.

10. A non-transitory computer-readable medium having instructions stored thereon, which when executable by one or more processors of a distributed storage system, cause the distributed storage system to:

determine system metrics of the distributed storage system based upon use of the distributed storage system by a plurality of clients;

calculate a system load value based upon the system metrics, wherein the system load value quantifies a load on the distributed storage system by the plurality of clients;

calculate client loads for the plurality of clients, wherein each client load of the client loads represents a contribution to the use of the distributed storage system by an individual client of the plurality of clients and is expressed as a relative degree or amount of the system load value;

calculate a target performance value for a first client of the plurality of clients based on the calculated client load corresponding to the first client, and based on a quality of service parameter value provisioned for the first client to access the distributed storage system; and

adjust a level of performance provided by the distributed storage system to the first client by introducing or removing a latency for the first client based upon the target performance value.

11. The non-transitory computer-readable medium of claim 10 , wherein service load values are calculated based on read latency or write latency relating to read operations or write operations, respectively, associated with a plurality of services, and wherein the service load values are used as input to quality of service functionality.

12. The non-transitory computer-readable medium of claim 10 , wherein each of the client loads is calculated based on a measured amount of read latency or write latency relating to services that have been assigned to handle read, write or replication operations for the clients.

13. The non-transitory computer-readable medium of claim 10 , wherein the system metrics are calculated at a system level, a cluster level, a node level, a service level, or a drive level.

14. The non-transitory computer-readable medium of claim 13 , wherein the distributed storage system includes a plurality of nodes and the system metrics are calculated at the node level.

15. The non-transitory computer-readable medium of claim 14 , wherein the relative degree or amount of the system load value for the first client comprises a maximum of write latency load values associated with two different nodes of the plurality of nodes associated with the first client.

16. The non-transitory computer-readable medium of claim 10 , wherein the system metrics include measured or aggregated metrics including one or more of read latency, write latency, input/output (I/O) operations per second (IOPS), read IOPS, write IOPS, I/O size, write cache capacity, dedupeability, compressibility, total bandwidth, read bandwidth, write bandwidth, read/write ratio, workload type, data content, and data type.

17. The non-transitory computer-readable medium of claim 10 , wherein introduction of the latency for the first client is based on the target performance value and determining that the system load value is above a predefined threshold.

18. The non-transitory computer-readable medium of claim 10 , wherein the system load value is determined based upon a plurality of load values associated with the first client, wherein the system load value comprises a maximum value of write latency load values associated with two different servers of the distributed storage system, and wherein the two different servers are both associated with the first client.

19. A method comprising:

determining system metrics of a distributed storage system based upon use of the distributed storage system by a plurality of clients;

calculating a system load value based upon the system metrics, wherein the system load value quantifies a load on the distributed storage system by the plurality of clients;

calculating client loads for the plurality of clients, wherein each client load of the client loads represents a contribution to the use of the distributed storage system by an individual client of the plurality of clients and is expressed as a relative degree or amount of the system load value;

calculating a target performance value for a first client of the plurality of clients based on the calculated client load corresponding to the first client, and based on a quality of service parameter value provisioned for the first client to access the distributed storage system; and

adjust a level of performance provided by the distributed storage system to the first client by introducing or removing a latency for the first client based upon the target performance value.

20. The method of claim 19 , wherein introduction of the latency for the first client is based on the target performance value and determining that the system load value represents an overload condition in which the system load value exceeds a predefined threshold.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 13, 2021
From: LESSO, JOHN PAUL; HATFIELD, ROBERT JAMES
To: WOLFSON MICROELECTRONICS PLC
Reel/Frame 058375/0766 →
Continuity (9)
Continuation 17163679 · Feb 1, 2021
Continuation 16588594 · Sep 30, 2019
Continuation 15651438 · Jul 17, 2017
Continuation 14701832 · May 1, 2015
Continuation 13856997 · Apr 4, 2013
Continuation PCTUS2012071844 · Dec 27, 2012
Continuation In Part 13338039 · Dec 27, 2011
Provisional Application 61697905 · Sep 7, 2012
Related Publication 20220103436A1 · Mar 31, 2022
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