IP Library Granted Patent US 12,373,126
Granted Patent B2
US 12,373,126 · App. 18/297,452 · Granted Jul 29, 2025

Uniform model for distinct types of data replication

Inventors: David Grunwald (San Francisco, CA); Thomas Gill (Bury St Edmunds, GB); Ronald Karr (Palo Alto, CA); Matthew Fay (Mountain View, CA); Luke Paulsen (Mountain View, CA); John Colgrove (Los Altos, CA)
Assignee: PURE STORAGE, INC.
G06F3/065G06F3/0614G06F3/067G06F11/1458G06F16/2379G06F16/27G06F16/383G06F2201/84
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Quick Facts
Patent No.
US 12,373,126
App. No.
18/297,452
Granted
Jul 29, 2025
Kind
B2
Abstract

A uniform model for distinct types of data replication, including receiving, at a source data repository, an update to a dataset; generating, based on the update to the dataset, both metadata describing the update to the dataset and also a metadata representation of the dataset; and initiating, based on the same metadata describing the update to the dataset and also based on the same metadata representation of the dataset, either a first type of data replication or a second type of data replication from among a plurality of types of data replication.

Claims (29)

1. A method comprising:

receiving an update to a dataset that is being replicated with a first type of replication, the dataset being represented by a metadata representation that is used when replicating the dataset with the first type of replication or with a second type of replication;

generating, based on the received update to the dataset, an update to the metadata representation of the dataset, the metadata representation including one or more logical representations of portions of the dataset; and

using the update to the metadata representation that was generated during replication of the dataset with the first type of replication, replicating the update with the second type of replication.

2. The method of claim 1 , wherein the first type of data replication is a distinct type of data replication from the second type of data replication.

3. The method of claim 2 , wherein the first type of data replication and the second type of data replication are among a plurality of types of data replication, including synchronous replication, configurable asynchronous data replication, periodic data replication, snapshot-based data replication, continuous data replication, and a combination of configurable asynchronous data replication and dynamically determined snapshot updates.

4. The method of claim 3 , wherein the dynamically determined snapshot updates are based on asynchronous data replication not occurring with sufficient frequency to prevent surpassing a backlog threshold.

5. The method of claim 4 , wherein subsequent to sending one or more snapshot updates from a source data repository to a target data repository, asynchronous data replication continues from the source data repository to the target data repository without snapshots while the data replication occurs with sufficient frequency to prevent surpassing the backlog threshold.

6. The method of claim 1 , wherein the metadata representation references content identifiers on a respective source data repository and target data repository, wherein the content identifiers are a basis for avoiding transfer of data based on identifying content on the target data repository that is the same as content on the source data repository, and wherein content is identified as being the same based on sharing a common definition for respective content identifiers on the source data repository and the target data repository.

7. The method of claim 1 , wherein the one or more logical representations include metadata object nodes, wherein leaf nodes include pointers to respective data objects.

8. The method of claim 1 , wherein the metadata representation includes one or more metadata objects that are representative of content of the dataset as distinct from one or more content identifiers used to identify the dataset.

9. A storage system that includes a computer memory and a computer processor, the computer memory including program instructions that, when executed by the computer processor, cause the storage system to carry out the steps of:

receiving an update to a dataset that is being replicated with a first type of replication, the dataset being represented by a metadata representation that is used when replicating the dataset with the first type of replication or with a second type of replication;

generating, based on the received update to the dataset, an update to the metadata representation of the dataset, the metadata representation including one or more logical representations of portions of the dataset; and

using the update to the metadata representation that was generated during replication of the dataset with the first type of replication, replicating the update with the second type of replication.

10. The storage system of claim 9 , wherein the first type of data replication is distinct type of data replication from the second type of data replication.

11. The storage system of claim 10 , wherein the first type of data replication and the second type of data replication are among a plurality of types of data replication, including synchronous replication, configurable asynchronous data replication, periodic data replication, snapshot-based data replication, continuous data replication, and a combination of configurable asynchronous data replication and dynamically determined snapshot updates.

12. The storage system of claim 11 , wherein the dynamically determined snapshot updates are based on asynchronous data replication not occurring with sufficient frequency to prevent surpassing a backlog threshold.

13. The storage system of claim 12 , wherein subsequent to sending one or more snapshot updates from a source data repository to a target data repository, asynchronous data replication continues from the source data repository to the target data repository without snapshots while the data replication occurs with sufficient frequency to prevent surpassing the backlog threshold.

14. The storage system of claim 13 , wherein data and metadata included within a snapshot is excluded from subsequent data and metadata transfers in subsequent asynchronous data replication transfers from the source data repository to the target data repository.

15. The storage system of claim 9 , wherein the update to the dataset is included within an ordered log of metadata comprising one or more checkpoints.

16. The storage system of claim 9 , wherein the one or more logical representations include metadata object nodes, wherein leaf nodes include pointers to respective data objects.

17. The storage system of claim 9 , wherein the metadata representation includes one or more metadata objects that are representative of content of the dataset as distinct from one or more content identifiers used to identify the dataset.

18. An apparatus comprising a computer processor, a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, cause the apparatus to carry out the steps of:

receiving an update to a dataset that is being replicated with a first type of replication, the dataset being represented by a metadata representation that is used when replicating the dataset with the first type of replication or with a second type of replication;

generating, based on the received update to the dataset, an update to the metadata representation of the dataset, the metadata representation including one or more logical representations of portions of the dataset; and

using the update to the metadata representation that was generated during replication of the dataset with the first type of replication, replicating the update with the second type of replication.

19. The apparatus of claim 18 , wherein the one or more logical representations include metadata object nodes, wherein leaf nodes include points to respective data objects.

20. The apparatus of claim 18 , wherein the metadata representation includes one or more metadata objects that are representative of content of the dataset as distinct from one or more content identifiers used to identify the dataset.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 7, 2023
From: GRUNWALD, DAVID; GILL, THOMAS; KARR, RONALD; FAY, MATTHEW; PAULSEN, LUKE; COLGROVE, JOHN
To: PURE STORAGE, INC.
Reel/Frame 063262/0679 →
Continuity (3)
Continuation 16668664 · Oct 30, 2019
Provisional Application 62900330 · Sep 13, 2019
Related Publication 20230266908A1 · Aug 24, 2023
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