Intelligent data propagation using performance monitoring

• US 9,621,654 B2
• Filed: 12/21/2015
• Issued: 04/11/2017
• Est. Priority Date: 11/14/2013
• Status: Active Grant

• Current Assignee: Vmware LLC (Broadcom, Inc.)
• Original Assignee: VMware, Inc. (Broadcom, Inc.)
• Inventors: Magdon-Ismail, Tariq, Cheveresan, Razvan
• Primary Examiner(s): THAI, HANH B
• Application Number:
  US14/977,434
• Publication Number:
  US 20160191625A1
• Time in Patent Office: 477 Days
• Field of Search: 707610, 707626, 707639
• CPC Class Codes: G06F 16/128 Details of file system snapshots on the file-level, e.g. snapshot creation, administration, deletion use of snapshots for error detection or correction G06F11/14, G06F11/16
• CPC Class Codes: G06F 16/182 Distributed file systems
• CPC Class Codes: G06F 16/27 Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 3/06 Digital input from, or digital output to, record carriers , e.g. RAID, emulated record carriers or networked record carriers
• CPC Class Codes: G06F 3/0611 in relation to response time
• CPC Class Codes: G06F 3/0635 by changing the path, e.g. traffic rerouting, path reconfiguration
• CPC Class Codes: G06F 3/065 Replication mechanisms
• CPC Class Codes: G06F 3/067 Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
• CPC Class Codes: H04L 41/12 Discovery or management of network topologies
• CPC Class Codes: H04L 43/087 Jitter
• CPC Class Codes: H04L 43/0876 Network utilisation, e.g. volume of load or congestion level
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 45/12 Shortest path evaluation
• CPC Class Codes: H04L 67/1097 for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]

Abstract

Exemplary methods, apparatuses, and systems that can intelligently copy data to a plurality of datastores using performance monitoring are described. In one embodiment, a shortest path tree determines the most efficient paths available for copying data from a source datastore to one or more destination datastores. During the copying of the data between a source datastore and the one or more destination datastores, a performance value of each of the datastores involved in the copying process is compared to a threshold. In response to determining that the performance value of a given source or destination datastore involved in the copying exceeds the threshold, the copying of the data to the corresponding destination datastore is suspended. An updated shortest path tree is determined to locate a more efficient path for copying data to the suspended destination datastore. Copying is resumed to the suspended destination datastore using the updated shortest path tree.

Claims

1. A computer-implemented method comprising:

copying data to a plurality of datastores, wherein the copying of the data includes determining a path from a source datastore to a remainder of the plurality of datastores;

determining that one of the plurality of datastores has exceeded a performance threshold during the copying of the data to the datastore or during the copying of the data from the datastore;

suspending the copying of the data to or from the datastore in response to the datastore exceeding the performance threshold;

determining an updated path from a source datastore to the datastore; and

resuming the copying of the data to the datastore using the updated path.

2. The computer-implemented method of claim 1, further comprising:

generating a snapshot of a virtual machine from the source datastore; and

running a copy of the virtual machine on a host device using the snapshot while the copying is performed, wherein the data that is copied from the source datastore to one or more of the plurality of datastores is the virtual machine.

3. The computer-implemented method of claim 1, further comprising:

determining a distance value of a path between each of the plurality of datastores based upon a network performance measurement between the datastores; and

performing a graph cluster analysis using the distance values to create a plurality of clusters, wherein each cluster includes one or more of the datastores within close proximity to one another based upon the distance values.

4. The computer-implemented method of claim 3, further comprising:

determining a performance value for each datastore, wherein the datastore performance value is based on resource utilization, network latency, or I/O latency of the corresponding datastore; and

modifying the distance values using corresponding datastore performance values of one or more datastores in the corresponding path, wherein the graph cluster analysis uses the modified distance values.

5. The computer-implemented method of claim 3, wherein the determination of the path or the updated path includes representing each datastore as a vertex in a shortest path tree, the source datastore as a root of the shortest path tree, and ordering each child vertex of the root in descending order according to a number of unique clusters to which descendants of the child vertex belong.

6. The computer-implemented method of claim 5, wherein the resuming the copying of the data on the datastore using the updated shortest path tree is based on the ordering each child vertex of the root in descending order according to a number of unique clusters to which descendants of the child vertex belong.

7. The computer-implemented method of claim 5, wherein the ordering each child vertex in the shortest path tree or the updated shortest path tree in descending order is further based upon a number of children of each child vertex, resource utilization of each child vertex'"'"'s corresponding datastore, I/O latency of each child vertex'"'"'s corresponding datastore, or network latency of each child vertex'"'"'s corresponding datastore.

8. The computer-implemented method of claim 5, wherein copying the data comprises:

copying the data from the source datastore to a datastore represented by a first child vertex of the source datastore;

promoting the first child vertex to a new source datastore upon completion of the copying of the data to the first child vertex;

ordering each child vertex of the new source datastore in descending order according to a number of unique clusters to which descendants of the child vertex of the new source datastore belong; and

copying the data from the new source datastore to one or more of the plurality of datastores in the descending order of the child vertices of the new source datastore.

9. The computer-implemented method of claim 5 wherein the determining an updated shortest path tree is in response to a threshold number of times the data is copied to the plurality of datastores, the updated shortest path tree including an updated source datastore that is one of the source datastore and another datastore storing a copy of the data, the method further comprising:

ordering each child vertex of the updated source datastore in descending order according to a number of unique clusters to which descendants of the child vertex of the updated source datastore belong; and

copying the data from the updated source datastore to one or more of the plurality of datastores in the descending order of the child vertices of the updated source datastore.

10. A non-transitory computer-readable medium storing instructions, which when executed by a processing device, cause the processing device to perform a method comprising:

copying data to a plurality of datastores, wherein the copying of the data includes determining a path from a source datastore to a remainder of the plurality of datastores;

determining that one of the plurality of datastores has exceeded a performance threshold during the copying of the data to the datastore or during the copying of the data from the datastore;

suspending the copying of the data to or from the datastore in response to the datastore exceeding the performance threshold;

determining an updated path from a source datastore to the datastore; and

resuming the copying of the data to the datastore using the updated path.

11. The non-transitory computer-readable medium of claim 10, the method further comprising:

generating a snapshot of a virtual machine from the source datastore; and

running a copy of the virtual machine on a host device using the snapshot while the copying is performed, wherein the data that is copied from the source datastore to one or more of the plurality of datastores is the virtual machine.

12. The non-transitory computer-readable medium of claim 10, the method further comprising:

determining a distance value of a path between each of the plurality of datastores based upon a network performance measurement between the datastores; and

performing a graph cluster analysis using the distance values to create a plurality of clusters, wherein each cluster includes one or more of the datastores within close proximity to one another based upon the distance values.

13. The non-transitory computer-readable medium of claim 12, the method further comprising:

determining a performance value for each datastore, wherein the datastore performance value is based on resource utilization, network latency, or I/O latency of the corresponding datastore; and

modifying the distance values using corresponding datastore performance values of one or more datastores in the corresponding path, wherein the graph cluster analysis uses the modified distance values.

14. The non-transitory computer-readable medium of claim 12, wherein the determination of the path or the updated path includes representing each datastore as a vertex in a shortest path tree, the source datastore as a root of the shortest path tree, and ordering each child vertex of the root in descending order according to a number of unique clusters to which descendants of the child vertex belong.

15. The non-transitory computer-readable medium of claim 14, wherein the resuming the copying of the data on the datastore using the updated shortest path tree is based on the ordering each child vertex of the root in descending order according to a number of unique clusters to which descendants of the child vertex belong.

16. The non-transitory computer-readable medium of claim 14, wherein the ordering each child vertex in the shortest path tree or the updated shortest path in descending order is further based upon a number of children of each child vertex, resource utilization of each child vertex'"'"'s corresponding datastore, I/O latency of each child vertex'"'"'s corresponding datastore, or network latency of each child vertex'"'"'s corresponding datastore.

17. The non-transitory computer-readable medium of claim 14, wherein copying the data comprises:

copying the data from the source datastore to a datastore represented by a first child vertex of the source datastore;

promoting the first child vertex to a new source datastore upon completion of the copying of the data to the first child vertex;

ordering each child vertex of the new source datastore in descending order according to a number of unique clusters to which descendants of the child vertex of the new source datastore belong; and

copying the data from the new source datastore to one or more of the plurality of datastores in the descending order of the child vertices of the new source datastore.

18. The computer implemented method of claim 14, wherein the determining an updated shortest path tree is in response to a threshold number of times the data is copied to the plurality of datastores, the updated shortest path tree including an updated source datastore that is one of the source datastore and another datastore storing a copy of the data, the method further comprising:

ordering each child vertex of the updated source datastore in descending order according to a number of unique clusters to which descendants of the child vertex of the updated source datastore belong; and

copying the data from the updated source datastore to one or more of the plurality of datastores in the descending order of the child vertices of the updated source datastore.

19. An apparatus comprising:

a processing device, wherein the processing device executes instructions that cause the apparatus to perform a method comprising;

copying data to a plurality of datastores, wherein the copying of the data includes determining a path from a source datastore to a remainder of the plurality of datastores;

determining that one of the plurality of datastores has exceeded a performance threshold during the copying of the data to the datastore or during the copying of the data from the datastore;

suspending the copying of the data to or from the datastore in response to the datastore exceeding the performance threshold;

determining an updated path from a source datastore to the datastore; and

resuming the copying of the data to the datastore using the updated path.

20. The apparatus of claim 19, the method further comprising:

determining a distance value of a path between each of the plurality of datastores based upon a network performance measurement between the datastores; and

performing a graph cluster analysis using the distance values to create a plurality of clusters, wherein each cluster includes one or more of the datastores within close proximity to one another based upon the distance values, wherein the determination of the shortest path tree or the updated shortest path tree includes representing each datastore as a vertex in the shortest path tree, the source datastore as a root of the shortest path tree, and ordering each child vertex of the root in descending order according to a number of unique clusters to which descendants of the child vertex belong.