System and method for asynchronously transferring replication data

A method, computer program product, and computing system for determining a recovery point object (RPO) value for a storage object. An amount of data to transfer from the storage object to a disaster recovery site is determined. A data replication transfer schedule for the storage object is generated based upon, at least in part, the RPO value and the amount of data to transfer. Data is asynchronously transferred from the storage object to the disaster recovery site using the data replication transfer schedule.

BACKGROUND

Storing and safeguarding electronic content may be beneficial in modern business and elsewhere. Accordingly, various methodologies may be employed to protect and distribute such electronic content.

For example, data services like asynchronous replication preserve data but have an impact on host input/output (IO) request latency. Asynchronous replication depends on refreshing snapshots and the snapshot creation and deletion associated with snapshot refresh has an impact. Additionally, further latency impacts are due to the steps involved in data transfer of the changes to a disaster recovery (DR) site and this includes the calculation of differences between two snapshots used for asynchronous replication and the transfer of the differences or deltas. In this manner, data services such as asynchronous replication compete for resources with host applications and impact host latency. Users generally need these additional data services on top of the host applications and while users understand that host latency will be impacted, the impact should be as minimal as possible.

SUMMARY OF DISCLOSURE

In one example implementation, a computer-implemented method executed on a computing device may include, but is not limited to, determining a recovery point object (RPO) value for a storage object. An amount of data to transfer from the storage object to a disaster recovery site is determined. A data replication transfer schedule for the storage object is generated based upon, at least in part, the RPO value and the amount of data to transfer. Data is asynchronously transferred from the storage object to the disaster recovery site using the data replication transfer schedule.

One or more of the following example features may be included. A priority may be determined of each storage object. Generating the data replication transfer schedule for the storage object may be further based upon, at least in part, the priority of each storage object. An asynchronous data transfer capacity may be determined for the storage object. Generating the data replication transfer schedule for the storage object may be further based upon, at least in part, the asynchronous data transfer capacity for the storage object. The RPO value and the amount of data to transfer from the storage object may be periodically re-determined. The data replication transfer schedule may be adjusted based upon, at least in part, a change in one or more of the RPO value and the amount of data to transfer from the storage object.

In another example implementation, a computer program product resides on a computer readable medium that has a plurality of instructions stored on it. When executed by a processor, the instructions cause the processor to perform operations that may include, but are not limited to, determining a recovery point object (RPO) value for a storage object. An amount of data to transfer from the storage object to a disaster recovery site is determined. A data replication transfer schedule for the storage object is generated based upon, at least in part, the RPO value and the amount of data to transfer. Data is asynchronously transferred from the storage object to the disaster recovery site using the data replication transfer schedule.

One or more of the following example features may be included. A priority may be determined of each storage object. Generating the data replication transfer schedule for the storage object may be further based upon, at least in part, the priority of each storage object. An asynchronous data transfer capacity may be determined for the storage object. Generating the data replication transfer schedule for the storage object may be further based upon, at least in part, the asynchronous data transfer capacity for the storage object. The RPO value and the amount of data to transfer from the storage object may be periodically re-determined. The data replication transfer schedule may be adjusted based upon, at least in part, a change in one or more of the RPO value and the amount of data to transfer from the storage object.

In another example implementation, a computing system includes at least one processor and at least one memory architecture coupled with the at least one processor, wherein the at least one processor configured to determine a recovery point object (RPO) value for a storage object. An amount of data to transfer from the storage object to a disaster recovery site is determined. A data replication transfer schedule for the storage object is generated based upon, at least in part, the RPO value and the amount of data to transfer. Data is asynchronously transferred from the storage object to the disaster recovery site using the data replication transfer schedule.

One or more of the following example features may be included. A priority may be determined of each storage object. Generating the data replication transfer schedule for the storage object may be further based upon, at least in part, the priority of each storage object. An asynchronous data transfer capacity may be determined for the storage object. Generating the data replication transfer schedule for the storage object may be further based upon, at least in part, the asynchronous data transfer capacity for the storage object. The RPO value and the amount of data to transfer from the storage object may be periodically re-determined. The data replication transfer schedule may be adjusted based upon, at least in part, a change in one or more of the RPO value and the amount of data to transfer from the storage object.

DETAILED DESCRIPTION

Referring toFIG.1, there is shown data replication process10that may reside on and may be executed by storage system12, which may be connected to network14(e.g., the Internet or a local area network). Examples of storage system12may include, but are not limited to: a Network Attached Storage (NAS) system, a Storage Area Network (SAN), a personal computer with a memory system, a server computer with a memory system, and a cloud-based device with a memory system.

As is known in the art, a SAN may include one or more of a personal computer, a server computer, a series of server computers, a mini computer, a mainframe computer, a RAID device and a NAS system. The various components of storage system12may execute one or more operating systems, examples of which may include but are not limited to: Microsoft® Windows®; Mac® OS X®; Red Hat® Linux®, Windows® Mobile, Chrome OS, Blackberry OS, Fire OS, or a custom operating system. (Microsoft and Windows are registered trademarks of Microsoft Corporation in the United States, other countries or both; Mac and OS X are registered trademarks of Apple Inc. in the United States, other countries or both; Red Hat is a registered trademark of Red Hat Corporation in the United States, other countries or both; and Linux is a registered trademark of Linus Torvalds in the United States, other countries or both).

The instruction sets and subroutines of data replication process10, which may be stored on storage device16included within storage system12, may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within storage system12. Storage device16may include but is not limited to: a hard disk drive; a tape drive; an optical drive; a RAID device; a random access memory (RAM); a read-only memory (ROM); and all forms of flash memory storage devices. Additionally/alternatively, some portions of the instruction sets and subroutines of data replication process10may be stored on storage devices (and/or executed by processors and memory architectures) that are external to storage system12.

Various IO requests (e.g. IO request20) may be sent from client applications22,24,26,28to storage system12. Examples of IO request20may include but are not limited to data write requests (e.g., a request that content be written to storage system12) and data read requests (e.g., a request that content be read from storage system12).

The instruction sets and subroutines of client applications22,24,26,28, which may be stored on storage devices30,32,34,36(respectively) coupled to client electronic devices38,40,42,44(respectively), may be executed by one or more processors (not shown) and one or more memory architectures (not shown) incorporated into client electronic devices38,40,42,44(respectively). Storage devices30,32,34,36may include but are not limited to: hard disk drives; tape drives; optical drives; RAID devices; random access memories (RAM); read-only memories (ROM), and all forms of flash memory storage devices. Examples of client electronic devices38,40,42,44may include, but are not limited to, personal computer38, laptop computer40, smartphone42, notebook computer44, a server (not shown), a data-enabled, cellular telephone (not shown), and a dedicated network device (not shown).

Users46,48,50,52may access storage system12directly through network14or through secondary network18. Further, storage system12may be connected to network14through secondary network18, as illustrated with link line54.

Client electronic devices38,40,42,44may each execute an operating system, examples of which may include but are not limited to Microsoft® Windows®; Mac® OS X®; Red Hat® Linux®, Windows® Mobile, Chrome OS, Blackberry OS, Fire OS, or a custom operating system. (Microsoft and Windows are registered trademarks of Microsoft Corporation in the United States, other countries or both; Mac and OS X are registered trademarks of Apple Inc. in the United States, other countries or both; Red Hat is a registered trademark of Red Hat Corporation in the United States, other countries or both; and Linux is a registered trademark of Linus Torvalds in the United States, other countries or both).

In some implementations, as will be discussed below in greater detail, a data replication process, such as data replication process10ofFIG.1, may include but is not limited to, determining a recovery point object (RPO) value for a storage object. An amount of data to transfer from the storage object to a disaster recovery site may be determined. A data replication transfer schedule for the storage object may be generated based upon, at least in part, the RPO value and the amount of data to transfer. Data may be asynchronously transferred from the storage object to the disaster recovery site using the data replication transfer schedule.

For example purposes only, storage system12will be described as being a network-based storage system that includes a plurality of electro-mechanical backend storage devices. However, this is for example purposes only and is not intended to be a limitation of this disclosure, as other configurations are possible and are considered to be within the scope of this disclosure.

The Storage System:

Referring also toFIG.2, storage system12may include storage processor100and a plurality of storage targets T 1-n (e.g., storage targets102,104,106,108). Storage targets102,104,106,108may be configured to provide various levels of performance and/or high availability. For example, one or more of storage targets102,104,106,108may be configured as a RAID 0 array, in which data is striped across storage devices (e.g., storage devices110) used to create the storage targets. By striping data across a plurality of storage targets, improved performance may be realized. However, RAID 0 arrays do not provide a level of high availability. Accordingly, one or more of storage targets102,104,106,108may be configured as a RAID 1 array, in which data is mirrored between storage devices used to create the storage targets. By mirroring data between storage devices, a level of high availability is achieved as multiple copies of the data are stored within storage system12.

While storage targets102,104,106,108are discussed above as being configured in a RAID 0 or RAID 1 array, this is for example purposes only and is not intended to be a limitation of this disclosure, as other configurations are possible. For example, storage targets102,104,106,108may be configured as a RAID 3, RAID 4, RAID 5 or RAID 6 array.

While in this particular example, storage system12is shown to include four storage targets (e.g. storage targets102,104,106,108), this is for example purposes only and is not intended to be a limitation of this disclosure. Specifically, the actual number of storage targets may be increased or decreased depending upon e.g., the level of redundancy/performance/capacity required.

Storage system12may also include one or more coded targets111. As is known in the art, a coded target may be used to store coded data that may allow for the regeneration of data lost/corrupted on one or more of storage targets102,104,106,108. An example of such a coded target may include but is not limited to a hard disk drive that is used to store parity data within a RAID array.

While in this particular example, storage system12is shown to include one coded target (e.g., coded target111), this is for example purposes only and is not intended to be a limitation of this disclosure. Specifically, the actual number of coded targets may be increased or decreased depending upon e.g. the level of redundancy/performance/capacity required.

Storage targets102,104,106,108and coded target111may be created as volumes using one or more electro-mechanical hard disk drives and/or solid-state/flash devices (e.g., storage devices110), wherein a combination of storage targets102,104,106,108and coded target111and processing/control systems (not shown) may form data array112.

The manner in which storage system12is implemented may vary depending upon e.g. the level of redundancy/performance/capacity required. For example, storage system12may be a RAID device in which storage processor100is a RAID controller card and storage targets102,104,106,108and/or coded target111are individual “hot-swappable” hard disk drives. Another example of such a RAID device may include but is not limited to an NAS device. Alternatively, storage system12may be configured as a SAN, in which storage processor100may be e.g., a server computer and each of storage targets102,104,106,108and/or coded target111may be a RAID device and/or computer-based hard disk drives. Further still, one or more of storage targets102,104,106,108and/or coded target111may be a SAN.

In the event that storage system12is configured as a SAN, the various components of storage system12(e.g. storage processor100, storage targets102,104,106,108, and coded target111) may be coupled using network infrastructure114, examples of which may include but are not limited to an Ethernet (e.g., Layer2or Layer3) network, a fiber channel network, an InfiniBand network, or any other circuit switched/packet switched network.

Storage system12may execute all or a portion of data replication process10. The instruction sets and subroutines of data replication process10, which may be stored on a storage device (e.g., storage device16) coupled to storage processor100, may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within storage processor100. Storage device16may include but is not limited to: a hard disk drive; a tape drive; an optical drive; a RAID device; a random access memory (RAM); a read-only memory (ROM); and all forms of flash memory storage devices. As discussed above, some portions of the instruction sets and subroutines of data replication process10may be stored on storage devices (and/or executed by processors and memory architectures) that are external to storage system12.

As discussed above, various IO requests (e.g. IO request20) may be generated. For example, these IO requests may be sent from client applications22,24,26,28to storage system12. Additionally/alternatively and when storage processor100is configured as an application server, these IO requests may be internally generated within storage processor100. Examples of IO request20may include but are not limited to data write request116(e.g., a request that content118be written to storage system12) and data read request120(i.e. a request that content118be read from storage system12).

During operation of storage processor100, content118to be written to storage system12may be processed by storage processor100. Additionally/alternatively and when storage processor100is configured as an application server, content118to be written to storage system12may be internally generated by storage processor100.

Storage processor100may include frontend cache memory system122. Examples of frontend cache memory system122may include but are not limited to a volatile, solid-state, cache memory system (e.g., a dynamic RAM cache memory system) and/or a non-volatile, solid-state, cache memory system (e.g., a flash-based, cache memory system).

Storage processor100may initially store content118within frontend cache memory system122. Depending upon the manner in which frontend cache memory system122is configured, storage processor100may immediately write content118to data array112(if frontend cache memory system122is configured as a write-through cache) or may subsequently write content118to data array112(if frontend cache memory system122is configured as a write-back cache).

As discussed above, the instruction sets and subroutines of data replication process10, which may be stored on storage device16included within storage system12, may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within storage system12. Accordingly, in addition to being executed on storage processor100, some or all of the instruction sets and subroutines of data replication process10may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within data array112.

Further and as discussed above, during the operation of data array112, content (e.g., content118) to be written to data array112may be received from storage processor100and initially stored within backend cache memory system124prior to being stored on e.g. one or more of storage targets102,104,106,108,111. Accordingly, during use of data array112, backend cache memory system124may be populated (e.g., warmed) and, therefore, subsequent read requests may be satisfied by backend cache memory system124(e.g., if the content requested in the read request is present within backend cache memory system124), thus avoiding the need to obtain the content from storage targets102,104,106,108,111(which would typically be slower).

In some implementations, storage system12may include multi-node active/active storage clusters configured to provide high availability to a user. As is known in the art, the term “high availability” may generally refer to systems or components that are durable and likely to operate continuously without failure for a long time. For example, an active/active storage cluster may be made up of at least two nodes (e.g., storage processors100,124), both actively running the same kind of service(s) simultaneously. One purpose of an active-active cluster may be to achieve load balancing. Load balancing may distribute workloads across all nodes in order to prevent any single node from getting overloaded. Because there are more nodes available to serve, there will also be a marked improvement in throughput and response times. Another purpose of an active-active cluster may be to provide at least one active node in the event that one of the nodes in the active-active cluster fails.

In some implementations, storage processor124may function like storage processor100. For example, during operation of storage processor124, content118to be written to storage system12may be processed by storage processor124. Additionally/alternatively and when storage processor124is configured as an application server, content118to be written to storage system12may be internally generated by storage processor124.

Storage processor124may include frontend cache memory system126. Examples of frontend cache memory system126may include but are not limited to a volatile, solid-state, cache memory system (e.g., a dynamic RAM cache memory system) and/or a non-volatile, solid-state, cache memory system (e.g., a flash-based, cache memory system).

Storage processor124may initially store content118within frontend cache memory system124. Depending upon the manner in which frontend cache memory system126is configured, storage processor124may immediately write content118to data array112(if frontend cache memory system126is configured as a write-through cache) or may subsequently write content118to data array112(if frontend cache memory system126is configured as a write-back cache).

In some implementations, the instruction sets and subroutines of node fencing process10, which may be stored on storage device16included within storage system12, may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within storage system12. Accordingly, in addition to being executed on storage processor124, some or all of the instruction sets and subroutines of node fencing10may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within data array112.

Further and as discussed above, during the operation of data array112, content (e.g., content118) to be written to data array112may be received from storage processor124and initially stored within backend cache memory system124prior to being stored on e.g. one or more of storage targets102,104,106,108,111. Accordingly, during use of data array112, backend cache memory system124may be populated (e.g., warmed) and, therefore, subsequent read requests may be satisfied by backend cache memory system124(e.g., if the content requested in the read request is present within backend cache memory system124), thus avoiding the need to obtain the content from storage targets102,104,106,108,111(which would typically be slower).

As discussed above, storage processor100and storage processor124may be configured in an active/active configuration where processing of data by one storage processor may be synchronized to the other storage processor. For example, data may be synchronized between each storage processor via a separate link or connection (e.g., connection128).

The Data Replication Process:

Referring also to the examples ofFIGS.3-7and in some implementations, data replication process10may determine300a recovery point object (RPO) value for a storage object. An amount of data to transfer from the storage object to a disaster recovery site may be determined302. A data replication transfer schedule for the storage object may be generated304based upon, at least in part, the RPO value and the amount of data to transfer. Data may be asynchronously transferred306from the storage object to the disaster recovery site using the data replication transfer schedule.

As will be discussed in greater detail below, implementations of the present disclosure may allow for the scheduling or pacing of replication data transfer in a RPO window such that the impact to host latency is as minimal as possible. For example and as discussed above, data services like asynchronous replication preserve data but have an impact on host input/output (IO) request latency. Asynchronous replication depends on refreshing snapshots and the snapshot creation and deletion associated with snapshot refresh has an impact. Additionally, further latency impacts are due to the steps involved in data transfer of the changes to a disaster recovery (DR) site and this includes the calculation of differences between two snapshots used for asynchronous replication and the transfer of the differences or deltas. In this manner, data services such as asynchronous replication compete for resources with host applications and impact host latency. Users generally need these additional data services on top of the host applications and while users understand that host latency will be impacted, the impact should be as minimal as possible. Accordingly, implementations of the present disclosure provide a dynamically adjustable data replication transfer schedule based upon, at least in part, an RPO value and the amount of data to transfer from a particular storage object to a disaster recovery site.

Referring also toFIG.4and in some implementations, a storage system (e.g., storage system12) may be communicatively coupled (e.g., via a network) to a disaster recovery (DR) site (e.g., disaster recovery site400). Storage system12may be configured to asynchronously replicate data to disaster recovery site400. For example, disaster recovery site400may maintain a disaster recovery version or copy of the data of storage system12. In some implementations, storage system12may generate snapshots periodically and/or in response to receiving a threshold number of changes to particular storage objects. A storage object may generally include a volume, a file system, an object store bucket, a virtual volume (vVol), or any other container in memory for storing data. As disaster recovery site400may be geographically isolated or separated from storage system12such that data may recovered from disaster recovery site400during or after a disaster involving storage system12. However, the process of replicating data from storage system12may be limited by the processing constraints associated with storage system12, disaster recovery site400, and/or the networking resources between storage system12and disaster recovery site400. As discussed above, storage system12may balance resources between performing IO operations from a host device and asynchronously replicating data. As such, data replication process10may attempt to optimize the asynchronous replication of data by scheduling the data transfer to minimize latency issues for the host IO operations without compromising high availability of the data.

In some implementations, data replication process10determines300a recovery point object (RPO) value for a storage object. A recovery point object (RPO) generally includes the maximum amount of data that can be lost from a storage object on a disaster requiring recovery at a disaster recover (RD) site. Typically, the maximum amount of data is measured in units of time (e.g., seconds, minutes, hours, etc.). For example, suppose a user defines a RPO of e.g., 60 minutes for a particular storage object and there is a disaster on the production site (e.g., storage system12) and recovery happens at time “t0”. In this example, the user expects all data written after time (t0−60) minutes to be available on the disaster recovery site. In order to meet this RPO and using the example of RPO=60 minutes, asynchronous data replication is performed such that the replicated copy of the volume is created every 30 minutes and the other 30 minutes is used to transfer the data to the DR site.

In some implementations, the RPO value may be defined by a user (e.g., e.g., during creation of the storage object, during operation of the storage object, etc.), as a default value, and/or dynamically by data replication process10. For example, a user may use a user interface to define the RPO value for a storage object. As discussed above, the RPO value may be a maximum amount of data that can be lost during a disaster recovery event measured in terms of time. In some implementations, a user may reconfigure the RPO value at any point in the operation of the storage object. The RPO value for each storage object may be maintained by the storage node as metadata within the storage object, in a database associated with the storage object, and/or in a separate storage object. Accordingly, data replication process10may determine300the RPO value for the storage object by processing each storage object and reading the RPO value and/or processing a database of RPO values. In some implementations, data replication process10may determine300the RPO value for each storage object periodically and/or in response to receiving a threshold of new data (e.g., via IO write requests) on a particular storage object.

Referring also toFIG.5, suppose storage system12includes e.g., eight storage objects (e.g., storage objects500,502,504,506,508,510,512,514). In this example, each storage object may be replicated on disaster recovery site400by asynchronously replicating data from each storage object to disaster recovery site400. In some implementations, storage system12may replicate data from the plurality of storage objects (e.g., storage objects500,502,504,506,508,510,512,514) to a plurality of disaster recovery sites (e.g., disaster recovery site400). For this example, storage system12may replicate data from storage objects500,502,504,506,508,510,512,514to a single disaster recovery site (e.g., disaster recovery site400). However, it will be appreciated that data replication process10may replicate data to any number of disaster recovery sites within the scope of the present disclosure. Referring also to Table 1 below, data replication process10may determine300the RPO value for each storage object. For example and as shown in Row 3, data replication process10may determine300that storage object500has a RPO of e.g., five minutes; storage object502has a RPO of e.g., five minutes; storage object504has a RPO of e.g., 15 minutes; storage object506has a RPO of e.g., 30 minutes; storage object508has a RPO of e.g., 60 minutes; storage object510has a RPO of e.g., 360 minutes; storage object512has a RPO of e.g., 360 minutes; and storage object514has a RPO of e.g., 720 minutes.

In some implementations, data replication process10may determine a transfer time associated with the storage object based upon, at least in part, the RPO value for each storage object. For example, suppose that storage object500has an RPO value of e.g., five minutes. As discussed above, a five minute RPO value represents that maximum amount of data that can be lost during a disaster recovery event. Now suppose that the process of transferring the data from storage object500to disaster recovery site400requires a known or determinable amount of time. In this example, suppose that the amount of time required to transfer data from storage object500to disaster recovery site400is e.g., 50% of the RPO value. Accordingly, data replication process10may determine the transfer time for storage object500to be 2.5 minutes (e.g., 50% of five minutes). As shown in Row 5 of Table 1, data replication process10may determine the transfer time associated with each storage object based upon, at least in part, the RPO value for each storage object. In this example, data replication process10may determine a transfer time of 2.5 minutes for storage object500(e.g., 50% of five minutes); a transfer time of 2.5 minutes for storage object502(e.g., 50% of five minutes); a transfer time of 7.5 minutes for storage object504(e.g., 50% of 15 minutes); a transfer time of 15 minutes for storage object506(e.g., 50% of 30 minutes); a transfer time of 30 minutes for storage object508(e.g., 50% of 60 minutes); a transfer time of 180 minutes for storage object510(e.g., 50% of 360 minutes); a transfer time of 180 minutes for storage object512(e.g., 50% of 360 minutes); and a transfer time of 360 minutes for storage object514(e.g., 50% of 720 minutes).

In some implementations, data replication process10determines302an amount of data to transfer from the storage object to a disaster recovery site. For example, data replication process10may track IO operations for a plurality of storage objects in predefined intervals (e.g., a five second interval). Data replication process10uses this information to determine302or estimate the amount of data transfer for a RPO period (e.g., amount of time defined by RPO value). In some implementations, data replication process10may determine302the amount of data to transfer for each storage object periodically and/or in response to receiving a threshold of new data (e.g., via IO write requests) on a particular storage object. In some implementations, data replication process10may query a database to determine the total write IO requests for a storage object in the period of RPO start time to RPO end time. In this manner, data replication process10may determine302the total amount of data to be transferred for that storage object during the RPO period. As will be discussed in greater detail below, knowing the total transfer for a storage object allows the algorithm to calculate the transfer rate (e.g., transfer rate per second).

Referring again to Table 1, data replication process10may determine302an amount of data to transfer from each storage object (e.g., storage object500,502,504,506,508,510,512,514) to disaster recovery site (e.g., disaster recovery site400). For example, data replication process10may determine302that storage object500has e.g., 500 megabytes of data to transfer; storage object502has e.g., 1,000 megabytes of data to transfer; storage object504has e.g., 3,000 megabytes of data to transfer; storage object506has e.g., 3,000 megabytes of data to transfer; storage object508has e.g., 5,000 megabytes of data to transfer; storage object510has e.g., 10,000 megabytes of data to transfer; storage object512has e.g., 15,000 megabytes of data to transfer; and storage object514has e.g., 20,000 megabytes of data to transfer.

In some implementations, with the amount of data to transfer from the storage object to the disaster recovery site, data replication process10may access a past, average data transfer rate to each DR site. Accordingly, data replication process10may determine how long it will take to transfer the cumulative data transfers for all storage objects to a specific DR site. In one example, suppose data replication process10determines that the average network throughput between storage system12and disaster recover site400is 500 megabytes per second or 30,000 megabytes per minute. However, it will be appreciated that the average network throughput may be any value within the scope of the present disclosure.

In some implementations, data replication process10determines308a priority of each storage object. For example, a priority for each storage object may indicate the relative prioritization of a storage object relative to a plurality of storage objects when asynchronously transferring data to the disaster recovery site. In some implementations, the priority of each storage object may be defined by a user and/or by data replication process10using one or more rulesets indicating priority for each storage object based upon, at least in part, various properties or characteristics of the storage object. For example, data replication process10may prioritize particular storage objects based upon, at least in part, the amount of data transfer for a particular storage object for a RPO, the RPO duration, any past RPO misses (i.e., situations where the RPO value was not met by asynchronous data replication), use of multiple DR sites, etc. In some implementations and as will be discussed in greater detail below, data replication process10may represent the priority of each storage object as a multiplier value as shown in Table 1. For example, suppose that data replication process10determines that the RPO value for storage objects500and502is less than some threshold (e.g., less than five minutes) as shown in Row 3. In this example, data replication process10may prioritize storage objects500and502as shown in Row 8 with a two times multiplier value. Further, suppose that data replication process10determines that certain storage objects have missed their RPO value as shown in Row 4. Accordingly, data replication process10may assign or determine various priorities to storage objects500,502,504,506. In some implementations, data replication process10may apply a multiplier value of less than one to de-prioritize a storage object relative to other storage objects.

In some implementations, data replication process10determines310an asynchronous data transfer capacity for the storage object. An asynchronous data transfer capacity is the amount of transfer capacity allocated by the storage system for asynchronous data transfer. For example, a storage system may include a data path regulator configured to issue a number of tokens for allocating control or access to a data path (e.g., data path into and out of the storage system). In one example, the data path regulator may issue a number of tokens for the processing of each IO operation. These tokens may be returned or de-allocated when the IO operation processing is complete. In another example, tokens may be allocated for asynchronous data replication from a particular storage object to a disaster recovery site. These tokens may similarly be returned or de-allocated when the data replication is complete. In some implementations, data replication process10may determine310the asynchronous data transfer capacity for the storage object by querying (e.g., using an application programmable interface (API)) the data path regulator for a number of available tokens. With the available number of tokens, data replication process10may determine the asynchronous data transfer capacity. In some implementations, the asynchronous data transfer capacity may be representative of the total available asynchronous data transfer capacity for each storage object. In one example, data replication process10provides a query to the data path regulator and determines that the data path regulator will allow e.g., 100 megabytes per second or 6,000 megabytes per minute. As will be discussed in greater detail below, the asynchronous data transfer capacity may be defined for any number of storage objects (e.g., one storage object, a set of storage objects, all storage objects, etc.).

In some implementations, data replication process10generates304a data replication transfer schedule for the storage object based upon, at least in part, the RPO value and the amount of data to transfer. A data replication transfer schedule is a listing of how much data to asynchronously transfer per unit of time (e.g., per minute) for each storage object based upon, at least in part, the storage object's RPO. With each unit of time, the transfer rate may be adjusted by data replication process10to ensure that the complete transfer period allowed per the RPO value. Referring again to Row 7 of Table 1, data replication process10may determine the transfer rate based upon, at least in part, an amount of data to be transferred for a RPO window and the current rate of transfer. As shown in Row 7, data replication process10may determine the transfer rate for storage object500to be 200 megabytes per minute (e.g., 500 megabytes divided by 2.5 minutes for transfer); the transfer rate for storage object502to be 400 megabytes per minute (e.g., 1,000 megabytes divided by 2.5 minutes for transfer); the transfer rate for storage object504to be 400 megabytes per minute (e.g., 3,000 megabytes divided by 7.5 minutes for transfer); the transfer rate for storage object506to be 200 megabytes per minute (e.g., 3,000 megabytes divided by 15 minutes for transfer); the transfer rate for storage object508to be 167 megabytes per minute (e.g., 5,000 megabytes divided by 30 minutes for transfer); the transfer rate for storage object510to be 56 megabytes per minute (e.g., 10,000 megabytes divided by 180 minutes for transfer); the transfer rate for storage object512to be 84 megabytes per minute (e.g., 15,000 megabytes divided by 180 minutes for transfer); and the transfer rate for storage object514to be 56 megabytes per minute (e.g., 20,000 megabytes divided by 360 minutes for transfer).

In some implementations, data replication process10generates304the data replication transfer schedule for the storage object based upon, at least in part, the priority of each storage object. For example, data replication process10may include prioritization in the data replication transfer schedule by multiplying the transfer rate determined for each storage object by a priority-based multiplicative value. As shown in Row 8, storage objects500,502,504,506may include a multiplicative value greater than “1” indicating a priority relative to storage objects508,510,512,514. In this manner, the data replication transfer schedule may allocate more of the asynchronous data transfer capacity to the higher priority storage objects. Referring to Rows 9-11 of Table 1, data replication process10may determine the transfer rate based upon, at least in part, an amount of data to be transferred for a RPO window and the current rate of transfer. As shown in Row 9, data replication process10may determine an amount of data (e.g., data516) to transfer for storage object500in a first time interval (e.g., 400 megabytes starting at time t0, where 200 megabytes per minute multiplied by multiplicative factor of “2” equals 400 megabytes for minute to to t0+1); an amount of data (e.g., data518) to transfer for storage object502in a first time interval (e.g., 800 megabytes starting at time t0, where 400 megabytes per minute multiplied by multiplicative factor of “2” equals 800 megabytes for minute t0to t0+1); an amount of data (e.g., data520) to transfer for storage object504in a first time interval (e.g., 600 megabytes starting at time t0, where 400 megabytes per minute multiplied by multiplicative factor of “1.5” equals 600 megabytes for minute t0to t0+1); an amount of data (e.g., data522) to transfer for storage object506in a first time interval (e.g., 300 megabytes starting at time t0, where 200 megabytes per minute multiplied by multiplicative factor of “1.5” equals 300 megabytes for minute t0to t0+1); and an amount of data (e.g., data524) to transfer for storage object508in a first time interval (e.g., 200 megabytes starting at time t0).

As shown in Row 9, the remaining, non-prioritized storage objects may be reduced or delayed during the first time interval given the increased RPO values. For example, as shown in Table 1, storage objects508,510,512,514may have a reduced transfer rate during the first time interval because of the significantly longer RPO value than the RPO values of storage objects500,502,504,506.

Data replication process10may generate304the data replication transfer schedule for the storage object with a plurality of time intervals to account for all of the replication data to be transferred to the disaster recovery site. As shown in Rows 10-11 of Table 1, additional time intervals may be included in the data replication transfer schedule.

In some implementations, data replication process10generates304the data replication transfer schedule for the storage object based upon, at least in part, the asynchronous data transfer capacity for the storage object. For example, without the self-pacing data replication process10describes, the replication transfer engine would attempt to transfer 6,000 megabytes per minute if the data path regulator provided the needed tokens. However, with self-pacing imposed by data replication process10, the amount of replication transfer data is reduced and spread over a period to provide better performance tradeoff with the host IO operation processing. In some implementations, data replication process10may generate304the data replication transfer schedule to balance the storage object transfer needs among all the non-prioritized storage objects while keeping the requests below the asynchronous data transfer capacity (i.e., the limit allowed by the data path regulator) without violating any of the RPO commitments for the storage objects. As shown in the last column of Table 1, for each time interval (e.g., Rows 9-11), data replication process10may keep the total transfer amount less than the asynchronous data replication transfer capacity (e.g., 6,000 megabytes per minute) by adjusting the amount of data transferred per storage object per time interval.

In some implementations, data replication process10asynchronously transfers306data from the storage object to the disaster recovery site using the data replication transfer schedule. For example, and as shown inFIG.5, data replication process10may asynchronously transfer306data (e.g., data500,502,504,506,508) from the storage object (e.g., storage objects500,502,504,506,508) to the disaster recovery site (e.g., disaster recovery site400) using the data replication transfer schedule (e.g., data replication transfer schedule526). As shown in Row 9 of Table 1, at time interval t0−t0+1, data replication process10may asynchronously transfer306data (e.g., data500,502,504,506,508) from the storage object (e.g., storage objects500,502,504,506,508) to the disaster recovery site (e.g., disaster recovery site400). As shown inFIG.6and Row 10 of Table 1, at time interval t0+1−t0+2, data replication process10may asynchronously transfer306data (e.g., data600,602,604,606,608,610,612,614) from the storage object (e.g., storage objects500,502,504,506,508,510,512,514) to the disaster recovery site (e.g., disaster recovery site400). Finally, as shown inFIG.7and Row 11 of Table 1, at time interval t0+2−t0+3, data replication process10may asynchronously transfer306data (e.g., data700,702,704,706,708,710) from the storage object (e.g., storage objects506,508,510,512,514) to the disaster recovery site (e.g., disaster recovery site400). WhileFIGS.5-7include three time intervals, it will be appreciated that data replication process10may asynchronously transfer306data from the storage object to the disaster recovery site using the data replication transfer schedule including any number of time intervals within the scope of the present disclosure.

In some implementations, data replication process10periodically re-determines312the RPO value and the amount of data to transfer from the storage object. For example, data replication process10may determine312the RPO value and the amount of data to transfer from the storage object periodically (e.g., every “N” seconds). Accordingly, data replication process10may re-determine312the RPO value and the amount of data to transfer from the storage object after an additional N seconds. In some implementations, the periodicity between determination of the RPO value and the amount of data to transfer may be user-defined (e.g., using a user interface), may be a default value (e.g., every five seconds), or defined dynamically by data replication process10. In some implementations, the periodicity between determinations of the RPO value and the amount of data to transfer may be determined based upon, at least in part, a threshold amount of data processed by storage system12. For example, data replication process10may determine that a storage object has received at least a threshold amount of new data that needs to be replicated. Accordingly, data replication process10may re-determine312the RPO value and the amount of data to transfer.

In some implementations, data replication process10adjusts314the data replication transfer schedule based upon, at least in part, a change in one or more of the RPO value and the amount of data to transfer from the storage object. For example, data replication process10may determine that the RPO value and/or the amount of data to transfer has changed. In one example, data replication process10may adjust the data replication transfer schedule in response to determining that at least a threshold amount of data has changed. In another example, data replication process10may adjust314the data replication transfer schedule in response to any changes or the lack thereof in the RPO value and/or amount of data to transfer.