Storage management system and method

A method, computer program product, and computing system for receiving one or more IO requests on a storage system coupled to a cloud-based storage platform, wherein the cloud-based storage platform has a defined maximum IOPS rate; determining a current level of utilization of the defined maximum IOPS rate; and determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform based, at least in part, upon the current level of utilization of the defined maximum IOPS rate.

TECHNICAL FIELD

This disclosure relates to storage management processes and, more particularly, to storage management processes for use in high-availability storage systems.

BACKGROUND

Storing and safeguarding electronic content is of paramount importance in modern business. Accordingly, various methodologies may be employed to protect and distribute such electronic content, wherein the storage systems that process such content may strive to do so in as an efficient manner as possible.

As storage is being migrated from onprem (i.e., on premises) to the cloud, technical hurdles often complicate things. For example, IOPS (input-output-operations-per-second) bottlenecks may be encountered that result in a level of latency that is undesirable when compared to onprem storage.

SUMMARY OF DISCLOSURE

In one implementation, a computer-implemented method is executed on a computing system and includes: receiving one or more IO requests on a storage system coupled to a cloud-based storage platform, wherein the cloud-based storage platform has a defined maximum IOPS rate; determining a current level of utilization of the defined maximum IOPS rate; and determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform based, at least in part, upon the current level of utilization of the defined maximum IOPS rate.

One or more of the following features may be included. Determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform may include: excluding from queuing consideration any read IO requests included within the one or more IO requests received. Determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform may further include: immediately processing the read IO requests included within the one or more IO requests received. A likelihood of queuing the one or more IO requests for the aggregated write operation to the cloud-based storage platform may generally increase as the utilization of the defined maximum IOPS rate is approached. The defined maximum IOPS rate may define a maximum number of IOPS per unit time. The current level of utilization of the defined maximum IOPS rate may identify the total IO requests and the breakdown between read IO requests and write IO requests. The storage system may be a log-based storage system.

In another implementation, a computer program product resides on a computer readable medium and has a plurality of instructions stored on it. When executed by a processor, the instructions cause the processor to perform operations including receiving one or more IO requests on a storage system coupled to a cloud-based storage platform, wherein the cloud-based storage platform has a defined maximum IOPS rate; determining a current level of utilization of the defined maximum IOPS rate; and determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform based, at least in part, upon the current level of utilization of the defined maximum IOPS rate.

One or more of the following features may be included. Determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform may include: excluding from queuing consideration any read IO requests included within the one or more IO requests received. Determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform may further include: immediately processing the read IO requests included within the one or more IO requests received. A likelihood of queuing the one or more IO requests for the aggregated write operation to the cloud-based storage platform may generally increase as the utilization of the defined maximum IOPS rate is approached. The defined maximum IOPS rate may define a maximum number of IOPS per unit time. The current level of utilization of the defined maximum IOPS rate may identify the total IO requests and the breakdown between read IO requests and write IO requests. The storage system may be a log-based storage system.

In another implementation, a computing system includes a processor and memory is configured to perform operations including receiving one or more IO requests on a storage system coupled to a cloud-based storage platform, wherein the cloud-based storage platform has a defined maximum IOPS rate; determining a current level of utilization of the defined maximum IOPS rate; and determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform based, at least in part, upon the current level of utilization of the defined maximum IOPS rate.

One or more of the following features may be included. Determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform may include: excluding from queuing consideration any read IO requests included within the one or more IO requests received. Determining whether to queue the one or more IO requests for an aggregated write operation to the cloud-based storage platform may further include: immediately processing the read IO requests included within the one or more IO requests received. A likelihood of queuing the one or more IO requests for the aggregated write operation to the cloud-based storage platform may generally increase as the utilization of the defined maximum IOPS rate is approached. The defined maximum IOPS rate may define a maximum number of IOPS per unit time. The current level of utilization of the defined maximum IOPS rate may identify the total IO requests and the breakdown between read IO requests and write IO requests. The storage system may be a log-based storage system.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

System Overview

Referring toFIG.1, there is shown storage management 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 personal computer with a memory system, a server computer with a memory system, a Network Attached Storage (NAS) system, a Storage Area Network (SAN) 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 Server™; Redhat Linux™, Unix, or a custom operating system, for example.

The instruction sets and subroutines of storage management process10, which may be stored on storage device16coupled to 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; an optical drive; a RAID device; a random-access memory (RAM); a read-only memory (ROM); and all forms of flash memory storage devices.

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 (i.e. a request that content be written to storage system12) and data read requests (i.e. 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; 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™, Apple Macintosh™, Redhat Linux™, or a custom operating system.

The Data Storage System:

Referring also toFIG.2, there is shown a general implementation of storage system12. In this general implementation, storage system12may include processing node100, wherein processing node100may be configured to perform computational tasks and to store data within storage platform102.

Depending upon the manner in which storage system12is configured, storage platform102may include a single storage device (such as a single hard disk drive or a single solid state storage device) or may include a plurality of storage devices that are configured to provide various levels of performance and/or high availability. For example and if storage platform102includes a plurality of storage devices (e.g., hard disk drives and/or solid state storage devices), this plurality of storage devices may be configured to form a RAID storage array utilizing various standard RAID structures (e.g., RAID 0, RAID 1, RAID 3, RAID 5, RAID 6, RAID 7 or RAID 10), thus providing a higher level of performance and/or availability. Further, storage platform102may be a cloud-based storage platform that provides virtualized storage functionality to (in this example) users46,48,50,52.

As is known in the art, cloud storage is a model of computer data storage in which the digital data is stored in logical pools, said to be on “the cloud”. The physical storage spans multiple servers (sometimes in multiple locations) and the physical environment is typically owned and managed by a hosting company. These cloud storage providers are responsible for keeping the data available and accessible, and the physical environment secured, protected, and running. People and organizations buy or lease storage capacity from the providers to store user, organization, or application data. Cloud storage services may be accessed through a collocated cloud computing service, a web service application programming interface (API) or by applications that use the API, such as cloud desktop storage, a cloud storage gateway or Web-based content management systems.

Storage system12may be configured to execute all or a portion of storage management process10. The instruction sets and subroutines of storage management process10, which may be stored on a storage device (e.g., storage device16) coupled to e.g., processing node100, may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within processing node100. Storage device16may include but is not limited to: a hard disk 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, 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 system12is configured as an application server, these IO requests may be internally generated within storage system12. Examples of IO request20may include but are not limited to data write request104(i.e., a request that content106be written to storage system12) and data read request108(i.e., a request that content106be read from storage system12).

During operation of processing node100, content106to be written to storage system12may be processed by processing node100. Additionally/alternatively and when storage system12is configured as an application server, content106to be written to storage system12may be internally generated by processing node100.

Processing node100may include cache memory system110. Examples of cache memory system110may include but are not limited to a volatile, solid-state, cache memory system (e.g., a static RAM cache memory system) and/or a non-volatile, solid-state, cache memory system (e.g., a flash-based, cache memory system). Processing node100may initially store content106within cache memory system110. Depending upon the manner in which cache memory system110is configured, processing node100may immediately write content106to storage platform102(if cache memory system110is configured as a write-through cache) or may subsequently write content106to storage platform102(if cache memory system110is configured as a write-back cache).

Storage system12may be configured to include a plurality of processing nodes, each of which may be configured to receive, generate and/or process content (e.g., content106). For example and in addition to processing node100, storage system12may include one or more additional processing nodes (e.g., processing node112).

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 (e.g., computing cluster114) may be formed from at least two nodes (e.g., processing nodes100,112), both actively running the same kind of service(s) simultaneously. One purpose of an active-active cluster (e.g., computing cluster114) 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 (e.g., computing cluster114) may be to provide at least one active node in the event that one of the nodes in the active-active cluster fails.

Storage system12may be configured as a log-based storage system. If so configured, storage management process10may store received data in a log memory system (e.g., log memory system116). As is known in the art, a log memory system (e.g., log memory system116) may generally include one or more non-volatile random-access memory (NVRAM) devices configured to store a log of the data written to storage system12. Additionally/alternatively, the log of the data written to storage system12may be stored on a remote storage device (e.g., solid state storage on a backend device of the cloud storage provider).

As discussed above, an example of IO request20may include but is not limited to data write request104(i.e., a request that content106be written to storage system12). Further and as discussed above, upon receiving data write request104and content106, data write request104and content106may be written to cache memory system110(which may be volatile). However and when configured as a log-based storage system, upon receiving data write request104and content106, data write request104and/or content106may also be written to log memory system116(which is persistent).

Therefore and through the use of log memory system116, the content of cache memory system110(e.g., data write request104and content106) may be recovered (via log memory system116) in the event of a power failure and/or a failure of cache memory system110. Further and due to such failure recoverability, data (e.g., content106) may be considered to be persistently stored (i.e., as if stored in storage platform102) once such data (e.g., content106) is saved within log memory system116. Therefore, once such data (e.g., content106) is saved within log memory system116, a write acknowledgement may be provided to the sender of data write request104, acknowledging the successful saving of such data (e.g., content106), wherein such data (e.g., content106) may be subsequently written to storage platform102.

Log memory system116may include a page buffer pool (e.g., page buffer pool118) and/or a page descriptor ring buffer (e.g., page descriptor ring buffer120) to effectuate the above-described temporary storage of (in this example) content106. For example, storage management process10may store one or more pages (associated with content106) in one or more page buffers within page buffer pool118based, at least in part, upon the processing of (in this example) write request104. Further, storage management process10may store information concerning the data (e.g., content106) stored within log memory system116in a page descriptor (e.g., page descriptor122), wherein page descriptor122may generally include a reference (i.e., a pointer) to the related page buffer(s) within page buffer pool118. Page descriptor122may also include a sequence transaction number that tracks the order of write operations and/or other types of information.

Storage management process10may store each page descriptor (e.g., page descriptor122) in a page descriptor ring buffer (e.g., page descriptor ring buffer120). As is known in the art, a page descriptor ring buffer may allow data to be added to the “head” of the page descriptor ring buffer and released or overwritten from the tail of the page descriptor ring buffer. Accordingly, page descriptor ring buffer120may appear to be circular in that older data is overwritten with newer data as data (e.g., content106) is moved from page buffer pool118to storage platform102.

Storage Management Process:

As discussed above, 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., write request104which is a request that content106be written to storage system12) and data read requests (e.g., read request108, which is a request that content106be read from storage system12).

Accordingly and referring also toFIG.3, storage management process10may receive200one or more IO requests (e.g., write request104and/or read request108) on a storage system (e.g., storage system12) coupled to a cloud-based storage platform (e.g., storage platform102). As discussed above, cloud storage is a model of computer data storage in which the digital data is stored in logical pools, wherein the physical storage spans multiple servers (sometimes in multiple locations) and the physical environment is typically owned and managed by a hosting company.

For this particular example, assume that the cloud-based storage platform (e.g., storage platform102) has a defined maximum IOPS rate, wherein this defined maximum IOPS rate may define a maximum number of IO operations per unit time. Typically, when utilizing a cloud-based storage platform (e.g., storage platform102), access is granted to the user based upon such a defined maximum IOPS rate. Examples of such a defined maximum IOPS rate may include 1,000 IO operations per second, 2,000 IO operations per second, 3,000 IO operations per second, 5,000 IO operations per second, and 10,000 IO operations per second. The above examples of the defined maximum IOPS rate are for illustrative purposes only and are 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. For example, these numbers may be increased or decreased depending upon need/design criteria/technical capabilities. Naturally, as the quantity of IO operations per unit time increases, the fee for such access also increases. Accordingly, it is in the interest of the user to only purchase the quantity of IO operations per unit time they need. However, in the event that such quantity is reached, access is typically paused (e.g., throttled) until the unit time is reset. Therefore, assume for this discussion that the plan selected if for 2,000 IO operations per second. Further assume that during the first/4 of a second (i.e., 250 milliseconds), you use those 2,000 IO operations. Accordingly, you are going to be paused (e.g., throttled) for the next % of a second (e.g., 750 milliseconds) until the unit time period resets.

As will be discussed below in greater detail, in order to avoid the undesirable situation of getting paused (e.g., throttled), storage management process10may be configured to aggregate write operations to reduce the consumption of such IO operations. For example, cloud-based storage platform service providers often quantify an IO operation as the reading or writing of a defined quantity of data. A common value for this defined quantity is 256 kilobytes of data. However, this value is for illustrative 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. For example, this defined quantity may be increased or decreased depending upon the limitation/capabilities of the cloud-based storage platform (e.g., storage platform102).

Accordingly, if you write 256 k of content to cloud-based storage platform (e.g., storage platform102), that is one IO operation (e.g., of the 2,000 IO operations per second you are allowed). However, if you write only 4 k of content to the cloud-based storage platform (e.g., storage platform102), that is also one IO operation (e.g., of the 2,000 IO operations per second you are allowed). Therefore, it may be beneficial to aggregate write operations to reduce the consumption of such IO operations. For example, sixty-four 4 k write operation may be aggregated to form one 256 k write operation, and the writing of this 256 k of aggregated data would only consume one IO operation (as opposed to sixty-four).

Unfortunately, aggregation introduces latency into storage system12. However, if storage system12is a log-based storage system, the impact of such latency may be reduced, since (as discussed above) acknowledgement of the writing of data (e.g., content106) associated with a write request (e.g., write request104) may be made upon the related content being written to (in this example) log memory system116. Accordingly, content may be aggregated in such a log memory system (e.g., log memory system116) until such an aggregated write operation is performed.

Accordingly and once such IO requests (e.g., write request104and/or read request108) are received200on storage system12coupled to the cloud-based storage platform (e.g., storage platform102), storage management process10may determine202a current level of utilization of the defined maximum IOPS rate. As discussed above, assume that the defined maximum IOPS rate is 2,000 IO operations per second. The current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second) may identify the total IO requests and the breakdown between read IO requests (e.g., read request108) and write IO requests (e.g., write request104).

Once this current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second) is determined202, storage management process10may determine204whether to queue the one or more IO requests (e.g., write request104and/or read request108) for an aggregated write operation to the cloud-based storage platform (e.g., storage platform102) based, at least in part, upon the current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second).

As will be illustrated bellow, the likelihood of queuing the one or more IO requests (e.g., write request104and/or read request108) for the aggregated write operation to the cloud-based storage platform (e.g., storage platform102) may generally increase as the utilization of the defined maximum IOPS rate is approached.

Below explains one manner in which the determination204may be made concerning whether to queue the one or more IO requests (e.g., write request104and/or read request108) for an aggregated write operation to the cloud-based storage platform (e.g., storage platform102) based, at least in part, upon the current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second).If the defined maximum IOPS rate is 25% utilized or less, IO requests (e.g., write request104and/or read request108) received200on storage system12may not aggregated and are immediately processed.If the defined maximum IOPS rate is above 25% utilized and write IO operations constitute at least 20% of total OP operations; IO requests (e.g., write request104and/or read request108) received200on storage system12may be aggregated for a maximum duration of 200 μs and/or until a maximum aggregation size of 32 k before such an aggregated write operation is performed on the cloud-based storage platform (e.g., storage platform102).If the defined maximum IOPS rate is above 50% utilized and write IO operations constitute at least 25% of total OP operations; IO requests (e.g., write request104and/or read request108) received200on storage system12may be aggregated for a maximum duration of 500 μs and/or until a maximum aggregation size of 64 k before such an aggregated write operation is performed on the cloud-based storage platform (e.g., storage platform102).If the defined maximum IOPS rate is above 75% utilized and write IO operations constitute at least 30% of total OP operations; IO requests (e.g., write request104and/or read request108) received200on storage system12may be aggregated for a maximum duration of 800 μs and/or until a maximum aggregation size of 128 k before such an aggregated write operation is performed on the cloud-based storage platform (e.g., storage platform102).If the defined maximum IOPS rate is above 90% utilized and write IO operations constitute at least 40% of total OP operations; IO requests (e.g., write request104and/or read request108) received200on storage system12may be aggregated for a maximum duration of 1000 μs and/or until a maximum aggregation size of 256 k before such an aggregated write operation is performed on the cloud-based storage platform (e.g., storage platform102).

While the above-stated example illustrates five rules, this is for illustrative 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. For example, this rule set may be increased/decreased/modified based upon specific performance criteria/design choices.

Applying the above-described five rules:If it is determined202that the current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second) is 400 IO requests having been received during the current time interval (i.e., 20% of 2,000 IO operations per second) and 20% of these 400 IO requests are write IO requests (e.g., write request104); storage management process10may not aggregate and may process all IO requests immediately.If it is determined202that the current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second) is 600 IO requests having been received during the current time interval (i.e., 30% of 2,000 IO operations per second) and 22% of these 600 IO requests are write IO requests (e.g., write request104); storage management process10may aggregate for a maximum duration of 200 μs and/or until a maximum aggregation size of 32 k before such an aggregated write operation is performed on the cloud-based storage platform (e.g., storage platform102).If it is determined202that the current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second) is 1.100 IO requests having been received during the current time interval (i.e., 55% of 2,000 IO operations per second) and 27% of these 1,100 IO requests are write IO requests (e.g., write request104); storage management process10may aggregate for a maximum duration of 500 μs and/or until a maximum aggregation size of 64 k before such an aggregated write operation is performed on the cloud-based storage platform (e.g., storage platform102).If it is determined202that the current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second) is 1.600 IO requests having been received during the current time interval (i.e., 80% of 2,000 IO operations per second) and 33% of these 1,600 IO requests are write IO requests (e.g., write request104); storage management process10may aggregate for a maximum duration of 800 μs and/or until a maximum aggregation size of 128 k before such an aggregated write operation is performed on the cloud-based storage platform (e.g., storage platform102).If it is determined202that the current level of utilization of the defined maximum IOPS rate (e.g., 2,000 IO operations per second) is 1,900 IO requests having been received during the current time interval (i.e., 95% of 2,000 IO operations per second) and 45% of these 1,900 IO requests are write IO requests (e.g., write request104); storage management process10may aggregate for a maximum duration of 1000 μs and/or until a maximum aggregation size of 256 k before such an aggregated write operation is performed on the cloud-based storage platform (e.g., storage platform102). In this illustrative example, the maximum aggregation size is set to the maximum defined quantity of data for a single IO operation within the cloud-based storage platform (e.g., storage platform102).

When determine204whether to queue the one or more IO requests (e.g., write request104and/or read request108) for an aggregated write operation to the cloud-based storage platform (e.g., storage platform102), storage management process10may exclude206from queuing consideration any read IO requests (e.g., read request108) included within the one or more IO requests (e.g., write request104and/or read request108) received.

As stated above, aggregation introduces latency into storage system12. But if storage system12is a log-based storage system, the impact of such latency may be reduced, since (as discussed above) acknowledgement of the writing of data (e.g., content106) associated with a write request (e.g., write request104) may be made upon the related content being written to (in this example) log memory system116. Unfortunately, such a log memory system (e.g., log memory system116) does not mitigate latency with respect to read IO requests (e.g., read request108). Accordingly, storage management process10may exclude206from queuing consideration any read IO requests (e.g., read request108) included within the one or more IO requests (e.g., write request104and/or read request108) received.

Accordingly and when determining204whether to queue the one or more IO requests (e.g., write request104and/or read request108) for an aggregated write operation to the cloud-based storage platform (e.g., storage platform102), storage management process10may immediately process208the read IO requests (e.g., read request108) included within the one or more IO requests (e.g., write request104and/or read request108) received.

General