Patent ID: 12242425

DETAILED DESCRIPTION

In a storage system it is desirable to deduplicate data to increase storage efficiency. One way to perform deduplication is to hash a sector (or multiple sectors) and then perform a lookup into a large collection of hashes to see if an exact match to deduplicate to can be located. This approach may have scaling problem in various embodiments. For example, in one embodiment the hashes may be stored in a database that can become relatively large. In another example, finding the hash in such a large database grows at least with O(log n). Furthermore, the larger the database, the larger the potential likelihood of running into a collision.

To resolve the above deficiencies, in one implementation, a controller associated with multiple storage devices identifies a first data object stored on the storage devices, determines a first content type of the first data object, and determines a first centroid corresponding to the first data object. In one embodiment the first centroid is of the first content type. The controller may further identify a first content-dependent feature of the first data object and a corresponding second content-dependent feature of the first centroid, determine a difference between the first feature and the second feature, and deduplicate the first data object in view of the difference being less than or equal to a delta threshold.

Generally, a data sector (fixed or variable) may be deduplicated by extracting a feature of the sector (e.g., a content-based feature), deduplicating the feature and storing the delta to the feature. A successful deduplication may have a reference to a deduplicated feature sector, as well as a delta to that sector. Reading the original sector may be performed by reading the feature sector and applying the delta. Advantageously, in some embodiments a relatively small amount of data may be stored to deduplicate data sectors with large changes to underlying data, but relatively small changes to content-based features.

Example methods, apparatus, and products for workload planning and quality-of-service (‘QoS’) integration in accordance with embodiments of the present disclosure are described with reference to the accompanying drawings, beginning withFIG.1A.FIG.1Aillustrates an example system for data storage, in accordance with some implementations. System100(also referred to as “storage system” herein) includes numerous elements for purposes of illustration rather than limitation. It may be noted that system100may include the same, more, or fewer elements configured in the same or different manner in other implementations.

System100includes a number of computing devices164A-B. Computing devices (also referred to as “client devices” herein) may be embodied, for example, a server in a data center, a workstation, a personal computer, a notebook, or the like. Computing devices164A-B may be coupled for data communications to one or more storage arrays102A-B through a storage area network (‘SAN’)158or a local area network (‘LAN’)160.

The SAN158may be implemented with a variety of data communications fabrics, devices, and protocols. For example, the fabrics for SAN158may include Fibre Channel, Ethernet, Infiniband, Serial Attached Small Computer System Interface (‘SAS’), or the like. Data communications protocols for use with SAN158may include Advanced Technology Attachment (‘ATA’), Fibre Channel Protocol, Small Computer System Interface (‘SCSI’), Internet Small Computer System Interface (‘iSCSI’), HyperSCSI, Non-Volatile Memory Express (‘NVMe’) over Fabrics, or the like. It may be noted that SAN158is provided for illustration, rather than limitation. Other data communication couplings may be implemented between computing devices164A-B and storage arrays102A-B.

The LAN160may also be implemented with a variety of fabrics, devices, and protocols. For example, the fabrics for LAN160may include Ethernet (802.3), wireless (802.11), or the like. Data communication protocols for use in LAN160may include Transmission Control Protocol (‘TCP’), User Datagram Protocol (‘UDP’), Internet Protocol (‘IP’), HyperText Transfer Protocol (‘HTTP’), Wireless Access Protocol (‘WAP’), Handheld Device Transport Protocol (‘HDTP’), Session Initiation Protocol (‘SIP’), Real Time Protocol (‘RTP’), or the like.

Storage arrays102A-B may provide persistent data storage for the computing devices164A-B. Storage array102A may be contained in a chassis (not shown), and storage array102B may be contained in another chassis (not shown), in implementations. Storage array102A and102B may include one or more storage array controllers110(also referred to as “controller” herein). A storage array controller110may be embodied as a module of automated computing machinery comprising computer hardware, computer software, or a combination of computer hardware and software. In some implementations, the storage array controllers110may be configured to carry out various storage tasks. Storage tasks may include writing data received from the computing devices164A-B to storage array102A-B, erasing data from storage array102A-B, retrieving data from storage array102A-B and providing data to computing devices164A-B, monitoring and reporting of disk utilization and performance, performing redundancy operations, such as Redundant Array of Independent Drives (‘RAID’) or RAID-like data redundancy operations, compressing data, encrypting data, and so forth.

Storage array controller110may be implemented in a variety of ways, including as a Field Programmable Gate Array (‘FPGA’), a Programmable Logic Chip (‘PLC’), an Application Specific Integrated Circuit (‘ASIC’), System-on-Chip (‘SOC’), or any computing device that includes discrete components such as a processing device, central processing unit, computer memory, or various adapters. Storage array controller110may include, for example, a data communications adapter configured to support communications via the SAN158or LAN160. In some implementations, storage array controller110may be independently coupled to the LAN160. In implementations, storage array controller110may include an I/O controller or the like that couples the storage array controller110for data communications, through a midplane (not shown), to a persistent storage resource170A-B (also referred to as a “storage resource” herein). The persistent storage resource170A-B main include any number of storage drives171A-F (also referred to as “storage devices” herein) and any number of non-volatile Random Access Memory (‘NVRAM’) devices (not shown).

In some implementations, the NVRAM devices of a persistent storage resource170A-B may be configured to receive, from the storage array controller110, data to be stored in the storage drives171A-F. In some examples, the data may originate from computing devices164A-B. In some examples, writing data to the NVRAM device may be carried out more quickly than directly writing data to the storage drive171A-F. In implementations, the storage array controller110may be configured to utilize the NVRAM devices as a quickly accessible buffer for data destined to be written to the storage drives171A-F. Latency for write requests using NVRAM devices as a buffer may be improved relative to a system in which a storage array controller110writes data directly to the storage drives171A-F. In some implementations, the NVRAM devices may be implemented with computer memory in the form of high bandwidth, low latency RAM. The NVRAM device is referred to as “non-volatile” because the NVRAM device may receive or include a unique power source that maintains the state of the RAM after main power loss to the NVRAM device. Such a power source may be a battery, one or more capacitors, or the like. In response to a power loss, the NVRAM device may be configured to write the contents of the RAM to a persistent storage, such as the storage drives171A-F.

In implementations, storage drive171A-F may refer to any device configured to record data persistently, where “persistently” or “persistent” refers as to a device's ability to maintain recorded data after loss of power. In some implementations, storage drive171A-F may correspond to non-disk storage media. For example, the storage drive171A-F may be one or more solid-state drives (‘SSDs’), flash memory based storage, any type of solid-state non-volatile memory, or any other type of non-mechanical storage device. In other implementations, storage drive171A-F may include may include mechanical or spinning hard disk, such as hard-disk drives (‘HDD’).

In some implementations, the storage array controllers110may be configured for offloading device management responsibilities from storage drive171A-F in storage array102A-B. For example, storage array controllers110may manage control information that may describe the state of one or more memory blocks in the storage drives171A-F. The control information may indicate, for example, that a particular memory block has failed and should no longer be written to, that a particular memory block contains boot code for a storage array controller110, the number of program-erase (‘P/E’) cycles that have been performed on a particular memory block, the age of data stored in a particular memory block, the type of data that is stored in a particular memory block, and so forth. In some implementations, the control information may be stored with an associated memory block as metadata. In other implementations, the control information for the storage drives171A-F may be stored in one or more particular memory blocks of the storage drives171A-F that are selected by the storage array controller110. The selected memory blocks may be tagged with an identifier indicating that the selected memory block contains control information. The identifier may be utilized by the storage array controllers110in conjunction with storage drives171A-F to quickly identify the memory blocks that contain control information. For example, the storage controllers110may issue a command to locate memory blocks that contain control information. It may be noted that control information may be so large that parts of the control information may be stored in multiple locations, that the control information may be stored in multiple locations for purposes of redundancy, for example, or that the control information may otherwise be distributed across multiple memory blocks in the storage drive171A-F.

In implementations, storage array controllers110may offload device management responsibilities from storage drives171A-F of storage array102A-B by retrieving, from the storage drives171A-F, control information describing the state of one or more memory blocks in the storage drives171A-F. Retrieving the control information from the storage drives171A-F may be carried out, for example, by the storage array controller110querying the storage drives171A-F for the location of control information for a particular storage drive171A-F. The storage drives171A-F may be configured to execute instructions that enable the storage drive171A-F to identify the location of the control information. The instructions may be executed by a controller (not shown) associated with or otherwise located on the storage drive171A-F and may cause the storage drive171A-F to scan a portion of each memory block to identify the memory blocks that store control information for the storage drives171A-F. The storage drives171A-F may respond by sending a response message to the storage array controller110that includes the location of control information for the storage drive171A-F. Responsive to receiving the response message, storage array controllers110may issue a request to read data stored at the address associated with the location of control information for the storage drives171A-F.

In other implementations, the storage array controllers110may further offload device management responsibilities from storage drives171A-F by performing, in response to receiving the control information, a storage drive management operation. A storage drive management operation may include, for example, an operation that is typically performed by the storage drive171A-F (e.g., the controller (not shown) associated with a particular storage drive171A-F). A storage drive management operation may include, for example, ensuring that data is not written to failed memory blocks within the storage drive171A-F, ensuring that data is written to memory blocks within the storage drive171A-F in such a way that adequate wear leveling is achieved, and so forth.

In implementations, storage array102A-B may implement two or more storage array controllers110. For example, storage array102A may include storage array controllers110A and storage array controllers110B. At a given instance, a single storage array controller110(e.g., storage array controller110A) of a storage system100may be designated with primary status (also referred to as “primary controller” herein), and other storage array controllers110(e.g., storage array controller110A) may be designated with secondary status (also referred to as “secondary controller” herein). The primary controller may have particular rights, such as permission to alter data in persistent storage resource170A-B (e.g., writing data to persistent storage resource170A-B). At least some of the rights of the primary controller may supersede the rights of the secondary controller. For instance, the secondary controller may not have permission to alter data in persistent storage resource170A-B when the primary controller has the right. The status of storage array controllers110may change. For example, storage array controller110A may be designated with secondary status, and storage array controller110B may be designated with primary status.

In some implementations, a primary controller, such as storage array controller110A, may serve as the primary controller for one or more storage arrays102A-B, and a second controller, such as storage array controller110B, may serve as the secondary controller for the one or more storage arrays102A-B. For example, storage array controller110A may be the primary controller for storage array102A and storage array102B, and storage array controller110B may be the secondary controller for storage array102A and102B. In some implementations, storage array controllers110C and110D (also referred to as “storage processing modules”) may neither have primary or secondary status. Storage array controllers110C and110D, implemented as storage processing modules, may act as a communication interface between the primary and secondary controllers (e.g., storage array controllers110A and110B, respectively) and storage array102B. For example, storage array controller110A of storage array102A may send a write request, via SAN158, to storage array102B. The write request may be received by both storage array controllers110C and110D of storage array102B. Storage array controllers110C and110D facilitate the communication, e.g., send the write request to the appropriate storage drive171A-F. It may be noted that in some implementations storage processing modules may be used to increase the number of storage drives controlled by the primary and secondary controllers.

In implementations, storage array controllers110are communicatively coupled, via a midplane (not shown), to one or more storage drives171A-F and to one or more NVRAM devices (not shown) that are included as part of a storage array102A-B. The storage array controllers110may be coupled to the midplane via one or more data communication links and the midplane may be coupled to the storage drives171A-F and the NVRAM devices via one or more data communications links. The data communications links described herein are collectively illustrated by data communications links108A-D and may include a Peripheral Component Interconnect Express (‘PCIe’) bus, for example.

FIG.1Billustrates an example system for data storage, in accordance with some implementations. Storage array controller101illustrated inFIG.1Bmay similar to the storage array controllers110described with respect toFIG.1A. In one example, storage array controller101may be similar to storage array controller110A or storage array controller110B. Storage array controller101includes numerous elements for purposes of illustration rather than limitation. It may be noted that storage array controller101may include the same, more, or fewer elements configured in the same or different manner in other implementations. It may be noted that elements ofFIG.1Amay be included below to help illustrate features of storage array controller101.

Storage array controller101may include one or more processing devices104and random access memory (‘RAM’)111. Processing device104(or controller101) represents one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like. More particularly, the processing device104(or controller101) may be a complex instruction set computing (‘CISC’) microprocessor, reduced instruction set computing (‘RISC’) microprocessor, very long instruction word (‘VLIW’) microprocessor, or a processor implementing other instruction sets or processors implementing a combination of instruction sets. The processing device104(or controller101) may also be one or more special-purpose processing devices such as an application specific integrated circuit (‘ASIC’), a field programmable gate array (‘FPGA’), a digital signal processor (‘DSP’), network processor, or the like.

The processing device104may be connected to the RAM111via a data communications link106, which may be embodied as a high speed memory bus such as a Double-Data Rate4(‘DDR4’) bus. Stored in RAM111is an operating system112. In some implementations, instructions113are stored in RAM111. Instructions113may include computer program instructions for performing operations in in a direct-mapped flash storage system. In one embodiment, a direct-mapped flash storage system is one that that addresses data blocks within flash drives directly and without an address translation performed by the storage controllers of the flash drives.

In implementations, storage array controller101includes one or more host bus adapters103A-C that are coupled to the processing device104via a data communications link105A-C. In implementations, host bus adapters103A-C may be computer hardware that connects a host system (e.g., the storage array controller) to other network and storage arrays. In some examples, host bus adapters103A-C may be a Fibre Channel adapter that enables the storage array controller101to connect to a SAN, an Ethernet adapter that enables the storage array controller101to connect to a LAN, or the like. Host bus adapters103A-C may be coupled to the processing device104via a data communications link105A-C such as, for example, a PCIe bus.

In implementations, storage array controller101may include a host bus adapter114that is coupled to an expander115. The expander115may be used to attach a host system to a larger number of storage drives. The expander115may, for example, be a SAS expander utilized to enable the host bus adapter114to attach to storage drives in an implementation where the host bus adapter114is embodied as a SAS controller.

In implementations, storage array controller101may include a switch116coupled to the processing device104via a data communications link109. The switch116may be a computer hardware device that can create multiple endpoints out of a single endpoint, thereby enabling multiple devices to share a single endpoint. The switch116may, for example, be a PCIe switch that is coupled to a PCIe bus (e.g., data communications link109) and presents multiple PCIe connection points to the midplane.

In implementations, storage array controller101includes a data communications link107for coupling the storage array controller101to other storage array controllers. In some examples, data communications link107may be a QuickPath Interconnect (QPI) interconnect.

A traditional storage system that uses traditional flash drives may implement a process across the flash drives that are part of the traditional storage system. For example, a higher level process of the storage system may initiate and control a process across the flash drives. However, a flash drive of the traditional storage system may include its own storage controller that also performs the process. Thus, for the traditional storage system, a higher level process (e.g., initiated by the storage system) and a lower level process (e.g., initiated by a storage controller of the storage system) may both be performed.

To resolve various deficiencies of a traditional storage system, operations may be performed by higher level processes and not by the lower level processes. For example, the flash storage system may include flash drives that do not include storage controllers that provide the process. Thus, the operating system of the flash storage system itself may initiate and control the process. This may be accomplished by a direct-mapped flash storage system that addresses data blocks within the flash drives directly and without an address translation performed by the storage controllers of the flash drives.

The operating system of the flash storage system may identify and maintain a list of allocation units across multiple flash drives of the flash storage system. The allocation units may be entire erase blocks or multiple erase blocks. The operating system may maintain a map or address range that directly maps addresses to erase blocks of the flash drives of the flash storage system.

Direct mapping to the erase blocks of the flash drives may be used to rewrite data and erase data. For example, the operations may be performed on one or more allocation units that include a first data and a second data where the first data is to be retained and the second data is no longer being used by the flash storage system. The operating system may initiate the process to write the first data to new locations within other allocation units and erasing the second data and marking the allocation units as being available for use for subsequent data. Thus, the process may only be performed by the higher level operating system of the flash storage system without an additional lower level process being performed by controllers of the flash drives.

Advantages of the process being performed only by the operating system of the flash storage system include increased reliability of the flash drives of the flash storage system as unnecessary or redundant write operations are not being performed during the process. One possible point of novelty here is the concept of initiating and controlling the process at the operating system of the flash storage system. In addition, the process can be controlled by the operating system across multiple flash drives. This is contrast to the process being performed by a storage controller of a flash drive.

A storage system can consist of two storage array controllers that share a set of drives for failover purposes, or it could consist of a single storage array controller that provides a storage service that utilizes multiple drives, or it could consist of a distributed network of storage array controllers each with some number of drives or some amount of Flash storage where the storage array controllers in the network collaborate to provide a complete storage service and collaborate on various aspects of a storage service including storage allocation and garbage collection.

FIG.1Cillustrates a third example system117for data storage in accordance with some implementations. System117(also referred to as “storage system” herein) includes numerous elements for purposes of illustration rather than limitation. It may be noted that system117may include the same, more, or fewer elements configured in the same or different manner in other implementations.

In one embodiment, system117includes a dual Peripheral Component Interconnect (‘PCI’) flash storage device118with separately addressable fast write storage. System117may include a storage controller119. In one embodiment, storage controller119may be a CPU, ASIC, FPGA, or any other circuitry that may implement control structures necessary according to the present disclosure. In one embodiment, system117includes flash memory devices (e.g., including flash memory devices120a-n), operatively coupled to various channels of the storage device controller119. Flash memory devices120a-n, may be presented to the controller119as an addressable collection of Flash pages, erase blocks, and/or control elements sufficient to allow the storage device controller119to program and retrieve various aspects of the Flash. In one embodiment, storage device controller119may perform operations on flash memory devices120A-N including storing and retrieving data content of pages, arranging and erasing any blocks, tracking statistics related to the use and reuse of Flash memory pages, erase blocks, and cells, tracking and predicting error codes and faults within the Flash memory, controlling voltage levels associated with programming and retrieving contents of Flash cells, etc.

In one embodiment, system117may include RAM121to store separately addressable fast-write data. In one embodiment, RAM121may be one or more separate discrete devices. In another embodiment, RAM121may be integrated into storage device controller119or multiple storage device controllers. The RAM121may be utilized for other purposes as well, such as temporary program memory for a processing device (e.g., a CPU) in the storage device controller119.

In one embodiment, system119may include a stored energy device122, such as a rechargeable battery or a capacitor. Stored energy device122may store energy sufficient to power the storage device controller119, some amount of the RAM (e.g., RAM121), and some amount of Flash memory (e.g., Flash memory120a-120n) for sufficient time to write the contents of RAM to Flash memory. In one embodiment, storage device controller119may write the contents of RAM to Flash Memory if the storage device controller detects loss of external power.

In one embodiment, system117includes two data communications links123a,123b. In one embodiment, data communications links123a,123bmay be PCI interfaces. In another embodiment, data communications links123a,123bmay be based on other communications standards (e.g., HyperTransport, InfiniBand, etc.). Data communications links123a,123bmay be based on non-volatile memory express (‘NVMe’) or NVMe over fabrics (‘NVMf’) specifications that allow external connection to the storage device controller119from other components in the storage system117. It should be noted that data communications links may be interchangeably referred to herein as PCI buses for convenience.

System117may also include an external power source (not shown), which may be provided over one or both data communications links123a,123b, or which may be provided separately. An alternative embodiment includes a separate Flash memory (not shown) dedicated for use in storing the content of RAM121. The storage device controller119may present a logical device over a PCI bus which may include an addressable fast-write logical device, or a distinct part of the logical address space of the storage device118, which may be presented as PCI memory or as persistent storage. In one embodiment, operations to store into the device are directed into the RAM121. On power failure, the storage device controller119may write stored content associated with the addressable fast-write logical storage to Flash memory (e.g., Flash memory120a-n) for long-term persistent storage.

In one embodiment, the logical device may include some presentation of some or all of the content of the Flash memory devices120a-n, where that presentation allows a storage system including a storage device118(e.g., storage system117) to directly address Flash memory pages and directly reprogram erase blocks from storage system components that are external to the storage device through the PCI bus. The presentation may also allow one or more of the external components to control and retrieve other aspects of the Flash memory including some or all of: tracking statistics related to use and reuse of Flash memory pages, erase blocks, and cells across all the Flash memory devices; tracking and predicting error codes and faults within and across the Flash memory devices; controlling voltage levels associated with programming and retrieving contents of Flash cells; etc.

In one embodiment, the stored energy device122may be sufficient to ensure completion of in-progress operations to the Flash memory devices107a-120nstored energy device122may power storage device controller119and associated Flash memory devices (e.g.,120a-n) for those operations, as well as for the storing of fast-write RAM to Flash memory. Stored energy device122may be used to store accumulated statistics and other parameters kept and tracked by the Flash memory devices120a-nand/or the storage device controller119. Separate capacitors or stored energy devices (such as smaller capacitors near or embedded within the Flash memory devices themselves) may be used for some or all of the operations described herein.

Various schemes may be used to track and optimize the life span of the stored energy component, such as adjusting voltage levels over time, partially discharging the storage energy device122to measure corresponding discharge characteristics, etc. If the available energy decreases over time, the effective available capacity of the addressable fast-write storage may be decreased to ensure that it can be written safely based on the currently available stored energy.

FIG.1Dillustrates a third example system124for data storage in accordance with some implementations. In one embodiment, system124includes storage controllers125a,125b. In one embodiment, storage controllers125a,125bare operatively coupled to Dual PCI storage devices119a,119band119c,119d, respectively. Storage controllers125a,125bmay be operatively coupled (e.g., via a storage network130) to some number of host computers127a-n.

In one embodiment, two storage controllers (e.g.,125aand125b) provide storage services, such as a SCS) block storage array, a file server, an object server, a database or data analytics service, etc. The storage controllers125a,125bmay provide services through some number of network interfaces (e.g.,126a-d) to host computers127a-noutside of the storage system124. Storage controllers125a,125bmay provide integrated services or an application entirely within the storage system124, forming a converged storage and compute system. The storage controllers125a,125bmay utilize the fast write memory within or across storage devices119a-dto journal in progress operations to ensure the operations are not lost on a power failure, storage controller removal, storage controller or storage system shutdown, or some fault of one or more software or hardware components within the storage system124.

In one embodiment, controllers125a,125boperate as PCI masters to one or the other PCI buses128a,128b. In another embodiment,128aand128bmay be based on other communications standards (e.g., HyperTransport, InfiniBand, etc.). Other storage system embodiments may operate storage controllers125a,125bas multi-masters for both PCI buses128a,128b. Alternately, a PCI/NVMe/NVMf switching infrastructure or fabric may connect multiple storage controllers. Some storage system embodiments may allow storage devices to communicate with each other directly rather than communicating only with storage controllers. In one embodiment, a storage device controller119amay be operable under direction from a storage controller125ato synthesize and transfer data to be stored into Flash memory devices from data that has been stored in RAM (e.g., RAM121ofFIG.1C). For example, a recalculated version of RAM content may be transferred after a storage controller has determined that an operation has fully committed across the storage system, or when fast-write memory on the device has reached a certain used capacity, or after a certain amount of time, to ensure improve safety of the data or to release addressable fast-write capacity for reuse. This mechanism may be used, for example, to avoid a second transfer over a bus (e.g.,128a,128b) from the storage controllers125a,125b. In one embodiment, a recalculation may include compressing data, attaching indexing or other metadata, combining multiple data segments together, performing erasure code calculations, etc.

In one embodiment, under direction from a storage controller125a,125b, a storage device controller119a,119bmay be operable to calculate and transfer data to other storage devices from data stored in RAM (e.g., RAM121ofFIG.1C) without involvement of the storage controllers125a,125b. This operation may be used to mirror data stored in one controller125ato another controller125b, or it could be used to offload compression, data aggregation, and/or erasure coding calculations and transfers to storage devices to reduce load on storage controllers or the storage controller interface129a,129bto the PCI bus128a,128b.

A storage device controller119may include mechanisms for implementing high availability primitives for use by other parts of a storage system external to the Dual PCI storage device118. For example, reservation or exclusion primitives may be provided so that, in a storage system with two storage controllers providing a highly available storage service, one storage controller may prevent the other storage controller from accessing or continuing to access the storage device. This could be used, for example, in cases where one controller detects that the other controller is not functioning properly or where the interconnect between the two storage controllers may itself not be functioning properly.

In one embodiment, a storage system for use with Dual PCI direct mapped storage devices with separately addressable fast write storage includes systems that manage erase blocks or groups of erase blocks as allocation units for storing data on behalf of the storage service, or for storing metadata (e.g., indexes, logs, etc.) associated with the storage service, or for proper management of the storage system itself. Flash pages, which may be a few kilobytes in size, may be written as data arrives or as the storage system is to persist data for long intervals of time (e.g., above a defined threshold of time). To commit data more quickly, or to reduce the number of writes to the Flash memory devices, the storage controllers may first write data into the separately addressable fast write storage on one more storage devices.

In one embodiment, the storage controllers125a,125bmay initiate the use of erase blocks within and across storage devices (e.g.,118) in accordance with an age and expected remaining lifespan of the storage devices, or based on other statistics. The storage controllers125a,125bmay initiate garbage collection and data migration data between storage devices in accordance with pages that are no longer needed as well as to manage Flash page and erase block lifespans and to manage overall system performance.

In one embodiment, the storage system124may utilize mirroring and/or erasure coding schemes as part of storing data into addressable fast write storage and/or as part of writing data into allocation units associated with erase blocks. Erasure codes may be used across storage devices, as well as within erase blocks or allocation units, or within and across Flash memory devices on a single storage device, to provide redundancy against single or multiple storage device failures or to protect against internal corruptions of Flash memory pages resulting from Flash memory operations or from degradation of Flash memory cells. Mirroring and erasure coding at various levels may be used to recover from multiple types of failures that occur separately or in combination.

The embodiments depicted with reference toFIGS.2A-Gillustrate a storage cluster that stores user data, such as user data originating from one or more user or client systems or other sources external to the storage cluster. The storage cluster distributes user data across storage nodes housed within a chassis, or across multiple chassis, using erasure coding and redundant copies of metadata. Erasure coding refers to a method of data protection or reconstruction in which data is stored across a set of different locations, such as disks, storage nodes or geographic locations. Flash memory is one type of solid-state memory that may be integrated with the embodiments, although the embodiments may be extended to other types of solid-state memory or other storage medium, including non-solid state memory. Control of storage locations and workloads are distributed across the storage locations in a clustered peer-to-peer system. Tasks such as mediating communications between the various storage nodes, detecting when a storage node has become unavailable, and balancing I/Os (inputs and outputs) across the various storage nodes, are all handled on a distributed basis. Data is laid out or distributed across multiple storage nodes in data fragments or stripes that support data recovery in some embodiments. Ownership of data can be reassigned within a cluster, independent of input and output patterns. This architecture described in more detail below allows a storage node in the cluster to fail, with the system remaining operational, since the data can be reconstructed from other storage nodes and thus remain available for input and output operations. In various embodiments, a storage node may be referred to as a cluster node, a blade, or a server.

The storage cluster may be contained within a chassis, i.e., an enclosure housing one or more storage nodes. A mechanism to provide power to each storage node, such as a power distribution bus, and a communication mechanism, such as a communication bus that enables communication between the storage nodes are included within the chassis. The storage cluster can run as an independent system in one location according to some embodiments. In one embodiment, a chassis contains at least two instances of both the power distribution and the communication bus which may be enabled or disabled independently. The internal communication bus may be an Ethernet bus, however, other technologies such as PCIe, InfiniBand, and others, are equally suitable. The chassis provides a port for an external communication bus for enabling communication between multiple chassis, directly or through a switch, and with client systems. The external communication may use a technology such as Ethernet, InfiniBand, Fibre Channel, etc. In some embodiments, the external communication bus uses different communication bus technologies for inter-chassis and client communication. If a switch is deployed within or between chassis, the switch may act as a translation between multiple protocols or technologies. When multiple chassis are connected to define a storage cluster, the storage cluster may be accessed by a client using either proprietary interfaces or standard interfaces such as network file system (‘NFS’), common internet file system (‘CIFS’), small computer system interface (‘SCSI’) or hypertext transfer protocol (‘HTTP’). Translation from the client protocol may occur at the switch, chassis external communication bus or within each storage node. In some embodiments, multiple chassis may be coupled or connected to each other through an aggregator switch. A portion and/or all of the coupled or connected chassis may be designated as a storage cluster. As discussed above, each chassis can have multiple blades, each blade has a media access control (‘MAC’) address, but the storage cluster is presented to an external network as having a single cluster IP address and a single MAC address in some embodiments.

Each storage node may be one or more storage servers and each storage server is connected to one or more non-volatile solid state memory units, which may be referred to as storage units or storage devices. One embodiment includes a single storage server in each storage node and between one to eight non-volatile solid state memory units, however this one example is not meant to be limiting. The storage server may include a processor, DRAM and interfaces for the internal communication bus and power distribution for each of the power buses. Inside the storage node, the interfaces and storage unit share a communication bus, e.g., PCI Express, in some embodiments. The non-volatile solid state memory units may directly access the internal communication bus interface through a storage node communication bus, or request the storage node to access the bus interface. The non-volatile solid state memory unit contains an embedded CPU, solid state storage controller, and a quantity of solid state mass storage, e.g., between 2-32 terabytes (‘TB’) in some embodiments. An embedded volatile storage medium, such as DRAM, and an energy reserve apparatus are included in the non-volatile solid state memory unit. In some embodiments, the energy reserve apparatus is a capacitor, super-capacitor, or battery that enables transferring a subset of DRAM contents to a stable storage medium in the case of power loss. In some embodiments, the non-volatile solid state memory unit is constructed with a storage class memory, such as phase change or magnetoresistive random access memory (‘MRAM’) that substitutes for DRAM and enables a reduced power hold-up apparatus.

One of many features of the storage nodes and non-volatile solid state storage is the ability to proactively rebuild data in a storage cluster. The storage nodes and non-volatile solid state storage can determine when a storage node or non-volatile solid state storage in the storage cluster is unreachable, independent of whether there is an attempt to read data involving that storage node or non-volatile solid state storage. The storage nodes and non-volatile solid state storage then cooperate to recover and rebuild the data in at least partially new locations. This constitutes a proactive rebuild, in that the system rebuilds data without waiting until the data is needed for a read access initiated from a client system employing the storage cluster. These and further details of the storage memory and operation thereof are discussed below.

FIG.2Ais a perspective view of a storage cluster161, with multiple storage nodes150and internal solid-state memory coupled to each storage node to provide network attached storage or storage area network, in accordance with some embodiments. A network attached storage, storage area network, or a storage cluster, or other storage memory, could include one or more storage clusters161, each having one or more storage nodes150, in a flexible and reconfigurable arrangement of both the physical components and the amount of storage memory provided thereby. The storage cluster161is designed to fit in a rack, and one or more racks can be set up and populated as desired for the storage memory. The storage cluster161has a chassis138having multiple slots142. It should be appreciated that chassis138may be referred to as a housing, enclosure, or rack unit. In one embodiment, the chassis138has fourteen slots142, although other numbers of slots are readily devised. For example, some embodiments have four slots, eight slots, sixteen slots, thirty-two slots, or other suitable number of slots. Each slot142can accommodate one storage node150in some embodiments. Chassis138includes flaps148that can be utilized to mount the chassis138on a rack. Fans144provide air circulation for cooling of the storage nodes150and components thereof, although other cooling components could be used, or an embodiment could be devised without cooling components. A switch fabric146couples storage nodes150within chassis138together and to a network for communication to the memory. In an embodiment depicted in herein, the slots142to the left of the switch fabric146and fans144are shown occupied by storage nodes150, while the slots142to the right of the switch fabric146and fans144are empty and available for insertion of storage node150for illustrative purposes. This configuration is one example, and one or more storage nodes150could occupy the slots142in various further arrangements. The storage node arrangements need not be sequential or adjacent in some embodiments. Storage nodes150are hot pluggable, meaning that a storage node150can be inserted into a slot142in the chassis138, or removed from a slot142, without stopping or powering down the system. Upon insertion or removal of storage node150from slot142, the system automatically reconfigures in order to recognize and adapt to the change. Reconfiguration, in some embodiments, includes restoring redundancy and/or rebalancing data or load.

Each storage node150can have multiple components. In the embodiment shown here, the storage node150includes a printed circuit board159populated by a CPU156, i.e., processor, a memory154coupled to the CPU156, and a non-volatile solid state storage152coupled to the CPU156, although other mountings and/or components could be used in further embodiments. The memory154has instructions which are executed by the CPU156and/or data operated on by the CPU156. As further explained below, the non-volatile solid state storage152includes flash or, in further embodiments, other types of solid-state memory.

Referring toFIG.2A, storage cluster161is scalable, meaning that storage capacity with non-uniform storage sizes is readily added, as described above. One or more storage nodes150can be plugged into or removed from each chassis and the storage cluster self-configures in some embodiments. Plug-in storage nodes150, whether installed in a chassis as delivered or later added, can have different sizes. For example, in one embodiment a storage node150can have any multiple of 4 TB, e.g., 8 TB, 12 TB, 16 TB, 32 TB, etc. In further embodiments, a storage node150could have any multiple of other storage amounts or capacities. Storage capacity of each storage node150is broadcast, and influences decisions of how to stripe the data. For maximum storage efficiency, an embodiment can self-configure as wide as possible in the stripe, subject to a predetermined requirement of continued operation with loss of up to one, or up to two, non-volatile solid state storage units152or storage nodes150within the chassis.

FIG.2Bis a block diagram showing a communications interconnect171A-F and power distribution bus172coupling multiple storage nodes150. Referring back toFIG.2A, the communications interconnect171A-F can be included in or implemented with the switch fabric146in some embodiments. Where multiple storage clusters161occupy a rack, the communications interconnect171A-F can be included in or implemented with a top of rack switch, in some embodiments. As illustrated inFIG.2B, storage cluster161is enclosed within a single chassis138. External port176is coupled to storage nodes150through communications interconnect171A-F, while external port174is coupled directly to a storage node. External power port178is coupled to power distribution bus172. Storage nodes150may include varying amounts and differing capacities of non-volatile solid state storage152as described with reference toFIG.2A. In addition, one or more storage nodes150may be a compute only storage node as illustrated inFIG.2B. Authorities168are implemented on the non-volatile solid state storages152, for example as lists or other data structures stored in memory. In some embodiments the authorities are stored within the non-volatile solid state storage152and supported by software executing on a controller or other processor of the non-volatile solid state storage152. In a further embodiment, authorities168are implemented on the storage nodes150, for example as lists or other data structures stored in the memory154and supported by software executing on the CPU156of the storage node150. Authorities168control how and where data is stored in the non-volatile solid state storages152in some embodiments. This control assists in determining which type of erasure coding scheme is applied to the data, and which storage nodes150have which portions of the data. Each authority168may be assigned to a non-volatile solid state storage152. Each authority may control a range of inode numbers, segment numbers, or other data identifiers which are assigned to data by a file system, by the storage nodes150, or by the non-volatile solid state storage152, in various embodiments.

Every piece of data, and every piece of metadata, has redundancy in the system in some embodiments. In addition, every piece of data and every piece of metadata has an owner, which may be referred to as an authority. If that authority is unreachable, for example through failure of a storage node, there is a plan of succession for how to find that data or that metadata. In various embodiments, there are redundant copies of authorities168. Authorities168have a relationship to storage nodes150and non-volatile solid state storage152in some embodiments. Each authority168, covering a range of data segment numbers or other identifiers of the data, may be assigned to a specific non-volatile solid state storage152. In some embodiments the authorities168for all of such ranges are distributed over the non-volatile solid state storages152of a storage cluster. Each storage node150has a network port that provides access to the non-volatile solid state storage(s)152of that storage node150. Data can be stored in a segment, which is associated with a segment number and that segment number is an indirection for a configuration of a RAID (redundant array of independent disks) stripe in some embodiments. The assignment and use of the authorities168thus establishes an indirection to data. Indirection may be referred to as the ability to reference data indirectly, in this case via an authority168, in accordance with some embodiments. A segment identifies a set of non-volatile solid state storage152and a local identifier into the set of non-volatile solid state storage152that may contain data. In some embodiments, the local identifier is an offset into the device and may be reused sequentially by multiple segments. In other embodiments the local identifier is unique for a specific segment and never reused. The offsets in the non-volatile solid state storage152are applied to locating data for writing to or reading from the non-volatile solid state storage152(in the form of a RAID stripe). Data is striped across multiple units of non-volatile solid state storage152, which may include or be different from the non-volatile solid state storage152having the authority168for a particular data segment.

If there is a change in where a particular segment of data is located, e.g., during a data move or a data reconstruction, the authority168for that data segment should be consulted, at that non-volatile solid state storage152or storage node150having that authority168. In order to locate a particular piece of data, embodiments calculate a hash value for a data segment or apply an inode number or a data segment number. The output of this operation points to a non-volatile solid state storage152having the authority168for that particular piece of data. In some embodiments there are two stages to this operation. The first stage maps an entity identifier (ID), e.g., a segment number, inode number, or directory number to an authority identifier. This mapping may include a calculation such as a hash or a bit mask. The second stage is mapping the authority identifier to a particular non-volatile solid state storage152, which may be done through an explicit mapping. The operation is repeatable, so that when the calculation is performed, the result of the calculation repeatably and reliably points to a particular non-volatile solid state storage152having that authority168. The operation may include the set of reachable storage nodes as input. If the set of reachable non-volatile solid state storage units changes the optimal set changes. In some embodiments, the persisted value is the current assignment (which is always true) and the calculated value is the target assignment the cluster will attempt to reconfigure towards. This calculation may be used to determine the optimal non-volatile solid state storage152for an authority in the presence of a set of non-volatile solid state storage152that are reachable and constitute the same cluster. The calculation also determines an ordered set of peer non-volatile solid state storage152that will also record the authority to non-volatile solid state storage mapping so that the authority may be determined even if the assigned non-volatile solid state storage is unreachable. A duplicate or substitute authority168may be consulted if a specific authority168is unavailable in some embodiments.

With reference toFIGS.2A and2B, two of the many tasks of the CPU156on a storage node150are to break up write data, and reassemble read data. When the system has determined that data is to be written, the authority168for that data is located as above. When the segment ID for data is already determined the request to write is forwarded to the non-volatile solid state storage152currently determined to be the host of the authority168determined from the segment. The host CPU156of the storage node150, on which the non-volatile solid state storage152and corresponding authority168reside, then breaks up or shards the data and transmits the data out to various non-volatile solid state storage152. The transmitted data is written as a data stripe in accordance with an erasure coding scheme. In some embodiments, data is requested to be pulled, and in other embodiments, data is pushed. In reverse, when data is read, the authority168for the segment ID containing the data is located as described above. The host CPU156of the storage node150on which the non-volatile solid state storage152and corresponding authority168reside requests the data from the non-volatile solid state storage and corresponding storage nodes pointed to by the authority. In some embodiments the data is read from flash storage as a data stripe. The host CPU156of storage node150then reassembles the read data, correcting any errors (if present) according to the appropriate erasure coding scheme, and forwards the reassembled data to the network. In further embodiments, some or all of these tasks can be handled in the non-volatile solid state storage152. In some embodiments, the segment host requests the data be sent to storage node150by requesting pages from storage and then sending the data to the storage node making the original request.

In some systems, for example in UNIX-style file systems, data is handled with an index node or inode, which specifies a data structure that represents an object in a file system. The object could be a file or a directory, for example. Metadata may accompany the object, as attributes such as permission data and a creation timestamp, among other attributes. A segment number could be assigned to all or a portion of such an object in a file system. In other systems, data segments are handled with a segment number assigned elsewhere. For purposes of discussion, the unit of distribution is an entity, and an entity can be a file, a directory or a segment. That is, entities are units of data or metadata stored by a storage system. Entities are grouped into sets called authorities. Each authority has an authority owner, which is a storage node that has the exclusive right to update the entities in the authority. In other words, a storage node contains the authority, and that the authority, in turn, contains entities.

A segment is a logical container of data in accordance with some embodiments. A segment is an address space between medium address space and physical flash locations, i.e., the data segment number, are in this address space. Segments may also contain meta-data, which enable data redundancy to be restored (rewritten to different flash locations or devices) without the involvement of higher level software. In one embodiment, an internal format of a segment contains client data and medium mappings to determine the position of that data. Each data segment is protected, e.g., from memory and other failures, by breaking the segment into a number of data and parity shards, where applicable. The data and parity shards are distributed, i.e., striped, across non-volatile solid state storage152coupled to the host CPUs156(SeeFIGS.2E and2G) in accordance with an erasure coding scheme. Usage of the term segments refers to the container and its place in the address space of segments in some embodiments. Usage of the term stripe refers to the same set of shards as a segment and includes how the shards are distributed along with redundancy or parity information in accordance with some embodiments.

A series of address-space transformations takes place across an entire storage system. At the top are the directory entries (file names) which link to an inode. Inodes point into medium address space, where data is logically stored. Medium addresses may be mapped through a series of indirect mediums to spread the load of large files, or implement data services like deduplication or snapshots. Medium addresses may be mapped through a series of indirect mediums to spread the load of large files, or implement data services like deduplication or snapshots. Segment addresses are then translated into physical flash locations. Physical flash locations have an address range bounded by the amount of flash in the system in accordance with some embodiments. Medium addresses and segment addresses are logical containers, and in some embodiments use a 128 bit or larger identifier so as to be practically infinite, with a likelihood of reuse calculated as longer than the expected life of the system. Addresses from logical containers are allocated in a hierarchical fashion in some embodiments. Initially, each non-volatile solid state storage unit152may be assigned a range of address space. Within this assigned range, the non-volatile solid state storage152is able to allocate addresses without synchronization with other non-volatile solid state storage152.

Data and metadata is stored by a set of underlying storage layouts that are optimized for varying workload patterns and storage devices. These layouts incorporate multiple redundancy schemes, compression formats and index algorithms. Some of these layouts store information about authorities and authority masters, while others store file metadata and file data. The redundancy schemes include error correction codes that tolerate corrupted bits within a single storage device (such as a NAND flash chip), erasure codes that tolerate the failure of multiple storage nodes, and replication schemes that tolerate data center or regional failures. In some embodiments, low density parity check (‘LDPC’) code is used within a single storage unit. Reed-Solomon encoding is used within a storage cluster, and mirroring is used within a storage grid in some embodiments. Metadata may be stored using an ordered log structured index (such as a Log Structured Merge Tree), and large data may not be stored in a log structured layout.

In order to maintain consistency across multiple copies of an entity, the storage nodes agree implicitly on two things through calculations: (1) the authority that contains the entity, and (2) the storage node that contains the authority. The assignment of entities to authorities can be done by pseudo randomly assigning entities to authorities, by splitting entities into ranges based upon an externally produced key, or by placing a single entity into each authority. Examples of pseudorandom schemes are linear hashing and the Replication Under Scalable Hashing (‘RUSH’) family of hashes, including Controlled Replication Under Scalable Hashing (‘CRUSH’). In some embodiments, pseudo-random assignment is utilized only for assigning authorities to nodes because the set of nodes can change. The set of authorities cannot change so any subjective function may be applied in these embodiments. Some placement schemes automatically place authorities on storage nodes, while other placement schemes rely on an explicit mapping of authorities to storage nodes. In some embodiments, a pseudorandom scheme is utilized to map from each authority to a set of candidate authority owners. A pseudorandom data distribution function related to CRUSH may assign authorities to storage nodes and create a list of where the authorities are assigned. Each storage node has a copy of the pseudorandom data distribution function, and can arrive at the same calculation for distributing, and later finding or locating an authority. Each of the pseudorandom schemes requires the reachable set of storage nodes as input in some embodiments in order to conclude the same target nodes. Once an entity has been placed in an authority, the entity may be stored on physical devices so that no expected failure will lead to unexpected data loss. In some embodiments, rebalancing algorithms attempt to store the copies of all entities within an authority in the same layout and on the same set of machines.

Examples of expected failures include device failures, stolen machines, datacenter fires, and regional disasters, such as nuclear or geological events. Different failures lead to different levels of acceptable data loss. In some embodiments, a stolen storage node impacts neither the security nor the reliability of the system, while depending on system configuration, a regional event could lead to no loss of data, a few seconds or minutes of lost updates, or even complete data loss.

In the embodiments, the placement of data for storage redundancy is independent of the placement of authorities for data consistency. In some embodiments, storage nodes that contain authorities do not contain any persistent storage. Instead, the storage nodes are connected to non-volatile solid state storage units that do not contain authorities. The communications interconnect between storage nodes and non-volatile solid state storage units consists of multiple communication technologies and has non-uniform performance and fault tolerance characteristics. In some embodiments, as mentioned above, non-volatile solid state storage units are connected to storage nodes via PCI express, storage nodes are connected together within a single chassis using Ethernet backplane, and chassis are connected together to form a storage cluster. Storage clusters are connected to clients using Ethernet or fiber channel in some embodiments. If multiple storage clusters are configured into a storage grid, the multiple storage clusters are connected using the Internet or other long-distance networking links, such as a “metro scale” link or private link that does not traverse the internet.

Authority owners have the exclusive right to modify entities, to migrate entities from one non-volatile solid state storage unit to another non-volatile solid state storage unit, and to add and remove copies of entities. This allows for maintaining the redundancy of the underlying data. When an authority owner fails, is going to be decommissioned, or is overloaded, the authority is transferred to a new storage node. Transient failures make it non-trivial to ensure that all non-faulty machines agree upon the new authority location. The ambiguity that arises due to transient failures can be achieved automatically by a consensus protocol such as Paxos, hot-warm failover schemes, via manual intervention by a remote system administrator, or by a local hardware administrator (such as by physically removing the failed machine from the cluster, or pressing a button on the failed machine). In some embodiments, a consensus protocol is used, and failover is automatic. If too many failures or replication events occur in too short a time period, the system goes into a self-preservation mode and halts replication and data movement activities until an administrator intervenes in accordance with some embodiments.

As authorities are transferred between storage nodes and authority owners update entities in their authorities, the system transfers messages between the storage nodes and non-volatile solid state storage units. With regard to persistent messages, messages that have different purposes are of different types. Depending on the type of the message, the system maintains different ordering and durability guarantees. As the persistent messages are being processed, the messages are temporarily stored in multiple durable and non-durable storage hardware technologies. In some embodiments, messages are stored in RAM, NVRAM and on NAND flash devices, and a variety of protocols are used in order to make efficient use of each storage medium. Latency-sensitive client requests may be persisted in replicated NVRAM, and then later NAND, while background rebalancing operations are persisted directly to NAND.

Persistent messages are persistently stored prior to being transmitted. This allows the system to continue to serve client requests despite failures and component replacement. Although many hardware components contain unique identifiers that are visible to system administrators, manufacturer, hardware supply chain and ongoing monitoring quality control infrastructure, applications running on top of the infrastructure address virtualize addresses. These virtualized addresses do not change over the lifetime of the storage system, regardless of component failures and replacements. This allows each component of the storage system to be replaced over time without reconfiguration or disruptions of client request processing, i.e., the system supports non-disruptive upgrades.

In some embodiments, the virtualized addresses are stored with sufficient redundancy. A continuous monitoring system correlates hardware and software status and the hardware identifiers. This allows detection and prediction of failures due to faulty components and manufacturing details. The monitoring system also enables the proactive transfer of authorities and entities away from impacted devices before failure occurs by removing the component from the critical path in some embodiments.

FIG.2Cis a multiple level block diagram, showing contents of a storage node150and contents of a non-volatile solid state storage152of the storage node150. Data is communicated to and from the storage node150by a network interface controller (‘NIC’)202in some embodiments. Each storage node150has a CPU156, and one or more non-volatile solid state storage152, as discussed above. Moving down one level inFIG.2C, each non-volatile solid state storage152has a relatively fast non-volatile solid state memory, such as nonvolatile random access memory (‘NVRAM’)204, and flash memory206. In some embodiments, NVRAM204may be a component that does not require program/erase cycles (DRAM, MRAM, PCM), and can be a memory that can support being written vastly more often than the memory is read from. Moving down another level inFIG.2C, the NVRAM204is implemented in one embodiment as high speed volatile memory, such as dynamic random access memory (DRAM)216, backed up by energy reserve218. Energy reserve218provides sufficient electrical power to keep the DRAM216powered long enough for contents to be transferred to the flash memory206in the event of power failure. In some embodiments, energy reserve218is a capacitor, super-capacitor, battery, or other device, that supplies a suitable supply of energy sufficient to enable the transfer of the contents of DRAM216to a stable storage medium in the case of power loss. The flash memory206is implemented as multiple flash dies222, which may be referred to as packages of flash dies222or an array of flash dies222. It should be appreciated that the flash dies222could be packaged in any number of ways, with a single die per package, multiple dies per package (i.e. multichip packages), in hybrid packages, as bare dies on a printed circuit board or other substrate, as encapsulated dies, etc. In the embodiment shown, the non-volatile solid state storage152has a controller212or other processor, and an input output (I/O) port210coupled to the controller212. I/O port210is coupled to the CPU156and/or the network interface controller202of the flash storage node150. Flash input output (I/O) port220is coupled to the flash dies222, and a direct memory access unit (DMA)214is coupled to the controller212, the DRAM216and the flash dies222. In the embodiment shown, the I/O port210, controller212, DMA unit214and flash I/O port220are implemented on a programmable logic device (‘PLD’)208, e.g., a field programmable gate array (FPGA). In this embodiment, each flash die222has pages, organized as sixteen kB (kilobyte) pages224, and a register226through which data can be written to or read from the flash die222. In further embodiments, other types of solid-state memory are used in place of, or in addition to flash memory illustrated within flash die222.

Storage clusters161, in various embodiments as disclosed herein, can be contrasted with storage arrays in general. The storage nodes150are part of a collection that creates the storage cluster161. Each storage node150owns a slice of data and computing required to provide the data. Multiple storage nodes150cooperate to store and retrieve the data. Storage memory or storage devices, as used in storage arrays in general, are less involved with processing and manipulating the data. Storage memory or storage devices in a storage array receive commands to read, write, or erase data. The storage memory or storage devices in a storage array are not aware of a larger system in which they are embedded, or what the data means. Storage memory or storage devices in storage arrays can include various types of storage memory, such as RAM, solid state drives, hard disk drives, etc. The storage units152described herein have multiple interfaces active simultaneously and serving multiple purposes. In some embodiments, some of the functionality of a storage node150is shifted into a storage unit152, transforming the storage unit152into a combination of storage unit152and storage node150. Placing computing (relative to storage data) into the storage unit152places this computing closer to the data itself. The various system embodiments have a hierarchy of storage node layers with different capabilities. By contrast, in a storage array, a controller owns and knows everything about all of the data that the controller manages in a shelf or storage devices. In a storage cluster161, as described herein, multiple controllers in multiple storage units152and/or storage nodes150cooperate in various ways (e.g., for erasure coding, data sharding, metadata communication and redundancy, storage capacity expansion or contraction, data recovery, and so on).

FIG.2Dshows a storage server environment, which uses embodiments of the storage nodes150and storage units152ofFIGS.2A-C. In this version, each storage unit152has a processor such as controller212(seeFIG.2C), an FPGA (field programmable gate array), flash memory206, and NVRAM204(which is super-capacitor backed DRAM216, seeFIGS.2B and2C) on a PCIe (peripheral component interconnect express) board in a chassis138(seeFIG.2A). The storage unit152may be implemented as a single board containing storage, and may be the largest tolerable failure domain inside the chassis. In some embodiments, up to two storage units152may fail and the device will continue with no data loss.

The physical storage is divided into named regions based on application usage in some embodiments. The NVRAM204is a contiguous block of reserved memory in the storage unit152DRAM216, and is backed by NAND flash. NVRAM204is logically divided into multiple memory regions written for two as spool (e.g., spool region). Space within the NVRAM204spools is managed by each authority168independently. Each device provides an amount of storage space to each authority168. That authority168further manages lifetimes and allocations within that space. Examples of a spool include distributed transactions or notions. When the primary power to a storage unit152fails, onboard super-capacitors provide a short duration of power hold up. During this holdup interval, the contents of the NVRAM204are flushed to flash memory206. On the next power-on, the contents of the NVRAM204are recovered from the flash memory206.

As for the storage unit controller, the responsibility of the logical “controller” is distributed across each of the blades containing authorities168. This distribution of logical control is shown inFIG.2Das a host controller242, mid-tier controller244and storage unit controller(s)246. Management of the control plane and the storage plane are treated independently, although parts may be physically co-located on the same blade. Each authority168effectively serves as an independent controller. Each authority168provides its own data and metadata structures, its own background workers, and maintains its own lifecycle.

FIG.2Eis a blade252hardware block diagram, showing a control plane254, compute and storage planes256,258, and authorities168interacting with underlying physical resources, using embodiments of the storage nodes150and storage units152ofFIGS.2A-Cin the storage server environment ofFIG.2D. The control plane254is partitioned into a number of authorities168which can use the compute resources in the compute plane256to run on any of the blades252. The storage plane258is partitioned into a set of devices, each of which provides access to flash206and NVRAM204resources.

In the compute and storage planes256,258ofFIG.2E, the authorities168interact with the underlying physical resources (i.e., devices). From the point of view of an authority168, its resources are striped over all of the physical devices. From the point of view of a device, it provides resources to all authorities168, irrespective of where the authorities happen to run. Each authority168has allocated or has been allocated one or more partitions260of storage memory in the storage units152, e.g. partitions260in flash memory206and NVRAM204. Each authority168uses those allocated partitions260that belong to it, for writing or reading user data. Authorities can be associated with differing amounts of physical storage of the system. For example, one authority168could have a larger number of partitions260or larger sized partitions260in one or more storage units152than one or more other authorities168.

FIG.2Fdepicts elasticity software layers in blades252of a storage cluster, in accordance with some embodiments. In the elasticity structure, elasticity software is symmetric, i.e., each blade's compute module270runs the three identical layers of processes depicted inFIG.2F. Storage managers274execute read and write requests from other blades252for data and metadata stored in local storage unit152NVRAM204and flash206. Authorities168fulfill client requests by issuing the necessary reads and writes to the blades252on whose storage units152the corresponding data or metadata resides. Endpoints272parse client connection requests received from switch fabric146supervisory software, relay the client connection requests to the authorities168responsible for fulfillment, and relay the authorities'168responses to clients. The symmetric three-layer structure enables the storage system's high degree of concurrency. Elasticity scales out efficiently and reliably in these embodiments. In addition, elasticity implements a unique scale-out technique that balances work evenly across all resources regardless of client access pattern, and maximizes concurrency by eliminating much of the need for inter-blade coordination that typically occurs with conventional distributed locking.

Still referring toFIG.2F, authorities168running in the compute modules270of a blade252perform the internal operations required to fulfill client requests. One feature of elasticity is that authorities168are stateless, i.e., they cache active data and metadata in their own blades'252DRAMs for fast access, but the authorities store every update in their NVRAM204partitions on three separate blades252until the update has been written to flash206. All the storage system writes to NVRAM204are in triplicate to partitions on three separate blades252in some embodiments. With triple-mirrored NVRAM204and persistent storage protected by parity and Reed-Solomon RAID checksums, the storage system can survive concurrent failure of two blades252with no loss of data, metadata, or access to either.

Because authorities168are stateless, they can migrate between blades252. Each authority168has a unique identifier. NVRAM204and flash206partitions are associated with authorities'168identifiers, not with the blades252on which they are running in some. Thus, when an authority168migrates, the authority168continues to manage the same storage partitions from its new location. When a new blade252is installed in an embodiment of the storage cluster, the system automatically rebalances load by: partitioning the new blade's252storage for use by the system's authorities168, migrating selected authorities168to the new blade252, starting endpoints272on the new blade252and including them in the switch fabric's146client connection distribution algorithm.

From their new locations, migrated authorities168persist the contents of their NVRAM204partitions on flash206, process read and write requests from other authorities168, and fulfill the client requests that endpoints272direct to them. Similarly, if a blade252fails or is removed, the system redistributes its authorities168among the system's remaining blades252. The redistributed authorities168continue to perform their original functions from their new locations.

FIG.2Gdepicts authorities168and storage resources in blades252of a storage cluster, in accordance with some embodiments. Each authority168is exclusively responsible for a partition of the flash206and NVRAM204on each blade252. The authority168manages the content and integrity of its partitions independently of other authorities168. Authorities168compress incoming data and preserve it temporarily in their NVRAM204partitions, and then consolidate, RAID-protect, and persist the data in segments of the storage in their flash206partitions. As the authorities168write data to flash206, storage managers274perform the necessary flash translation to optimize write performance and maximize media longevity. In the background, authorities168“garbage collect,” or reclaim space occupied by data that clients have made obsolete by overwriting the data. It should be appreciated that since authorities'168partitions are disjoint, there is no need for distributed locking to execute client and writes or to perform background functions.

The embodiments described herein may utilize various software, communication and/or networking protocols. In addition, the configuration of the hardware and/or software may be adjusted to accommodate various protocols. For example, the embodiments may utilize Active Directory, which is a database based system that provides authentication, directory, policy, and other services in a WINDOWS™ environment. In these embodiments, LDAP (Lightweight Directory Access Protocol) is one example application protocol for querying and modifying items in directory service providers such as Active Directory. In some embodiments, a network lock manager (‘NLM’) is utilized as a facility that works in cooperation with the Network File System (‘NFS’) to provide a System V style of advisory file and record locking over a network. The Server Message Block (‘SMB’) protocol, one version of which is also known as Common Internet File System (‘CIFS’), may be integrated with the storage systems discussed herein. SMP operates as an application-layer network protocol typically used for providing shared access to files, printers, and serial ports and miscellaneous communications between nodes on a network. SMB also provides an authenticated inter-process communication mechanism. AMAZON™ S3 (Simple Storage Service) is a web service offered by Amazon Web Services, and the systems described herein may interface with Amazon S3 through web services interfaces (REST (representational state transfer), SOAP (simple object access protocol), and BitTorrent). A RESTful API (application programming interface) breaks down a transaction to create a series of small modules. Each module addresses a particular underlying part of the transaction. The control or permissions provided with these embodiments, especially for object data, may include utilization of an access control list (‘ACL’). The ACL is a list of permissions attached to an object and the ACL specifies which users or system processes are granted access to objects, as well as what operations are allowed on given objects. The systems may utilize Internet Protocol version 6 (‘IPv6’), as well as IPv4, for the communications protocol that provides an identification and location system for computers on networks and routes traffic across the Internet. The routing of packets between networked systems may include Equal-cost multi-path routing (‘ECMP’), which is a routing strategy where next-hop packet forwarding to a single destination can occur over multiple “best paths” which tie for top place in routing metric calculations. Multi-path routing can be used in conjunction with most routing protocols, because it is a per-hop decision limited to a single router. The software may support Multi-tenancy, which is an architecture in which a single instance of a software application serves multiple customers. Each customer may be referred to as a tenant. Tenants may be given the ability to customize some parts of the application, but may not customize the application's code, in some embodiments. The embodiments may maintain audit logs. An audit log is a document that records an event in a computing system. In addition to documenting what resources were accessed, audit log entries typically include destination and source addresses, a timestamp, and user login information for compliance with various regulations. The embodiments may support various key management policies, such as encryption key rotation. In addition, the system may support dynamic root passwords or some variation dynamically changing passwords.

FIG.3Asets forth a diagram of a storage system306that is coupled for data communications with a cloud services provider302in accordance with some embodiments of the present disclosure. Although depicted in less detail, the storage system306depicted inFIG.3Amay be similar to the storage systems described above with reference toFIGS.1A-1DandFIGS.2A-2G. In some embodiments, the storage system306depicted inFIG.3Amay be embodied as a storage system that includes imbalanced active/active controllers, as a storage system that includes balanced active/active controllers, as a storage system that includes active/active controllers where less than all of each controller's resources are utilized such that each controller has reserve resources that may be used to support failover, as a storage system that includes fully active/active controllers, as a storage system that includes dataset-segregated controllers, as a storage system that includes dual-layer architectures with front-end controllers and back-end integrated storage controllers, as a storage system that includes scale-out clusters of dual-controller arrays, as well as combinations of such embodiments.

In the example depicted inFIG.3A, the storage system306is coupled to the cloud services provider302via a data communications link304. The data communications link304may be embodied as a dedicated data communications link, as a data communications pathway that is provided through the use of one or data communications networks such as a wide area network (‘WAN’) or local area network (‘LAN’), or as some other mechanism capable of transporting digital information between the storage system306and the cloud services provider302. Such a data communications link304may be fully wired, fully wireless, or some aggregation of wired and wireless data communications pathways. In such an example, digital information may be exchanged between the storage system306and the cloud services provider302via the data communications link304using one or more data communications protocols. For example, digital information may be exchanged between the storage system306and the cloud services provider302via the data communications link304using the handheld device transfer protocol (‘HDTP’), hypertext transfer protocol (‘HTTP’), internet protocol (‘IP’), real-time transfer protocol (‘RTP’), transmission control protocol (‘TCP’), user datagram protocol (‘UDP’), wireless application protocol (‘WAP’), or other protocol.

The cloud services provider302depicted inFIG.3Amay be embodied, for example, as a system and computing environment that provides services to users of the cloud services provider302through the sharing of computing resources via the data communications link304. The cloud services provider302may provide on-demand access to a shared pool of configurable computing resources such as computer networks, servers, storage, applications and services, and so on. The shared pool of configurable resources may be rapidly provisioned and released to a user of the cloud services provider302with minimal management effort. Generally, the user of the cloud services provider302is unaware of the exact computing resources utilized by the cloud services provider302to provide the services. Although in many cases such a cloud services provider302may be accessible via the Internet, readers of skill in the art will recognize that any system that abstracts the use of shared resources to provide services to a user through any data communications link may be considered a cloud services provider302.

In the example depicted inFIG.3A, the cloud services provider302may be configured to provide a variety of services to the storage system306and users of the storage system306through the implementation of various service models. For example, the cloud services provider302may be configured to provide services to the storage system306and users of the storage system306through the implementation of an infrastructure as a service (‘IaaS’) service model where the cloud services provider302offers computing infrastructure such as virtual machines and other resources as a service to subscribers. In addition, the cloud services provider302may be configured to provide services to the storage system306and users of the storage system306through the implementation of a platform as a service (‘PaaS’) service model where the cloud services provider302offers a development environment to application developers. Such a development environment may include, for example, an operating system, programming-language execution environment, database, web server, or other components that may be utilized by application developers to develop and run software solutions on a cloud platform. Furthermore, the cloud services provider302may be configured to provide services to the storage system306and users of the storage system306through the implementation of a software as a service (‘SaaS’) service model where the cloud services provider302offers application software, databases, as well as the platforms that are used to run the applications to the storage system306and users of the storage system306, providing the storage system306and users of the storage system306with on-demand software and eliminating the need to install and run the application on local computers, which may simplify maintenance and support of the application. The cloud services provider302may be further configured to provide services to the storage system306and users of the storage system306through the implementation of an authentication as a service (‘AaaS’) service model where the cloud services provider302offers authentication services that can be used to secure access to applications, data sources, or other resources. The cloud services provider302may also be configured to provide services to the storage system306and users of the storage system306through the implementation of a storage as a service model where the cloud services provider302offers access to its storage infrastructure for use by the storage system306and users of the storage system306. Readers will appreciate that the cloud services provider302may be configured to provide additional services to the storage system306and users of the storage system306through the implementation of additional service models, as the service models described above are included only for explanatory purposes and in no way represent a limitation of the services that may be offered by the cloud services provider302or a limitation as to the service models that may be implemented by the cloud services provider302.

In the example depicted inFIG.3A, the cloud services provider302may be embodied, for example, as a private cloud, as a public cloud, or as a combination of a private cloud and public cloud. In an embodiment in which the cloud services provider302is embodied as a private cloud, the cloud services provider302may be dedicated to providing services to a single organization rather than providing services to multiple organizations. In an embodiment where the cloud services provider302is embodied as a public cloud, the cloud services provider302may provide services to multiple organizations. Public cloud and private cloud deployment models may differ and may come with various advantages and disadvantages. For example, because a public cloud deployment involves the sharing of a computing infrastructure across different organization, such a deployment may not be ideal for organizations with security concerns, mission-critical workloads, uptime requirements demands, and so on. While a private cloud deployment can address some of these issues, a private cloud deployment may require on-premises staff to manage the private cloud. In still alternative embodiments, the cloud services provider302may be embodied as a mix of a private and public cloud services with a hybrid cloud deployment.

Although not explicitly depicted inFIG.3A, readers will appreciate that additional hardware components and additional software components may be necessary to facilitate the delivery of cloud services to the storage system306and users of the storage system306. For example, the storage system306may be coupled to (or even include) a cloud storage gateway. Such a cloud storage gateway may be embodied, for example, as hardware-based or software-based appliance that is located on premise with the storage system306. Such a cloud storage gateway may operate as a bridge between local applications that are executing on the storage array306and remote, cloud-based storage that is utilized by the storage array306. Through the use of a cloud storage gateway, organizations may move primary iSCSI or NAS to the cloud services provider302, thereby enabling the organization to save space on their on-premises storage systems. Such a cloud storage gateway may be configured to emulate a disk array, a block-based device, a file server, or other storage system that can translate the SCSI commands, file server commands, or other appropriate command into REST-space protocols that facilitate communications with the cloud services provider302.

In order to enable the storage system306and users of the storage system306to make use of the services provided by the cloud services provider302, a cloud migration process may take place during which data, applications, or other elements from an organization's local systems (or even from another cloud environment) are moved to the cloud services provider302. In order to successfully migrate data, applications, or other elements to the cloud services provider's302environment, middleware such as a cloud migration tool may be utilized to bridge gaps between the cloud services provider's302environment and an organization's environment. Such cloud migration tools may also be configured to address potentially high network costs and long transfer times associated with migrating large volumes of data to the cloud services provider302, as well as addressing security concerns associated with sensitive data to the cloud services provider302over data communications networks. In order to further enable the storage system306and users of the storage system306to make use of the services provided by the cloud services provider302, a cloud orchestrator may also be used to arrange and coordinate automated tasks in pursuit of creating a consolidated process or workflow. Such a cloud orchestrator may perform tasks such as configuring various components, whether those components are cloud components or on-premises components, as well as managing the interconnections between such components. The cloud orchestrator can simplify the inter-component communication and connections to ensure that links are correctly configured and maintained.

In the example depicted inFIG.3A, and as described briefly above, the cloud services provider302may be configured to provide services to the storage system306and users of the storage system306through the usage of a SaaS service model where the cloud services provider302offers application software, databases, as well as the platforms that are used to run the applications to the storage system306and users of the storage system306, providing the storage system306and users of the storage system306with on-demand software and eliminating the need to install and run the application on local computers, which may simplify maintenance and support of the application. Such applications may take many forms in accordance with various embodiments of the present disclosure. For example, the cloud services provider302may be configured to provide access to data analytics applications to the storage system306and users of the storage system306. Such data analytics applications may be configured, for example, to receive telemetry data phoned home by the storage system306. Such telemetry data may describe various operating characteristics of the storage system306and may be analyzed, for example, to determine the health of the storage system306, to identify workloads that are executing on the storage system306, to predict when the storage system306will run out of various resources, to recommend configuration changes, hardware or software upgrades, workflow migrations, or other actions that may improve the operation of the storage system306.

The cloud services provider302may also be configured to provide access to virtualized computing environments to the storage system306and users of the storage system306. Such virtualized computing environments may be embodied, for example, as a virtual machine or other virtualized computer hardware platforms, virtual storage devices, virtualized computer network resources, and so on. Examples of such virtualized environments can include virtual machines that are created to emulate an actual computer, virtualized desktop environments that separate a logical desktop from a physical machine, virtualized file systems that allow uniform access to different types of concrete file systems, and many others.

For further explanation,FIG.3Bsets forth a diagram of a storage system306in accordance with some embodiments of the present disclosure. Although depicted in less detail, the storage system306depicted inFIG.3Bmay be similar to the storage systems described above with reference toFIGS.1A-1DandFIGS.2A-2Gas the storage system may include many of the components described above.

The storage system306depicted inFIG.3Bmay include storage resources308, which may be embodied in many forms. For example, in some embodiments the storage resources308can include nano-RAM or another form of nonvolatile random access memory that utilizes carbon nanotubes deposited on a substrate. In some embodiments, the storage resources308may include 3D crosspoint non-volatile memory in which bit storage is based on a change of bulk resistance, in conjunction with a stackable cross-gridded data access array. In some embodiments, the storage resources308may include flash memory, including single-level cell (‘SLC’) NAND flash, multi-level cell (‘MLC’) NAND flash, triple-level cell (‘TLC’) NAND flash, quad-level cell (‘QLC’) NAND flash, and others. In some embodiments, the storage resources308may include non-volatile magnetoresistive random-access memory (‘MRAM’), including spin transfer torque (‘STT’) MRAM, in which data is stored through the use of magnetic storage elements. In some embodiments, the example storage resources308may include non-volatile phase-change memory (‘PCM’) that may have the ability to hold multiple bits in a single cell as cells can achieve a number of distinct intermediary states. In some embodiments, the storage resources308may include quantum memory that allows for the storage and retrieval of photonic quantum information. In some embodiments, the example storage resources308may include resistive random-access memory (‘ReRAM’) in which data is stored by changing the resistance across a dielectric solid-state material. In some embodiments, the storage resources308may include storage class memory (‘SCM’) in which solid-state nonvolatile memory may be manufactured at a high density using some combination of sub-lithographic patterning techniques, multiple bits per cell, multiple layers of devices, and so on. Readers will appreciate that other forms of computer memories and storage devices may be utilized by the storage systems described above, including DRAM, SRAM, EEPROM, universal memory, and many others. The storage resources308depicted inFIG.3Amay be embodied in a variety of form factors, including but not limited to, dual in-line memory modules (‘DIMMs’), non-volatile dual in-line memory modules (‘NVDIMMs’), M.2, U.2, and others.

The example storage system306depicted inFIG.3Bmay implement a variety of storage architectures. For example, storage systems in accordance with some embodiments of the present disclosure may utilize block storage where data is stored in blocks, and each block essentially acts as an individual hard drive. Storage systems in accordance with some embodiments of the present disclosure may utilize object storage, where data is managed as objects. Each object may include the data itself, a variable amount of metadata, and a globally unique identifier, where object storage can be implemented at multiple levels (e.g., device level, system level, interface level). Storage systems in accordance with some embodiments of the present disclosure utilize file storage in which data is stored in a hierarchical structure. Such data may be saved in files and folders, and presented to both the system storing it and the system retrieving it in the same format.

The example storage system306depicted inFIG.3Bmay be embodied as a storage system in which additional storage resources can be added through the use of a scale-up model, additional storage resources can be added through the use of a scale-out model, or through some combination thereof. In a scale-up model, additional storage may be added by adding additional storage devices. In a scale-out model, however, additional storage nodes may be added to a cluster of storage nodes, where such storage nodes can include additional processing resources, additional networking resources, and so on.

The storage system306depicted inFIG.3Balso includes communications resources310that may be useful in facilitating data communications between components within the storage system306, as well as data communications between the storage system306and computing devices that are outside of the storage system306. The communications resources310may be configured to utilize a variety of different protocols and data communication fabrics to facilitate data communications between components within the storage systems as well as computing devices that are outside of the storage system. For example, the communications resources310can include fibre channel (‘FC’) technologies such as FC fabrics and FC protocols that can transport SCSI commands over FC networks. The communications resources310can also include FC over ethernet (‘FCoE’) technologies through which FC frames are encapsulated and transmitted over Ethernet networks. The communications resources310can also include InfiniBand (‘IB’) technologies in which a switched fabric topology is utilized to facilitate transmissions between channel adapters. The communications resources310can also include NVM Express (‘NVMe’) technologies and NVMe over fabrics (‘NVMeoF’) technologies through which non-volatile storage media attached via a PCI express (‘PCIe’) bus may be accessed. The communications resources310can also include mechanisms for accessing storage resources308within the storage system306utilizing serial attached SCSI (‘SAS’), serial ATA (‘SATA’) bus interfaces for connecting storage resources308within the storage system306to host bus adapters within the storage system306, internet small computer systems interface (‘iSCSI’) technologies to provide block-level access to storage resources308within the storage system306, and other communications resources that that may be useful in facilitating data communications between components within the storage system306, as well as data communications between the storage system306and computing devices that are outside of the storage system306.

The storage system306depicted inFIG.3Balso includes processing resources312that may be useful in useful in executing computer program instructions and performing other computational tasks within the storage system306. The processing resources312may include one or more application-specific integrated circuits (‘ASICs’) that are customized for some particular purpose as well as one or more central processing units (‘CPUs’). The processing resources312may also include one or more digital signal processors (‘DSPs’), one or more field-programmable gate arrays (‘FPGAs’), one or more systems on a chip (‘SoCs’), or other form of processing resources312. The storage system306may utilize the storage resources312to perform a variety of tasks including, but not limited to, supporting the execution of software resources314that will be described in greater detail below.

The storage system306depicted inFIG.3Balso includes software resources314that, when executed by processing resources312within the storage system306, may perform various tasks. The software resources314may include, for example, one or more modules of computer program instructions that when executed by processing resources312within the storage system306are useful in carrying out various data protection techniques to preserve the integrity of data that is stored within the storage systems. Readers will appreciate that such data protection techniques may be carried out, for example, by system software executing on computer hardware within the storage system, by a cloud services provider, or in other ways. Such data protection techniques can include, for example, data archiving techniques that cause data that is no longer actively used to be moved to a separate storage device or separate storage system for long-term retention, data backup techniques through which data stored in the storage system may be copied and stored in a distinct location to avoid data loss in the event of equipment failure or some other form of catastrophe with the storage system, data replication techniques through which data stored in the storage system is replicated to another storage system such that the data may be accessible via multiple storage systems, data snapshotting techniques through which the state of data within the storage system is captured at various points in time, data and database cloning techniques through which duplicate copies of data and databases may be created, and other data protection techniques. Through the use of such data protection techniques, business continuity and disaster recovery objectives may be met as a failure of the storage system may not result in the loss of data stored in the storage system.

The software resources314may also include software that is useful in implementing software-defined storage (‘SDS’). In such an example, the software resources314may include one or more modules of computer program instructions that, when executed, are useful in policy-based provisioning and management of data storage that is independent of the underlying hardware. Such software resources314may be useful in implementing storage virtualization to separate the storage hardware from the software that manages the storage hardware.

The software resources314may also include software that is useful in facilitating and optimizing I/O operations that are directed to the storage resources308in the storage system306. For example, the software resources314may include software modules that perform carry out various data reduction techniques such as, for example, data compression, data deduplication, and others. The software resources314may include software modules that intelligently group together I/O operations to facilitate better usage of the underlying storage resource308, software modules that perform data migration operations to migrate from within a storage system, as well as software modules that perform other functions. Such software resources314may be embodied as one or more software containers or in many other ways.

Readers will appreciate that the various components depicted inFIG.3Bmay be grouped into one or more optimized computing packages as converged infrastructures. Such converged infrastructures may include pools of computers, storage and networking resources that can be shared by multiple applications and managed in a collective manner using policy-driven processes. Such converged infrastructures may minimize compatibility issues between various components within the storage system306while also reducing various costs associated with the establishment and operation of the storage system306. Such converged infrastructures may be implemented with a converged infrastructure reference architecture, with standalone appliances, with a software driven hyper-converged approach, or in other ways.

Readers will appreciate that the storage system306depicted inFIG.3Bmay be useful for supporting various types of software applications. For example, the storage system306may be useful in supporting artificial intelligence applications, database applications, DevOps projects, electronic design automation tools, event-driven software applications, high performance computing applications, simulation applications, high-speed data capture and analysis applications, machine learning applications, media production applications, media serving applications, picture archiving and communication systems (‘PACS’) applications, software development applications, and many other types of applications by providing storage resources to such applications.

The storage systems described above may operate to support a wide variety of applications. In view of the fact that the storage systems include compute resources, storage resources, and a wide variety of other resources, the storage systems may be well suited to support applications that are resource intensive such as, for example, artificial intelligence applications. Such artificial intelligence applications may enable devices to perceive their environment and take actions that maximize their chance of success at some goal. The storage systems described above may also be well suited to support other types of applications that are resource intensive such as, for example, machine learning applications. Machine learning applications may perform various types of data analysis to automate analytical model building. Using algorithms that iteratively learn from data, machine learning applications can enable computers to learn without being explicitly programmed.

In addition to the resources already described, the storage systems described above may also include graphics processing units (‘GPUs’), occasionally referred to as visual processing unit (‘VPUs’). Such GPUs may be embodied as specialized electronic circuits that rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. Such GPUs may be included within any of the computing devices that are part of the storage systems described above.

FIG.4illustrates a flow diagram for feature-based deduplication, in accordance with some implementations. The method400may be performed by processing logic that comprises hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (e.g., instructions run on a processing device to perform hardware simulation), or a combination thereof.

Referring toFIG.4, at block402, processing logic identifies, by a storage system controller (e.g., one or more storage systems controllers) associated with a plurality (e.g., one or more) of storage devices, a first content-dependent feature associated with a data sector. In one embodiment, the data sector is a fixed-length data sector. In another embodiment, the data sector is a variable-length data sector. The first content-dependent feature may be associated with the content of the data sector. In one embodiment, the data sector may correspond to an image object (e.g., a jpeg image file). In this embodiment, a content-dependent feature may be a characteristic (quality, feature, etc.) of the image itself, without consideration underlying image data. For example, content-dependent features of an image object may include objects, landscapes, animals, humans, etc. identified in the image. Content-dependent features of an image object may include lighting, composition, geographical location, color, etc. associated with the image. Content-dependent features may be different for various other classifications of data objects. For example, content-dependent features of an audio file may include tone, pitch, timing, etc. Generally, a content-dependent feature may include any characteristic that is specific to the classification (e.g., type) of data object in question.

At block404, processing logic determines, by the storage system controller, a baseline data sector associated with the data sector. In one embodiment, a baseline data sector is any data sector to which other data sectors of the same type (e.g., classification) may be compared. In one embodiment, to determine the baseline data sector, processing logic may identify405aa deduplicated data object associated with the data sector and assign405bthe deduplicated data object to be the baseline data sector. In another embodiment, processing logic may identify405ca snapshot data sector associated with the data sector and assign405dthe snapshot data sector to be the baseline data sector. Worth noting is that boxes405a-dofFIG.4are optional (as are all other boxes inFIG.4). In yet another embodiment, a mean-type algorithm (e.g., a m-mean algorithm) may be used to determine the baseline data sectors. Further details describing baseline data sectors and how they may be efficiently determined are explained with respect toFIGS.5-7.

At block406, processing logic determines, by the storage system controller, a content-dependent delta (e.g., difference) between the first content-dependent feature and a second content-dependent feature of the baseline data sector. In one embodiment, processing logic determines the second content-dependent feature. In another embodiment, the second content-dependent feature was recalculated and stored in the storage system for retrieval.

Processing logic may analyze the first data sector and the second data sector to determine content-dependent deltas between them. The content-dependent deltas may be stored in the storage system for future retrieval. In one example in which two images are compared, content-dependent deltas may include differences in objects pictured, geolocation, composition, etc. between the two images. In one embodiment, two images that include the same content but have slightly different compositions may be nearly identical visually, but the underlying image files corresponding to the two images may be more substantially different.

At block408, processing logic provides the content-dependent delta and an indicator to the baseline data sector (e.g., a pointer to the data sector) for storage on the plurality of storage devices. Advantageously, by determining content-dependent features of data sectors, and the differences between them, data sectors including minor content-dependent differences (with potentially large differences in the underlying data) may be efficiently deduplicated as described herein.

In another embodiment, processing logic may identify a plurality of data objects stored on a plurality of storage devices (e.g., embedded storage devices) and determine a content type of each of the plurality of data objects. Processing logic may identify a first subset of the plurality of data objects, where each data object of the first subset corresponds to a first content type. Processing logic may further determine a first centroid (e.g., a baseline data sector) corresponding to the first subset, wherein the first centroid is associated with the first subset of data objects. Processing logic may identify a first content-dependent feature of a first data object of the first subset and a corresponding second content-dependent feature of the first centroid. In one embodiment, the first content-dependent feature and the second content-dependent feature are dependent upon the first content type. In one embodiment, the first data object is a virtual machine image.

Processing logic may further determine a difference between the first content-dependent feature and the second content-dependent feature and deduplicate the first data object in view of the difference being less than or equal to a delta threshold. In one embodiment, it is advantageous to compare the difference to a threshold to determine the efficiency of the deduplication. In some embodiments (e.g., in which content-dependent differences are large) processing logic may determine, after comparing the difference to the threshold, that other methods of deduplication should be performed.

In one embodiment, to determine the first centroid corresponding to the first subset, processing logic may identify a deduplicated data object associated with the first subset and assign the deduplicated data object to be the first centroid. In another embodiment, processing logic may determine the first centroid using a mean-type algorithm. In yet another embodiment, processing logic may identify a snapshot data object associated with the first subset, and assign the snapshot data object to be the first centroid.

In one embodiment, processing logic may further receive a request to locate a second data object from the plurality of storage devices and determine based on metadata associated with the second object that the second data object corresponds to a second content type. Processing logic may search a second subset of data objects, where each data object of the second subset corresponds to the second content type, locate the second data object in the second subset, and provide the located second data object.

In one embodiment, processing logic may receive a second data object of a second content type to be stored to the plurality of storage devices, compare content-dependent features of the second data object to content-dependent features of a plurality of centroids of the second content type, and select a second centroid of the plurality of centroids based on the comparison. In one embodiment, the centroid that includes content-based features most similar to those of the second data object may be selected. In another embodiment, various other selection characteristics may be utilized. Processing logic may assign the second data object to the second centroid (e.g., based on the selection) and store an address and a delta between the content-dependent features of the second data object and the content-dependent features of the second centroid to the plurality of storage devices.

In another embodiment, processing logic may receive a request for a second data object from the plurality of storage devices, read metadata associated with the second data object, and determine, based on the metadata, a location of a second centroid associated with the second data object and a content-dependent delta between the second data object and the second centroid. Processing logic may generate the second data object by adding the content-dependent delta to the centroid and provide the generated second data object. In one embodiment, the first centroid and the second centroid may be located in two different levels of a tree-structure of the plurality of storage devices.

FIG.5is a first block diagram500showing example data sectors, in accordance with some implementations. In one embodiment, the data sectors correspond to virtual machine images. As shown by the data clusters of diagram500, sets of data sectors may be similar to each other (as shown by clusters502,504) and may be efficiently deduplicated by the operations described herein. In one embodiment, a storage system, such as the one described herein, may analyze existing data sectors (stored in the storage system or a different storage system), such as those shown inFIG.5, to determine how to efficiently deduplicate the data sectors.

FIG.6is a second block diagram showing deduplicated data sectors, in accordance with some implementations. As shown by the data clusters ofFIG.6, sets of data sectors may already be deduplicated in a storage system. The storage system may analyze already deduplicated data sectors to determine baseline data sectors, as described with respect toFIG.7. In one embodiment, it may be advantageous to select deduplicated data sectors to be baseline data sectors. Data sectors with the highest number of deduplicates (see602,604) may be good candidates for baseline data sectors.

FIG.7is a block diagram showing baseline data sectors, in accordance with some implementations. In one embodiment, baseline data sectors (e.g., centroids, as shown by the crosses inFIG.7) may be determined on a content-dependent delta proximity to neighboring data sectors. In one embodiment, a storage system may identify a deduplicated data object and assign the deduplicated data object to be a centroid, without performing additional calculations. In another embodiment, the storage system may determine a centroid using a mean-type algorithm (e.g., a k-mean algorithm or any other averaging algorithm). In yet another embodiment, the storage system may identify a snapshot data object (e.g., a virtual machine snapshot) and assign the snapshot data object to be the first centroid.

In one embodiment, the storage system may assign each data sector to a single, closest centroid. In one embodiment, clusters (e.g., sets) of data sectors are assigned to a single centroid based on an object type and/or a difference between content-dependent deltas of the data sectors and centroids. Advantageously, by determining centroids, the systems and operation described herein may provide efficient data deduplication where it was not before possible.