Patent Publication Number: US-11030090-B2

Title: Adaptive data migration

Description:
BACKGROUND 
     Solid-state memory, such as flash, is currently in use in solid-state drives (SSD) to augment or replace conventional hard disk drives (HDD), writable CD (compact disk) or writable DVD (digital versatile disk) drives, collectively known as spinning media, and tape drives, for storage of large amounts of data. Flash and other solid-state memories have characteristics that differ from spinning media. Yet, many solid-state drives are designed to conform to hard disk drive standards for compatibility reasons, which makes it difficult to provide enhanced features or take advantage of unique aspects of flash and other solid-state memory. Flash based arrays can be upgradeable. During these upgrades there may be a need to evacuate data from a shelf or migrate the data to a different shelf. It is within this context that the embodiments arise. 
     SUMMARY 
     In some embodiments, a method for elective garbage collection in storage memory, performed by a storage system is provided. The method includes monitoring storage space available in each of a plurality of portions of storage memory of a storage system and detecting an imbalance in the storage space available across the plurality of portions of storage memory. The method includes performing garbage collection to rebalance the space available across the plurality of portions of storage memory, responsive to the detecting. 
     In some embodiments, a storage system is provided. The storage system includes one or more processors and a plurality of portions of storage memory. The system includes a storage space detector, configurable to track storage space available in each of the plurality of portions of storage memory, and a garbage collection module, configurable to perform garbage collection so as to rebalance the storage space available across the plurality of portions of storage memory, responsive to identifying an imbalance across the plurality of portions of storage memory based on results from the storage space detector. 
     Other aspects and advantages of the embodiments will become apparent from the following detailed description taken in conjunction with the accompanying drawings which illustrate, by way of example, the principles of the described embodiments. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The described embodiments and the advantages thereof may best be understood by reference to the following description taken in conjunction with the accompanying drawings. These drawings in no way limit any changes in form and detail that may be made to the described embodiments by one skilled in the art without departing from the spirit and scope of the described embodiments. 
         FIG. 1  is a perspective view of a storage cluster with multiple storage nodes and internal storage coupled to each storage node to provide network attached storage, in accordance with some embodiments. 
         FIG. 2  is a block diagram showing an interconnect switch coupling multiple storage nodes in accordance with some embodiments. 
         FIG. 3  is a multiple level block diagram, showing contents of a storage node and contents of one of the non-volatile solid state storage units in accordance with some embodiments. 
         FIG. 4  shows a storage server environment, which may utilize the embodiments of the storage nodes and storage units of  FIGS. 1-3 . 
         FIG. 5  is a blade hardware block diagram, showing a control plane, compute and storage planes, and authorities interacting with underlying physical resources to perform distributed transactions, using embodiments of the storage nodes and storage units of  FIGS. 1-3  in the storage server environment of  FIG. 4  in accordance with some embodiments. 
         FIG. 6  is a block diagram of an embodiment of the space accounting logic shown in  FIG. 3  in accordance with some embodiments. 
         FIG. 7  is an action diagram depicting migration from a storage unit, along with an incoming workload, directed by the space accounting logic and an allocator in a storage node in accordance with some embodiments. 
         FIG. 8  is a flow diagram of a method for evacuating or migrating data from a write group in accordance with some embodiments. 
         FIG. 9  depicts the space detector and the garbage collection move module of  FIG. 6 , with two alternatives for garbage collection to rebalance an imbalance across the storage memory in accordance with some embodiments. 
         FIG. 10  is a flow diagram of a method for elective garbage collection in storage memory in accordance with some embodiments. 
         FIG. 11  is an illustration showing an exemplary computing device which may implement the embodiments described herein. 
     
    
    
     DETAILED DESCRIPTION 
     Various storage systems described herein, and further storage systems, can be optimized for distribution of selected data, according to various criteria, in flash or other solid-state memory. The embodiments below provide for an upgradeable flash/solid state drive storage system. Upon an upgrade to the system, the data from a storage shelf may be required to be migrated to another shelf. The embodiments provide for a system and method that considers the space or storage capacity in the system and the ability to adaptively and/or dynamically adjust between differing migration techniques based on the monitoring of the space or storage capacity of the system. Principles of operation, variations, and implementation details for the adaptive migration of data for a rebuild operation or an upgrade of the system according to the available space in the system are provided below. 
     The embodiments below describe 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, 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 is 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 Peripheral Component Interconnect (PCI) Express, 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. 
     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, dynamic random access memory (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 central processing unit (CPU), solid state storage controller, and a quantity of solid state mass storage, e.g., between 2-32 terabytes (TB) or more 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. 1  is a perspective view of a storage cluster  160 , with multiple storage nodes  150  and 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 clusters  160 , each having one or more storage nodes  150 , in a flexible and reconfigurable arrangement of both the physical components and the amount of storage memory provided thereby. The storage cluster  160  is 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 cluster  160  has a chassis  138  having multiple slots  142 . It should be appreciated that chassis  138  may be referred to as a housing, enclosure, or rack unit. In one embodiment, the chassis  138  has fourteen slots  142 , 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 slot  142  can accommodate one storage node  150  in some embodiments. Chassis  138  includes flaps  148  that can be utilized to mount the chassis  138  on a rack. Fans  144  provide air circulation for cooling of the storage nodes  150  and components thereof, although other cooling components could be used, or an embodiment could be devised without cooling components. A switch fabric  146  couples storage nodes  150  within chassis  138  together and to a network for communication to the memory. In an embodiment depicted in  FIG. 1 , the slots  142  to the left of the switch fabric  146  and fans  144  are shown occupied by storage nodes  150 , while the slots  142  to the right of the switch fabric  146  and fans  144  are empty and available for insertion of storage node  150  for illustrative purposes. This configuration is one example, and one or more storage nodes  150  could occupy the slots  142  in various further arrangements. The storage node arrangements need not be sequential or adjacent in some embodiments. Storage nodes  150  are hot pluggable, meaning that a storage node  150  can be inserted into a slot  142  in the chassis  138 , or removed from a slot  142 , without stopping or powering down the system. Upon insertion or removal of storage node  150  from slot  142 , 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 node  150  can have multiple components. In the embodiment shown here, the storage node  150  includes a printed circuit board  158  populated by a CPU  156 , i.e., processor, a memory  154  coupled to the CPU  156 , and a non-volatile solid state storage  152  coupled to the CPU  156 , although other mountings and/or components could be used in further embodiments. The memory  154  has instructions which are executed by the CPU  156  and/or data operated on by the CPU  156 . As further explained below, the non-volatile solid state storage  152  includes flash or, in further embodiments, other types of solid-state memory. 
     Referring to  FIG. 1 , storage cluster  160  is scalable, meaning that storage capacity with non-uniform storage sizes is readily added, as described above. One or more storage nodes  150  can be plugged into or removed from each chassis and the storage cluster self-configures in some embodiments. Plug-in storage nodes  150 , whether installed in a chassis as delivered or later added, can have different sizes. For example, in one embodiment a storage node  150  can have any multiple of 4 TB, e.g., 8 TB, 12 TB, 16 TB, 32 TB, etc. In further embodiments, a storage node  150  could have any multiple of other storage amounts or capacities. Storage capacity of each storage node  150  is 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 units  152  or storage nodes  150  within the chassis. 
       FIG. 2  is a block diagram showing a communications interconnect  170  and power distribution bus  172  coupling multiple storage nodes  150 . Referring back to  FIG. 1 , the communications interconnect  170  can be included in or implemented with the switch fabric  146  in some embodiments. Where multiple storage clusters  160  occupy a rack, the communications interconnect  170  can be included in or implemented with a top of rack switch, in some embodiments. As illustrated in  FIG. 2 , storage cluster  160  is enclosed within a single chassis  138 . External port  176  is coupled to storage nodes  150  through communications interconnect  170 , while external port  174  is coupled directly to a storage node. External power port  178  is coupled to power distribution bus  172 . Storage nodes  150  may include varying amounts and differing capacities of non-volatile solid state storage  152  as described with reference to  FIG. 1 . In addition, one or more storage nodes  150  may be a compute only storage node as illustrated in  FIG. 2 . Authorities  168  are implemented on the non-volatile solid state storages  152 , for example as lists or other data structures stored in memory. In some embodiments the authorities are stored within the non-volatile solid state storage  152  and supported by software executing on a controller or other processor of the non-volatile solid state storage  152 . In a further embodiment, authorities  168  are implemented on the storage nodes  150 , for example as lists or other data structures stored in the memory  154  and supported by software executing on the CPU  156  of the storage node  150 . Authorities  168  control how and where data is stored in the non-volatile solid state storages  152  in some embodiments. This control assists in determining which type of erasure coding scheme is applied to the data, and which storage nodes  150  have which portions of the data. Each authority  168  may be assigned to a non-volatile solid state storage  152 . 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 nodes  150 , or by the non-volatile solid state storage  152 , 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 authorities  168 . Authorities  168  have a relationship to storage nodes  150  and non-volatile solid state storage  152  in some embodiments. Each authority  168 , covering a range of data segment numbers or other identifiers of the data, may be assigned to a specific non-volatile solid state storage  152 . In some embodiments the authorities  168  for all of such ranges are distributed over the non-volatile solid state storages  152  of a storage cluster. Each storage node  150  has a network port that provides access to the non-volatile solid state storage(s)  152  of that storage node  150 . 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 authorities  168  thus establishes an indirection to data. Indirection may be referred to as the ability to reference data indirectly, in this case via an authority  168 , in accordance with some embodiments. A segment identifies a set of non-volatile solid state storage  152  and a local identifier into the set of non-volatile solid state storage  152  that 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 storage  152  are applied to locating data for writing to or reading from the non-volatile solid state storage  152  (in the form of a RAID stripe). Data is striped across multiple units of non-volatile solid state storage  152 , which may include or be different from the non-volatile solid state storage  152  having the authority  168  for 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 authority  168  for that data segment should be consulted, at that non-volatile solid state storage  152  or storage node  150  having that authority  168 . 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 storage  152  having the authority  168  for 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 storage  152 , 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 storage  152  having that authority  168 . 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 storage  152  for an authority in the presence of a set of non-volatile solid state storage  152  that are reachable and constitute the same cluster. The calculation also determines an ordered set of peer non-volatile solid state storage  152  that 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. 
     With reference to  FIGS. 1 and 2 , two of the many tasks of the CPU  156  on a storage node  150  are to break up write data, and reassemble read data. When the system has determined that data is to be written, the authority  168  for 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 storage  152  currently determined to be the host of the authority  168  determined from the segment. The host CPU  156  of the storage node  150 , on which the non-volatile solid state storage  152  and corresponding authority  168  reside, then breaks up or shards the data and transmits the data out to various non-volatile solid state storage  152 . 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 authority  168  for the segment ID containing the data is located as described above. The host CPU  156  of the storage node  150  on which the non-volatile solid state storage  152  and corresponding authority  168  reside 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 CPU  156  of storage node  150  then 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 storage  152 . In some embodiments, the segment host requests the data be sent to storage node  150  by 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 metadata, 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 storage  152  coupled to the host CPUs  156  (See  FIG. 5 ) 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. Modes 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. 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 unit  152  may be assigned a range of address space. Within this assigned range, the non-volatile solid state storage  152  is able to allocate addresses without synchronization with other non-volatile solid state storage  152 . 
     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. 
     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. 3  is a multiple level block diagram, showing contents of a storage node  150  and contents of a non-volatile solid state storage  152  of the storage node  150 . Data is communicated to and from the storage node  150  by a network interface controller (NIC)  202  in some embodiments. Each storage node  150  has a CPU  156 , and one or more non-volatile solid state storage  152 , as discussed above. CPU  156  includes space accounting logic  301 . Space accounting logic may be embodied as a software module that monitors space used in the system and provides attributes for compression/volumes for the data in the system. In some embodiments, space accounting logic  301  includes a space detector that detects imbalances through the evaluation/monitoring of write groups and initiating an event when an imbalance is detected as described in more detail below. Moving down one level in  FIG. 3 , each non-volatile solid state storage  152  has a relatively fast non-volatile solid state memory, such as nonvolatile random access memory (NVRAM)  204 , and flash memory  206 . In some embodiments, NVRAM  204  may 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 in  FIG. 3 , the NVRAM  204  is implemented in one embodiment as high speed volatile memory, such as dynamic random access memory (DRAM)  216 , backed up by energy reserve  218 . Energy reserve  218  provides sufficient electrical power to keep the DRAM  216  powered long enough for contents to be transferred to the flash memory  206  in the event of power failure. In some embodiments, energy reserve  218  is a capacitor, super-capacitor, battery, or other device, that supplies a suitable supply of energy sufficient to enable the transfer of the contents of DRAM  216  to a stable storage medium in the case of power loss. The flash memory  206  is implemented as multiple flash dies  222 , which may be referred to as packages of flash dies  222  or an array of flash dies  222 . It should be appreciated that the flash dies  222  could 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 storage  152  has a controller  212  or other processor, and an input output (I/O) port  210  coupled to the controller  212 . I/O port  210  is coupled to the CPU  156  and/or the network interface controller  202  of the flash storage node  150 . Flash input output (I/O) port  220  is coupled to the flash dies  222 , and a direct memory access unit (DMA)  214  is coupled to the controller  212 , the DRAM  216  and the flash dies  222 . In the embodiment shown, the I/O port  210 , controller  212 , DMA unit  214  and flash I/O port  220  are implemented on a programmable logic device (PLD)  208 , e.g., a field programmable gate array (FPGA). In this embodiment, each flash die  222  has pages, organized as sixteen kB (kilobyte) pages  224 , and a register  226  through which data can be written to or read from the flash die  222 . In further embodiments, other types of solid-state memory are used in place of, or in addition to flash memory illustrated within flash die  222 . 
     Storage clusters  160 , in various embodiments as disclosed herein, can be contrasted with storage arrays in general. The storage nodes  150  are part of a collection that creates the storage cluster  160 . Each storage node  150  owns a slice of data and computing required to provide the data. Multiple storage nodes  150  cooperate 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 units  152  described herein have multiple interfaces active simultaneously and serving multiple purposes. In some embodiments, some of the functionality of a storage node  150  is shifted into a storage unit  152 , transforming the storage unit  152  into a combination of storage unit  152  and storage node  150 . Placing computing (relative to storage data) into the storage unit  152  places 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 cluster  160 , as described herein, multiple controllers in multiple storage units  152  and/or storage nodes  150  cooperate 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. 4  shows a storage server environment, which uses embodiments of the storage nodes  150  and storage units  152  of  FIGS. 1-3 . In this version, each storage unit  152  has a processor such as controller  212  (see  FIG. 3 ), an FPGA (field programmable gate array), flash memory  206 , and NVRAM  204  (which may be super-capacitor backed DRAM  216 , see  FIG. 3 ) on a PCIe (peripheral component interconnect express) board in a chassis  138  (see  FIG. 1 ). The storage unit  152  may 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 units  152  may 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 NVRAM  204  is a contiguous block of reserved memory in the storage unit  152  DRAM  216 , and is backed by NAND flash. NVRAM  204  is logically divided into multiple memory regions written to as spools (e.g., spool_region). Space within the NVRAM  204  spools is managed by each authority  512  independently. Each device provides an amount of storage space to each authority  512 . That authority  512  further manages lifetimes and allocations within that space. Examples of a spool include distributed transactions or notions. When the primary power to a storage unit  152  fails, onboard super-capacitors provide a short duration of power hold up. During this holdup interval, the contents of the NVRAM  204  are flushed to flash memory  206 . On the next power-on, the contents of the NVRAM  204  are recovered from the flash memory  206 . 
     As for the storage unit controller, the responsibility of the logical “controller” is distributed across each of the blades containing authorities  512 . This distribution of logical control is shown in  FIG. 4  as a host controller  402 , mid-tier controller  404  and storage unit controller(s)  406 . Management of the control plane and the storage plane are treated independently, although parts may be physically co-located on the same blade. Each authority  512  effectively serves as an independent controller. Each authority  512  provides its own data and metadata structures, its own background workers, and maintains its own lifecycle. 
       FIG. 5  is a blade  502  hardware block diagram, showing a control plane  504 , compute and storage planes  506 ,  508 , and authorities  512  interacting with underlying physical resources to perform distributed transactions, using embodiments of the storage nodes  150  and storage units  152  of  FIGS. 1-3  in the storage server environment of  FIG. 4 . The control plane  504  is partitioned into a number of authorities  512  which can use the compute resources in the compute plane  506  to run on any of the blades  502 . The storage plane  508  is partitioned into a set of devices, each of which provides access to flash  206  and NVRAM  204  resources. In the compute and storage planes  506 ,  508  of  FIG. 5 , the authorities  512  interact with the underlying physical resources (i.e., devices). From the point of view of an authority  512 , its resources are striped over all of the physical devices. From the point of view of a device, it provides resources to all authorities  512 , irrespective of where the authorities happen to run. In order to communicate and represent the ownership of an authority  402 , including the right to record persistent changes on behalf of that authority  402 , the authority  402  provides some evidence of authority ownership that can be independently verifiable. A token is employed for this purpose and function in one embodiment, although other techniques are readily devised. 
     Still referring to  FIG. 5 , each authority  512  has allocated or has been allocated one or more partitions  510  of storage memory in the storage units  152 , e.g. partitions  510  in flash memory  206  and NVRAM  204 . Each authority  512  uses those allocated partitions  510  that 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 authority  512  could have a larger number of partitions  510  or larger sized partitions  510  in one or more storage units  152  than one or more other authorities  512 . The above-described storage systems and storage clusters, and variations thereof, and various further storage systems and storage clusters are suitable for the mechanism for rebuilding/evacuating data and as the migration of the data occurs the method is capable of dynamically or adaptively selecting mechanism for the migration based on monitoring space availability/usage for the system, as described below. It should be appreciated that, although described with flash memory, the teachings herein are applicable to other types of solid-state memory and other types of storage memory. 
     Migration of data from one failure domain, which may be referred to as a write group, in a flash array involves considering a number of factors: 
     a) Space available in the entire array, 
     Blindly migrating data (in the presence of more incoming data) can fill the array beyond comfortable limits, causing undue garbage collection pressure and other performance anomalies. 
     b) Balancing space available in individual failure domains. As noted above a failure domain may be referred to as a write group in some embodiments. 
     An imbalanced migration can cause some write groups to be fuller than other write groups, causing performance hotspots for reads. Write hotspots can also be created due to the allocator preferring some write groups over other. 
     c) Efficiency of migration. 
     Migrated data (depending on the method chosen) may migrate dead/overwritten data in addition to live data. 
     The embodiments provide a write group space aware mechanism, write group balanced migration. Migration typically has two methods available: 
     RAID rebuild. This mechanism copies bits over, and includes live as well as overwritten data. No space efficiency is achieved, however the operation is faster, as it does not involve testing the data for liveness while migrating and the amount of data written out is potentially smaller than in the GC move method. Since rebuild cannot change the structure/geometry of segments, target write groups for this data can only be the same or larger write groups. 
     GC (garbage collection) move. This mechanism analyses the data, cross referencing it with system metadata for check of liveness, and then picking up and recomposing the live-only data into new segments. This is more space efficient as a GC move will only migrate live data, but is more expensive in terms of central processing unit (CPU)/dynamic random access memory (DRAM) resources. Since entire new segments are composed, the target write. 
     9 can be any (even smaller) write groups that are chosen by the system allocator. That is, deduplication is integrated into the migration mechanism with the inclusion of a GC move. It should be appreciated that while the embodiments include the above two migration mechanisms, other migration techniques or mechanisms may be integrated with the embodiments, as the embodiments are not limited to the above two techniques. 
     In a system composed of write groups of different sizes, the migration proceeds as follows: 
     1. Start off by using rebuild (favor performance over space efficiency). 
     2. As migration proceeds, compatible write groups will get fuller more quickly than incompatible write groups. A space monitoring module signals imbalance in space usage of the write groups. 
     3. Migration reacts to the imbalance signal, by switching some segment migration using GC. If the signal persists, a majority (up to 100%) of the migrated segments may move over to using the GC method. 
     4. At any time, if the space usage of the entire array approaches a set threshold, migration just stalls, until the array is empty enough to proceed. 
     5. Also, at any time, GC method kicks in if space of the entire array goes above a soft threshold. 
     An aspect of this migration is that it considers side effects due to varying incoming workloads automatically. An incoming workload can: 
     Help restore balance from imbalance: New writes are assigned the emptiest write groups by an allocator, helping to restore balanced write groups. 
     Triggering space efficient migration by introducing imbalance: Sudden workloads will cause an imbalance, causing migration to tilt towards space efficient GC, attempting to restore balance. 
       FIG. 6  is a block diagram of an embodiment of the space accounting logic  301  shown in  FIG. 3 . Space accounting logic  301  could be implemented in hardware, firmware, software executing on a processor, or combination thereof, in a storage system, for example a high-availability controller-based storage system, or in a storage cluster, for example in a storage node  150 , or across storage nodes  150  as distributed software or logic. Further embodiments in various types of storage systems, including storage arrays in storage clusters, are readily devised in keeping with the teachings herein. In some embodiments, each of the storage nodes  150  of a storage cluster  160  has space accounting logic  301 . A space detector  602  monitors memory space, more specifically the amount of storage memory in blades, storage nodes  150  or storage units  152 , solid-state drives or other storage devices, etc., or the entire system, that is occupied by data or is available for writing data. In various embodiments, the space accounting logic  301  could count or determine erased blocks, written blocks, written pages or total amount of data written to a storage unit  152 , for example using one or more counters, score boarding, or other data structure and tracking erasures and writing, or by directly detecting blocks that have no written data. In some embodiments, the space accounting logic  301  can track write groups, for example by failure domain. For example, the space accounting logic  301  could report on storage usage as a percentage of size of write groups, space utilization from fullest to emptiest write group or failure domain, or other aspects of storage space utilization and availability. 
     Still referring to  FIG. 6 , a migration enable module  604  in the space accounting logic  301  is coupled to the space detector  602 , and determines whether migration should proceed with a RAID rebuild, as directed by a RAID rebuild module  606 , or by a garbage collection move, as directed by a garbage collection move module  608 . This decision is symbolized in  FIG. 6  by a switch, which could be implemented as a software decision, or in hardware or firmware. 
       FIG. 7  is an action diagram depicting migration from a storage unit  152 , along with an incoming workload  704 , directed by the space accounting logic  301  and an allocator  702  in a storage node  150 . In the scenario shown here, the middle storage unit  152  is being evacuated, for example to free up the storage unit  152  for replacement or upgrade. Data is being migrated out of the storage unit  152 , along a migration path  706  to another storage unit  152 . An alternate migration path  708  is shown in dashed lines. Other evacuation and migration scenarios are readily developed in keeping with the teachings herein. 
     As depicted in  FIG. 7 , the space accounting logic  301  monitors the space usage of multiple write groups or failure domains in the storage units  152 . This is performed using the space detector  602  shown in  FIG. 6 . Initially, the migration enable module  604  in the space accounting logic  301  selects the RAID rebuild module  606 , and directs a migration using RAID rebuild. Based on the fullness of the compatible write groups versus incompatible write groups, the migration can dynamically or adaptively switch to garbage collection move, as directed by the migration enable module  604  using the garbage collection move module  608 . For example, if the compatible write groups become more full than the incompatible write groups, the migration enable module  604  could direct a garbage collection move. This could be done with a percentage of the moves of the migration, or all of the moves of the migration, in various embodiments. In some embodiments, the percentage of the moves of the migration that are directed to a garbage collection move is a variable percentage, based on the relative amount of fullness of the compatible write groups in comparison with the fullness of the incompatible write groups. In some embodiments, there is a threshold, and all of the moves are switched from RAID rebuild to garbage collection move once the threshold is exceeded. Also, if the space of the entire array is above a threshold, in some embodiments, the migration switches to garbage collection move. In some embodiments, if the space usage of the entire storage system reaches a threshold, migration is stalled until the array is empty enough to proceed (i.e., the space usage drops below the threshold). In some embodiments, hysteresis is used for one or more thresholds. 
     Still referring to  FIG. 7 , the storage node  150  distributes writes from the incoming workload  704  in accordance with an allocator  702 . The allocator  702 , in some embodiments, assigns new writes to the emptiest write groups, which helps to restore balanced write groups. During a migration, the system can switch back and forth between RAID rebuild and garbage collection move for the migration, to restore or maintain balance between compatible write groups and incompatible write groups. As noted above, other migration techniques may be integrated with the embodiments. 
     In one embodiment, the storage system uses remapping to change addressing and point future writes to the portion of storage space that has more space available. This acts to rebalance the system by preferentially filling up the newly added blade or storage unit, or recently evacuated storage memory range with more available space, more rapidly than the blades, storage units, or other portions of storage memory with less storage space available. In various embodiments, the allocator  702  performs the remapping, or directs or otherwise cooperates with a remapping module. 
       FIG. 8  is a flow diagram of a method for evacuating or migrating data from a write group. The method can be practiced by a storage node and storage units of a storage cluster as described herein, in various embodiments. Also, the method can be practiced by a processor in a storage system. In an action  802 , a migration is started from a first write group of a failure domain in a storage system to a second write group, using RAID rebuild. In an action  804 , space usage of write groups is monitored. In a determination action  806 , it is determined whether compatible write groups are more full than incompatible write groups. In further embodiments some other threshold could be applied to this determination. If the answer in the determination action  806  is no, the migration is continued using RAID rebuild, in the action  808 . If the answer in the determination action  806  is yes, the migration is switched to using garbage collection move, in the action  810 . 
     Both of the actions  808 ,  810  rejoin the flow at the decision action  812 , where it is determined whether the space usage of the storage system is below a threshold. If the answer to the determination action  812  is yes, the space usage is below threshold, flow continues with the action  816 . If the answer to the decision action  812  is no, the space usage is not below the threshold (i.e., the space usage is at or above the threshold), the migration is stalled in the action  814 . Both of the actions  812 ,  814  rejoin the flow at the decision action  816 , in which it is determined whether there are new writes from an incoming workload. If not, flow proceeds back to the action  804 , to continue monitoring space usage of write groups. If there are new writes from the incoming workload, flow proceeds to the action  818 , in which the allocator assigns new writes to the emptiest write groups. Flow loops back to the action  804 , to continue monitoring space usage of write groups. 
     In variations of this flow, decision actions could be performed in different orders or combined. In a further variation, the portions of the migration could be continued using RAID rebuild while other portions continue using migration, proportional to or otherwise determined by a ratio or comparison of the fullness of compatible write groups relative to incompatible write groups. Thus, the mechanism can be employed in a dynamic and/or adaptive manner in some embodiments. It should be appreciated that the embodiments through the inclusion of the garbage collection move integrate and improve deduplication through the elimination of overwritten data. 
     It should be appreciated that garbage collection is used to distribute data evenly in a storage system, such as a storage array or storage cluster. Garbage collection involves reading live data and rewriting the data, then reclaiming storage memory that has dead data by erasing those parts of storage memory. The act of rewriting the data, in garbage collection, spreads the data throughout the storage system, for example as data stripes. Space pressure, based on detecting that the overall amount of available storage space is low, triggers garbage collection. Adding additional storage to alleviate space pressure, such as more storage in a storage array or storage cluster, can create hotspots as new data to be written is preferentially written to the added storage. Adding additional storage can also create a situation where the new storage is underutilized since the data striping relies on segments distributed across existing storage and the new storage, and the existing storage isn&#39;t seen by the system as having enough extra space to support added data stripes that use existing storage and the new storage. Adding the additional storage decreases space pressure, as the system detects that there is now more available storage space and does not trigger garbage collection. The two issues can be summarized as 1) adding additional storage doesn&#39;t necessarily improve system performance and may actually decrease system performance with the production of hotspots, and 2) adding additional storage doesn&#39;t necessarily increase total system storage space, since the added storage is underutilized in some storage systems. The new or additional storage space can be over utilized or underutilized, in either case creating problems. 
     One solution to the above mentioned issues is upon detecting addition of storage memory, e.g., insertion of a storage blade in a storage cluster, or added storage memory in a storage array, the system declares that the existing storage memory is entirely full of candidate memory for garbage collection, i.e., is full of garbage, and turns on garbage collection. A second solution is that the system tracks balance and imbalance of portions of storage memory in terms of amount of storage memory used versus amount of storage memory available, for example across blades, write groups, storage packs, solid-state drives, etc., upon detecting addition of storage memory, for example insertion of a blade to a storage cluster or addition of a storage pack, storage group or storage drive to a storage array, the system declares that imbalance has occurred, and triggers garbage collection. Garbage collection continues until the imbalance is corrected, for example until storage memory is evenly filled to within a threshold. In both of the above mentioned solutions, the storage system benefits from garbage collection, in terms of recovering storage memory space, benefits for data retention because the data is rewritten, and benefits by distributing data across a larger span of storage memory, including the newly added storage memory. 
     With reference back to  FIG. 6 , there is a depiction of space accounting logic  301 , including a space detector  602 , a migration enable module  604 , a RAID rebuild module  606 , and a garbage collection move module  608 . The space accounting logic  301  or portions thereof can be used in implementing one or both of the above solutions. In the first solution, the system could write to the space detector  602 , for example with a message or by writing to a parameter in memory, to declare that the existing storage memory is full of garbage. The migration enable module  604  responds to this declaration in the space detector  602 , and switches on the garbage collection move module  608 . This performs garbage collection over the entire existing storage memory, recovering memory to use along with the newly inserted storage blade  502 . With this as a background operation, regular reading and writing operations can continue without disruption. 
     With reference back to  FIG. 7 , the space accounting logic  301  is depicted monitoring space usage, for example of write groups, or the entire array relative to a threshold, of one storage unit  152  versus others, or even of a storage node  150  in comparison to other storage nodes  150 . When imbalance is detected, the space accounting logic  301  switches from RAID rebuilds to garbage collection move. In some embodiments, this is a variable amount of RAID rebuilds and garbage collection move, which could be proportional to the amount of balance or imbalance in the system. This mechanism is useful in implementing the second solution, where addition of a blade  502  to the storage cluster  160 , or addition of a storage unit  152  or a storage pack, storage group or storage drive causes the space accounting logic to detect imbalance of storage memory used versus memory available. This triggers a data migration using garbage collection move. In some embodiments, this is switched back and forth between garbage collection move and RAID rebuild, and in other embodiments this is varied between garbage collection move and RAID rebuild. 
       FIG. 9  depicts the space detector  602  and the garbage collection move module  608  of  FIG. 6 , with two alternatives for garbage collection to rebalance an imbalance across the storage memory in accordance with some embodiments. In these scenarios, the circled  1  shows an empty storage memory  906  in the storage system. For example, the empty storage memory  906  has been added to the storage system, by adding a blade  502  or a storage unit  152 , or a blade  502  or storage unit  152  has been evacuated. The circled  2  shows detection of an imbalance across the storage memory. The space detector  602  detects the imbalance, and the garbage collection move module  608  decides to perform garbage collection to migrate data from candidate storage memory  904  for garbage collection to the target storage memory, the empty storage memory  906 . The circled  3  shows two alternatives for how garbage collection can be performed. In one version, garbage collection reads live data and stripes the live data across the storage cluster or the storage array. This is followed by circled  4 , in which the storage memory is recovered from the dead data and the erased portions of storage memory, for example by block erases of the dead data and left behind live data that has already been copied and migrated to the target memory. In the alternative version, garbage collection makes a byte for byte copy from candidate storage memory  904  to target storage memory. This is likewise followed by circled  4 , to recover storage memory as above. It should be appreciated that both versions of garbage collection migrate data from more full portions of storage memory, and recover storage memory there, to more empty portions of storage memory, thereby rebalancing the storage memory. 
       FIG. 10  is a flow diagram of a method for elective garbage collection in storage memory in accordance with some embodiments. The method is performed by embodiments of the storage system described herein, more specifically by one or more processors in a storage system. In an action  1002 , storage space available is monitored. For example, space accounting logic could monitor storage space in each of the storage nodes, storage units or blades in a storage cluster. In a determination action  1004 , the question is asked, is there an imbalance? Storage space used or available in each of the storage nodes, storage units or blades in a storage cluster could be compared, and if a difference from one of these to another, or from one to the group average, etc., meets a threshold, an imbalance could be declared. If there is no imbalance, flow branches back to the action  1002 , in order to continue monitoring storage space available. If there is an imbalance, flow branches to the action  1006 . In the action  1006 , garbage collection is performed to rebalance storage space available. 
     Garbage collection could copy live data only, or could perform a byte for byte copy (i.e., copy live and dead data indiscriminately, one byte after another), from a candidate storage memory to a target storage memory that has more storage space available than the candidate storage memory. Garbage collection recovers storage memory, erasing former live data that has been copied from the candidate storage memory and migrated to the target storage memory and also erasing dead data, usually in block erases. The combination of triggering garbage collection when imbalance is detected, and targeting the migration of data with garbage collection, rebalances the storage memory. 
     It should be appreciated that the methods described herein may be performed with a digital processing system, such as a conventional, general-purpose computer system. Special purpose computers, which are designed or programmed to perform only one function may be used in the alternative.  FIG. 11  is an illustration showing an exemplary computing device which may implement the embodiments described herein. The computing device  1100  of  FIG. 11  may be used to perform embodiments of the functionality for an external processor (i.e., external to the flash controller) or the multithreaded/virtualized microcode sequence engine (internal to the flash controller) in accordance with some embodiments. The computing device includes a central processing unit (CPU)  1101 , which is coupled through a bus  1105  to a memory  1103 , and mass storage device  1107 . Mass storage device  1107  represents a persistent data storage device such as a disc drive, which may be local or remote in some embodiments. The mass storage device  1107  could implement a backup storage, in some embodiments. Memory  1103  may include read only memory, random access memory, etc. Applications resident on the computing device may be stored on or accessed via a computer readable medium such as memory  1103  or mass storage device  1107  in some embodiments. Applications may also be in the form of modulated electronic signals modulated accessed via a network modem or other network interface of the computing device. It should be appreciated that CPU  1101  may be embodied in a general-purpose processor, a special purpose processor, or a specially programmed logic device in some embodiments. 
     Display  1111  is in communication with CPU  1101 , memory  1103 , and mass storage device  1107 , through bus  1105 . Display  1111  is configured to display any visualization tools or reports associated with the system described herein. Input/output device  1109  is coupled to bus  1105  in order to communicate information in command selections to CPU  1101 . It should be appreciated that data to and from external devices may be communicated through the input/output device  1109 . CPU  1101  can be defined to execute the functionality described herein to enable the functionality described with reference to  FIGS. 1-10 . The code embodying this functionality may be stored within memory  1103  or mass storage device  1107  for execution by a processor such as CPU  1101  in some embodiments. The operating system on the computing device may be MS-WINDOWS™, UNIX™, LINUX™, iOS™, CentOS™, Android™, Redhat Linux™, z/OS™, or other known operating systems. It should be appreciated that the embodiments described herein may also be integrated with a virtualized computing system implemented with physical computing resources. 
     Detailed illustrative embodiments are disclosed herein. However, specific functional details disclosed herein are merely representative for purposes of describing embodiments. Embodiments may, however, be embodied in many alternate forms and should not be construed as limited to only the embodiments set forth herein. 
     It should be understood that although the terms first, second, etc. may be used herein to describe various steps or calculations, these steps or calculations should not be limited by these terms. These terms are only used to distinguish one step or calculation from another. For example, a first calculation could be termed a second calculation, and, similarly, a second step could be termed a first step, without departing from the scope of this disclosure. As used herein, the term “and/or” and the “/” symbol includes any and all combinations of one or more of the associated listed items. 
     As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises”, “comprising”, “includes”, and/or “including”, when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Therefore, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. 
     It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may in fact be executed substantially concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved. 
     With the above embodiments in mind, it should be understood that the embodiments might employ various computer-implemented operations involving data stored in computer systems. These operations are those requiring physical manipulation of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. Further, the manipulations performed are often referred to in terms, such as producing, identifying, determining, or comparing. Any of the operations described herein that form part of the embodiments are useful machine operations. The embodiments also relate to a device or an apparatus for performing these operations. The apparatus can be specially constructed for the required purpose, or the apparatus can be a general-purpose computer selectively activated or configured by a computer program stored in the computer. In particular, various general-purpose machines can be used with computer programs written in accordance with the teachings herein, or it may be more convenient to construct a more specialized apparatus to perform the required operations. 
     A module, an application, a layer, an agent or other method-operable entity could be implemented as hardware, firmware, or a processor executing software, or combinations thereof. It should be appreciated that, where a software-based embodiment is disclosed herein, the software can be embodied in a physical machine such as a controller. For example, a controller could include a first module and a second module. A controller could be configured to perform various actions, e.g., of a method, an application, a layer or an agent. 
     The embodiments can also be embodied as computer readable code on a tangible non-transitory computer readable medium. The computer readable medium is any data storage device that can store data, which can be thereafter read by a computer system. Examples of the computer readable medium include hard drives, network attached storage (NAS), read-only memory, random-access memory, CD-ROMs, CD-Rs, CD-RWs, magnetic tapes, and other optical and non-optical data storage devices. The computer readable medium can also be distributed over a network coupled computer system so that the computer readable code is stored and executed in a distributed fashion. Embodiments described herein may be practiced with various computer system configurations including hand-held devices, tablets, microprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers and the like. The embodiments can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a wire-based or wireless network. 
     Although the method operations were described in a specific order, it should be understood that other operations may be performed in between described operations, described operations may be adjusted so that they occur at slightly different times or the described operations may be distributed in a system which allows the occurrence of the processing operations at various intervals associated with the processing. 
     In various embodiments, one or more portions of the methods and mechanisms described herein may form part of a cloud-computing environment. In such embodiments, resources may be provided over the Internet as services according to one or more various models. Such models may include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). In IaaS, computer infrastructure is delivered as a service. In such a case, the computing equipment is generally owned and operated by the service provider. In the PaaS model, software tools and underlying equipment used by developers to develop software solutions may be provided as a service and hosted by the service provider. SaaS typically includes a service provider licensing software as a service on demand. The service provider may host the software, or may deploy the software to a customer for a given period of time. Numerous combinations of the above models are possible and are contemplated. 
     Various units, circuits, or other components may be described or claimed as “configured to” perform a task or tasks. In such contexts, the phrase “configured to” is used to connote structure by indicating that the units/circuits/components include structure (e.g., circuitry) that performs the task or tasks during operation. As such, the unit/circuit/component can be said to be configured to perform the task even when the specified unit/circuit/component is not currently operational (e.g., is not on). The units/circuits/components used with the “configured to” language include hardware—for example, circuits, memory storing program instructions executable to implement the operation, etc. Reciting that a unit/circuit/component is “configured to” perform one or more tasks is expressly intended not to invoke 35 U.S.C. 112, sixth paragraph, for that unit/circuit/component. Additionally, “configured to” can include generic structure (e.g., generic circuitry) that is manipulated by software and/or firmware (e.g., an FPGA or a general-purpose processor executing software) to operate in manner that is capable of performing the task(s) at issue. “Configured to” may also include adapting a manufacturing process (e.g., a semiconductor fabrication facility) to fabricate devices (e.g., integrated circuits) that are adapted to implement or perform one or more tasks. 
     The foregoing description, for the purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the embodiments and its practical applications, to thereby enable others skilled in the art to best utilize the embodiments and various modifications as may be suited to the particular use contemplated. Accordingly, the present embodiments are to be considered as illustrative and not restrictive, and the invention is not to be limited to the details given herein, but may be modified within the scope and equivalents of any appended claims.