Disaster recovery in a streaming data storage system

A streaming data storage system maintains a hierarchical structure of metadata in association with the data chunks of streams, in which the metadata facilitates recovery of the data streams if the streaming data storage system fails. In one implementation, the metadata comprises the pathnames and filenames of the chunks stored in a file storage system or object storage system, in which each pathname represents the epoch and segment of the chunks in the segment, and the chunks' filenames represent the relative ordering of the chunks in the segment. To recover the data stream, the epochs and their segments are recreated, and the segments are repopulated with references to their respective chunks. Once recovered, a new epoch is created with a number of active segments equal to the number of segments of the last recreated epoch, and event appends to the data stream can resume.

TECHNICAL FIELD

The subject application relates generally to data storage, and, for example, to a technology that recovers a data stream of event data in storage systems that implement data streams for storing and serving continuous and unbounded data, and related embodiments.

BACKGROUND

Some contemporary data storage systems, such as DELL EMC's PRAVEGA system/data storage service, store data in a storage abstraction referred to as a data stream, or more simply, a stream. A stream is identified with a name, and can store continuous and potentially unbounded data; more particularly, a stream comprises a durable, elastic, append-only, sequence of stored events. New events are added to a tail (front) of a stream. As can be readily appreciated, PRAVEGA is thus ideal for IoT (Internet of Things) data, where devices/sensors may generate thousands of data points per second. Notwithstanding, PRAVEGA may be highly beneficial for storing data corresponding to more traditional workloads, such as financial trading data that regularly changes.

One stream may be divided into one or more segments, with each new event appended by a writer application to a segment that is determined based on a hash computation of a routing key associated with that event. Once written, the events in a stream/stream segment are immutable and cannot be modified.

In general, a streaming data storage system keeps a small amount of fresh data in Tier-1 storage, which provides efficient access to the data for processing. Older data is aggregated into chunks and written to an object storage system (e.g., DELL EMC ECS) or to a file storage system (e.g., DELL EMC ISILON), where a chunk comprises an ordered list of events from one segment, stored in Tier-2 storage (e.g., in a cloud). For example, PRAVEGA works as a Tier-1 of a multi-tiered system and the file/object storage system works as a Tier-2 storage. Therefore, PRAVEGA implements automatic tiering for stream data.

The event data of a data stream can be retained indefinitely. However, it is possible that a streaming data storage system can fail, resulting in its data streams being lost, as some users of a data streaming storage system have a standalone data streaming storage system and/or no replication of the data stream. After such a failure, the event data in Tier-2 storage chunks still physically exists, but such data is now simply raw data that can no longer be interpreted, even when a new instance of the streaming data storage system is restarted.

DETAILED DESCRIPTION

Various aspects of the technology described herein are generally directed towards configuring/associating the chunks of a data stream with metadata that allows the data stream to be recovered following failure of the data streaming storage system that maintained the data stream. In one implementation, the metadata is based on the hierarchical aspects of a file system, in conjunction with a naming convention, in which the directory path to each chunk and the chunk's filename contain the information from which the data stream can be recovered. For example, the file system's directory pathname for a data stream can comprise the epoch and segment associated with each chunk, and the name of each chunk can establish the order of that chunk relative to any other chunks in the segment (that is, within the same “epoch/segment” pathname). Then, if needed to recover the data stream, the pathnames to the chunks are used to recreate the epochs and segments, and the filenames of the chunks are used to populate the segments with references to the chunks, in order, whereby the older events are readable in the proper order.

It should be understood that any of the examples herein are non-limiting. For instance, some of the examples are based on PRAVEGA data storage technology, which, for example, maintains event data in data chunks in Tier-2 (e.g., cloud) storage as files; however virtually any stream-based data storage system may benefit from the technology described herein. Thus, any of the embodiments, aspects, concepts, structures, functionalities or examples described herein are non-limiting, and the technology may be used in various ways that provide benefits and advantages in computing and data storage in general.

Reference throughout this specification to “one embodiment,” “an embodiment,” “one implementation,” “an implementation,” etc. means that a particular feature, structure, or characteristic described in connection with the embodiment/implementation can be included in at least one embodiment/implementation. Thus, the appearances of such a phrase “in one embodiment,” “in an implementation,” etc. in various places throughout this specification are not necessarily all referring to the same embodiment/implementation. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments/implementations.

FIG. 1shows a streaming data storage system100that maintains segments of streamed data events of a data stream102comprised of multiple segments104(1)-104(n). In general, data writes106received from one or more streaming application programs (event writers)108are appended to the tail of one of the segments based on a routing key associated with each event; (as is known, a conventional event comprises a routing key along with the event data contents to be stored; the event data contents are alternatively referred to herein as the payload). The routing key is hashed to a value that determines the segment.

In general, a controller110(or other similar component) moves older event data (from the data stream head) from Tier-1 storage to data chunks in Tier-2 storage112, such as based on administrator (or default) set policy. As described herein, the controller110, via naming/move logic114, names and moves the data chunks to the Tier-2 storage112in a way that allows recovery logic116to recover the (typically) major part of the data stream from the Tier-2 storage112. Note thatFIG. 1shows a single data stream102, however the streaming data storage system100can create and maintain any practical number of data streams.

Recovery allows data reads118of the older, recovered data events to occur by event readers/reader groups120that consume and process the data events' payloads. Note that in general, the event readers120do not know whether an event is maintained in Tier-1 storage or the Tier-2 storage112, however the recovered data events in Tier-2 storage are no longer lost after recovery.

As described herein, the way in which the chunks containing data stream events are stored in Tier-2 storage facilitates recovering data after a failure of the streaming data storage system100. The technology facilitates recovery of a (typically major) part of stream data, even after a complete loss of the streaming data storage system100. Note that recovery as described herein refers to restoring the part of the data stream(s) that are in Tier-2 storage chunks, which can be most, if not all, of the data streams' data; complete recovery is feasible for an active data stream if the events in Tier-1 storage, generally relatively few in number compared to the amount of the events in the Tier-2 storage chunks, are protected in some way.

The technology described herein is based, in part, on the high likelihood that the major part of a stream's data of the streaming data storage system100resides outside the streaming data storage system's Tier-1 storage, in the Tier-2 storage system112, e.g., in a cloud. The technology described herein is directed towards a way to correctly interpret the data saved in the Tier-2 storage112, which thereby recovers the major part of the data stream(s) of the streaming data storage system100.

It should be noted that the streaming data storage system100may use any file storage system or any object storage system as the Tier-2 storage112. What file storage systems and object storage systems have in common is a support of a hierarchical view on data. In other words, the Tier-2 storage supports directories (also known as folders). In one implementation, the hierarchical structure of such directories is leveraged to describe the content of data chunks created by the streaming data storage system100.

FIG. 2shows additional details of segments of data stream220as described herein, in which new events are appended to the end (tail) of a stream. As described herein, each ordered event comprises a routing key and an event payload. The routing key can be named by the user, and is often derived from data naturally occurring in the event, e.g. “device-id” of the device that generated the event; should the user not specify a routing key, a routing key can be randomly assigned by the streaming data storage system. Events are ordered per routing key, and can be read in append order by a conventional reader.

As shown inFIG. 2, the data stream220is split into segments, which are logical containers for the events within the data stream220. When a new event is written to a stream, the event is stored to one of the segments based on the event's routing key. As can be seen inFIG. 2, event routing keys are hashed (using consistent hashing) to form a “key space” which corresponds to the number of segments; for example Segment 1 contains events with routing keys that hash between 0.5 and 1.0.

FIG. 2also shows that data streams such as the data stream220are elastic, as the streaming data storage system can change a data stream's number of segments over time. The streaming data storage system monitors the usage of each of the stream's segments and decides whether those segments need to be scaled, meaning split or merged, e.g., based on the current event ingestion rate. A segment split creates two or more successor segments that (e.g., evenly) split a predecessor segment's routing key space. A segment merge combines two or more predecessor segments that are assigned to adjacent routing key spaces and creates a lesser number (typically one) successor segment that is assigned to the combined routing key space of the original predecessor segments. This elasticity of scaling allows data streams to react to changes in ingestion patterns (more segments are created when ingestion throughput increases and fewer segments are used when ingestion drops down).

When a data stream is created, and each time a scaling event occurs with respect to the data stream, a new epoch is created. By way of example, the data stream220starts with two parallel segments, Segment 1 and Segment 0, at an initial epoch, epoch 1. At time t1, Segment 1 is split, with Segments 2 and 3 as successors, resulting in epoch 2 being created. At time t2, Segment 0 is split, with Segments 4 and 5 as successors, creating epoch 3, and at time t3, Segments 2 and 5 are merged with Segment 6 as a successor, creating epoch 4. As described herein, the epochs of a data stream are uniquely identified, which in one implementation is based on sequentially numbering the epochs' names, in the order of their creation. Further, the segments of the data stream have unique segment identifiers, which in one implementation are based on numbering segment identifiers (names) sequentially, in the order of segment creation.

Thus, an epoch can be identified by a number that is unique within the epoch's stream, such as a sequential number that is incremented whenever a new epoch is created. Similarly, the segments of a data stream can be identified by a unique segment number (e.g., an increasing sequential number upon segment creation) in their data stream as well, rather than being identified by their sequential number within an epoch. As one segment, such as the Segment 0 inFIG. 2, may survive one or more epochs, in such a scheme more information about the stream structure throughout the various epochs can be determined from the segment's number. Note that there is no information about ranges of hashed routing keys associated with segments, however this information is needed for new events only, and is not needed for historical data.

In one implementation, when the events of the data stream are moved to Tier-2 storage, the chunks that maintain the events are named with a file system pathname based on the epochs and the segments associated with those epochs, with chunk filenames that represent the ordering of the chunks of each segment. For example, the group of data chunks (chunk 1-chunk i) represented by the block222each have as their file system directory pathname Epoch1/Segment0/, followed by the chunks' filenames. In one implementation, the filenames of the chunks represent the order of the chunks, that is, corresponding to the order of the events relative to one another within the chunks. For example, Epoch1/Segment0/Chunk1 contains that epoch's and segment's events, in appending order, prior to the events of Epoch1/Segment0/Chunk2, and so on. For clarity, not all of the pathnames for the epochs and segments shown inFIG. 2are shown with their corresponding set of data chunks, however the blocks222-226depict some of the epoch and segment pathnames, and each of their data chunks' filenames.

Thus, in contrast to existing streaming data storage systems, as described herein, in one implementation, chunks of a data stream can have meaningful names that produce a hierarchical structure of data. Note that a data stream is identified by a name (preferably, a meaningful string). Further, multiple data streams, each with a different name, can be organized within a scope (a namespace). A scope also can be identified by a meaningful name, and there can be multiple scopes managed by the streaming data storage system.

The example ofFIG. 3shows a hierarchical structure in which each chunk name describes where that chunk fits into the data stream. By way of example, the name (including pathname and filename) of one of the chunks332inFIG. 3is shown, in conjunction with its scope name and stream name, as: System_Root/scope_name_1/stream_name_1/epoch1/segment0/chunk2. Therefore, each chunk name describes data stored within the chunk, as well as defining the correct order of events stored to different chunks.

Thus, for each scope and data stream in that scope, the chunks from different epochs and segments can be ascertained from their directory location (pathname), and within that directory pathname chunks can be sequentially numbered locally, at the directory location level. As one benefit, this tends to make full names of chunks somewhat shorter than having a unique identifier per chunk filename, as the pathname is part of a chunk's unique identifier as described herein.

It should be noted that while the hierarchical structure of the chunks' pathnames and filenames can be used to recreate the epochs, segments and the ordering of chunk (event) data within each segment, this is only one very convenient and practical solution that leverages an already existing filesystem's hierarchy. Indeed, as each chunk needs a unique name, the pathname and filename provide a straightforward, easy to understand solution. An alternative includes separately maintaining (e.g., in Tier-2 cloud storage) basically the same metadata that is needed to recreate the epochs, segments and chunk ordering. For example, the streaming data storage system can maintain a key-value store (or stores) that maps more conventional chunk names to the epoch, segment and order information for that chunk/data stream. Another alternative is to maintain the scope name, stream name, epoch, segment and relative chunk ordering within the segment as part of the information in a chunk header for each chunk.

Turning to recovery-related operations after the streaming data storage system fails and a new instance thereof restarted,FIG. 4depicts some of the data structures that the controller110can recreate from the pathnames and filenames of the chunks, (once the streaming data storage system is again operational a failure). Note that although the example data structures are shown as being stored in a segment store440, the data structures can be stored in any suitable location.

In the example ofFIG. 4, each epoch's directory contains references to its segments, and thus epoch data442is recreated to relate the various epochs, recreated during recovery as described herein, to each of their segments. Each of the segments444is recreated as well, in association with the segment's epoch, and contain references to their chunks. Segment attributes446, such as the length of each segment, can be obtained based on the data in a segment's chunk(s).

As described herein, after the recovery the controller110seals the recreated segments444, e.g., identified via a data structure446, and thus allows no further appends to those segments. New active segments are created for storing further appends, as identified via block448, corresponding to active segment data450.

Once recovered, writers452, via an API call to a client component454, can write new events (have them appended to) to the active segments450. Readers456, via the client component456, can read from the active segment data450as well as from the recreated segment data444, via the references to the chunks that contain the event data.

FIG. 5shows some of the data structures generally corresponding to the data stream220ofFIG. 2. Consider that, for example, events were stored in Tier-2 storage up to and including Epoch 4. Using a hierarchical directory structure such as shown inFIG. 3, it is seen that Epoch 1 is recreated with recreated segments S1 and S2, Epoch 2 is recreated with recreated segments S3 and S2, plus (previously existing) segment S1, and so on. During recreation of a segment, that segment is populated with references to its chunk(s) as described herein.

As also described herein, after recovery, the recreated segments are sealed (block550), and a new Epoch 5 is created with active segments. The number of segments is the same number that existed in the last epoch, which in this example is Epoch 4, and which had three segments (S3, S6 and S4), whereby segments S7, S8 and S9 are created as the active segments (block552) of newly created Epoch 5.

Note that while one chunk belongs to one stream segment, the chunk may store events from two or more successive epochs. In such a situation, the home directory of a chunk can be derived using the epoch of the first event within the chunk. Further, a segment may create no chunks for some epoch N, but have chunks created for neighboring epochs N−1 and N+1.

FIGS. 6 and 7comprise a flow diagram of example operations of a data recovery procedure, as well as operations thereafter, as described herein. In a typical scenario, the system administrator commences the recovery procedure by identifying the system root directory (folder) within the Tier-2 storage system to be recovered.

In general, the procedure is driven by the controller, which begins at operation602by scanning the first two levels of the system root directory to produce a list of scopes and streams. At operation604, the controller creates the scopes and streams from the list, and operation606selects a first stream.

Once the list of scopes and streams is obtained, it should be noted that recovery can be performed for multiple data streams in parallel or substantially in parallel. Further, subsets of the data streams can be recovered in parallel, such as if insufficient computing resources are available to recover all the data streams of all the scopes in parallel. As such, once a first stream is selected, the operations in block608, including those ofFIG. 7, generally refer to recovery of one such data stream; operations622and624can represent generally parallel selection of the next stream(s) and so on, or can represent recovering as little as a single data stream at a time.

In general, via the example operations in block608, including those ofFIG. 7, the controller scans each stream directory to populate streams with data. For the selected stream, at operation610the controller handles epochs in the natural order, starting with epoch 1, and creates the first epoch.

In this example, for each epoch starting with the first epoch, the operations of the controller branch toFIG. 7, where the controller handles segments in their natural order, starting by selecting the segment with the lowest sequential segment number at operation702. At operation704, the controller adds the segment to the current epoch.

At operation706, the controller checks if the segment is new, that is, whether the segment was created for the current epoch. This can be easily using the segment's sequential number, because the sequential numbers of segments in the data stream increase over time.

If the segment is new, at operation708the controller instructs the segment store to create the segment. If the segment is not new, that is, was created for a previous epoch, at operation710the controller makes sure the segment reference has been added to the appropriate epoch(s), that is, those that follow the epoch that had produced the segment.

For each segment, the controller handles chunks (objects/files) in their natural order, starting with chunk1, as represented by operation711. At operation712, the controller instructs the segment store to add the current chunk (that is, the reference to the chunk) to the currently selected segment of the current stream. Operations714and716repeat the process for each other chunk of the selected segment until none remain for the selected segment.

When the segment has been populated with chunk reference(s), operations718and720select the next segment for this epoch, and so on until none remain to be repopulated. When none remain, operation718returns the process to operation612ofFIG. 6, which, in conjunction with operation614, create the next epoch and so on, until none remain.

When the epochs have been recreated with their recreated segments, and the segments repopulated as described herein, at operation616the controller instructs the segment store to seal the stream segments created during the recovery procedure. As described above with reference toFIG. 5, at operation618the controller creates a new epoch for new data, which is created with the same number of segments that last epoch had; in one implementation, the hashed routing key space is divided evenly between the new segments, which can later be changed via a scaling event. As represented by operation620, the data stream is now ready to accept new writes.

Apart from data, streams may also have other configuration data (e.g., data expiration policies, data retention policies, access control lists, and the like). After a failure and recovery, the administrator may restore the configuration manually. Alternatively, this information can be stored in chunks in some system stream. The full-dump approach can be used for configurations with small footprints. If the total size of streams' configuration exceeds a predefined threshold (e.g., 4 MB), the streaming data storage system may switch to a full-dump with increments approach. When the configuration is available from the Tier-2 storage, the recovery procedure described herein can utilize the configuration data to recover the various streams' configurations as well.

One or more aspects can be embodied in a system, such as represented inFIG. 8and for example can comprise a memory that stores computer executable components and/or operations, and a processor that executes computer executable components and/or operations stored in the memory. Example operations can comprise operation802, which represents storing a data stream as a hierarchical structure, in which epochs of the data stream are hierarchically higher than segments of the data stream, and the segments are hierarchically higher than data chunks containing event data of the data stream. Operation804represents recovering the data stream based on the hierarchical structure, comprising recreating the epochs of the data stream, recreating the segments of the data stream, associating the segments with the epochs based on the hierarchical structure, and associating the data chunks with the segments based on the hierarchical structure.

The hierarchical structure can correspond to a file system, in which the epochs and segments form directories of the file system, and in which the data chunks are files within the directories.

Each epoch can be identified by a sequential number in the data stream. Each segment can be identified by a sequential number in the data stream. A segment can be associated with two or more epochs.

Recreating the segments of the data stream can comprise determining whether a segment was created for an epoch, and, in response to determining that the segment was created for the epoch, instructing a segment store to create the segment in association with the epoch.

Recreating the segments of the data stream can comprise determining that a segment was created for a first epoch, and, in response to determining that the segment was created for the first epoch, adding an identifier of the segment to a second epoch following the first epoch.

Further operations can comprise sealing the segments, and creating a new epoch with a number of new segments corresponding to a number of segments of a last recreated epoch. Further operations can comprise dividing a routing key space evenly among the number of new segments. Further operations can comprise receiving an event comprising a routing key and payload, hashing the routing key to determine a matching segment to which the event is mapped, and appending the payload to the matching segment.

One or more aspects can be embodied in a system, such as represented inFIG. 9, and for example can comprise a memory that stores computer executable components and/or operations, and a processor that executes computer executable components and/or operations stored in the memory. Example operations can comprise operation902, which represents maintaining data chunks that store event data of a data stream, the data stream comprising epochs and segments, in which each data chunk is associated with metadata representing an epoch and a segment corresponding to the chunk and indicating an ordering of the chunk within the segment. Operation904represents recovering the data stream, comprising processing metadata of the data chunks to recreate the epochs and segments of the data stream, and to reference respective data chunks within respective segments based on the ordering of the respective data chunks within the respective segments.

The metadata associated with a chunk can comprise a directory pathname and a filename, the directory pathname representing the epoch and segment of the chunk, and the filename of the chunk indicating the ordering of the chunk within the segment.

A segment can be identified by a data stream unique value that indicates a relative order of segment creation.

Further operations can comprise sealing the segments, and creating a new epoch with a number of new segments corresponding to a number of segments of a last recreated epoch.

FIG. 10summarizes various example operations, e.g., corresponding to a machine-readable storage medium, comprising executable instructions that, when executed by a processor of a streaming data storage system, facilitate performance of operations. Operation1002represents storing a first data chunk, comprising first events of a data stream, in a first directory location comprising a first pathname that is based on a first epoch and a first segment associated with the first data chunk. Operation1004represents storing a second data chunk, comprising second events of the data stream, in a second directory location comprising a second pathname that is based on the first epoch and a second segment associated with the second data chunk. Operation1006represents recovering the data stream based on the first pathname and the second pathname, comprising recreating the first epoch, recreating the first segment in association with the first epoch, recreating the second segment in association with the first epoch, referencing the first data chunk from the first segment, and referencing the second data chunk from the second segment.

Further operations can comprise storing a third data chunk in a third directory location comprising the first pathname, the third data chunk comprising third events of the data stream, wherein the name of the first data chunk within the first pathname and the name of the third data chunk within the first pathname indicates that the first events the data stream are prior to the third events of the data stream.

Further operations can comprise determining that the recovering of the data stream is complete, and, in response to the determining that the recovering of the data stream is complete, creating a new epoch with a number of active segments corresponding to a number of segments of a last recreated epoch.

Further operations can comprise sealing the segments of the last recreated epoch. Further operations can comprise dividing a routing key space evenly among the number of active segments. Further operations can comprise receiving an event comprising a routing key and payload, hashing the routing key to determine a matching active segment to which the event is mapped, and appending the payload to the matching active segment.

The technology described herein for disaster recovery is practical to implement. The technology allows recovery of the major part of stream data even after a complete loss of a storage data storage system. The technology can be based on intelligent naming of the data chunks of stream data stored within a Tier-2 storage system.

FIG. 11is a schematic block diagram of a computing environment1100with which the disclosed subject matter can interact. The system1100comprises one or more remote component(s)1110. The remote component(s)1110can be hardware and/or software (e.g., threads, processes, computing devices). In some embodiments, remote component(s)1110can be a distributed computer system, connected to a local automatic scaling component and/or programs that use the resources of a distributed computer system, via communication framework1140. Communication framework1140can comprise wired network devices, wireless network devices, mobile devices, wearable devices, radio access network devices, gateway devices, femtocell devices, servers, etc.

The system1100also comprises one or more local component(s)1120. The local component(s)1120can be hardware and/or software (e.g., threads, processes, computing devices). In some embodiments, local component(s)1120can comprise an automatic scaling component and/or programs that communicate/use the remote resources1110and1120, etc., connected to a remotely located distributed computing system via communication framework1140.

One possible communication between a remote component(s)1110and a local component(s)1120can be in the form of a data packet adapted to be transmitted between two or more computer processes. Another possible communication between a remote component(s)1110and a local component(s)1120can be in the form of circuit-switched data adapted to be transmitted between two or more computer processes in radio time slots. The system1100comprises a communication framework1140that can be employed to facilitate communications between the remote component(s)1110and the local component(s)1120, and can comprise an air interface, e.g., Uu interface of a UMTS network, via a long-term evolution (LTE) network, etc. Remote component(s)1110can be operably connected to one or more remote data store(s)1150, such as a hard drive, solid state drive, SIM card, device memory, etc., that can be employed to store information on the remote component(s)1110side of communication framework1140. Similarly, local component(s)1120can be operably connected to one or more local data store(s)1130, that can be employed to store information on the local component(s)1120side of communication framework1140.

With reference again toFIG. 12, the example environment1200for implementing various embodiments of the aspects described herein includes a computer1202, the computer1202including a processing unit1204, a system memory1206and a system bus1208. The system bus1208couples system components including, but not limited to, the system memory1206to the processing unit1204. The processing unit1204can be any of various commercially available processors. Dual microprocessors and other multi-processor architectures can also be employed as the processing unit1204.

The computer1202further includes an internal hard disk drive (HDD)1214(e.g., EIDE, SATA), and can include one or more external storage devices1216(e.g., a magnetic floppy disk drive (FDD)1216, a memory stick or flash drive reader, a memory card reader, etc.). While the internal HDD1214is illustrated as located within the computer1202, the internal HDD1214can also be configured for external use in a suitable chassis (not shown). Additionally, while not shown in environment1200, a solid state drive (SSD) could be used in addition to, or in place of, an HDD1214.

Other internal or external storage can include at least one other storage device1220with storage media1222(e.g., a solid state storage device, a nonvolatile memory device, and/or an optical disk drive that can read or write from removable media such as a CD-ROM disc, a DVD, a BD, etc.). The external storage1216can be facilitated by a network virtual machine. The HDD1214, external storage device(s)1216and storage device (e.g., drive)1220can be connected to the system bus1208by an HDD interface1224, an external storage interface1226and a drive interface1228, respectively.

A number of program modules can be stored in the drives and RAM1212, including an operating system1230, one or more application programs1232, other program modules1234and program data1236. All or portions of the operating system, applications, modules, and/or data can also be cached in the RAM1212. The systems and methods described herein can be implemented utilizing various commercially available operating systems or combinations of operating systems.

Computer1202can optionally comprise emulation technologies. For example, a hypervisor (not shown) or other intermediary can emulate a hardware environment for operating system1230, and the emulated hardware can optionally be different from the hardware illustrated inFIG. 12. In such an embodiment, operating system1230can comprise one virtual machine (VM) of multiple VMs hosted at computer1202. Furthermore, operating system1230can provide runtime environments, such as the Java runtime environment or the .NET framework, for applications1232. Runtime environments are consistent execution environments that allow applications1232to run on any operating system that includes the runtime environment. Similarly, operating system1230can support containers, and applications1232can be in the form of containers, which are lightweight, standalone, executable packages of software that include, e.g., code, runtime, system tools, system libraries and settings for an application.

A monitor1246or other type of display device can be also connected to the system bus1208via an interface, such as a video adapter1248. In addition to the monitor1246, a computer typically includes other peripheral output devices (not shown), such as speakers, printers, etc.

When used in a LAN networking environment, the computer1202can be connected to the local network1254through a wired and/or wireless communication network interface or adapter1258. The adapter1258can facilitate wired or wireless communication to the LAN1254, which can also include a wireless access point (AP) disposed thereon for communicating with the adapter1258in a wireless mode.

When used in a WAN networking environment, the computer1202can include a modem1260or can be connected to a communications server on the WAN1256via other means for establishing communications over the WAN1256, such as by way of the Internet. The modem1260, which can be internal or external and a wired or wireless device, can be connected to the system bus1208via the input device interface1244. In a networked environment, program modules depicted relative to the computer1202or portions thereof, can be stored in the remote memory/storage device1252. It will be appreciated that the network connections shown are example and other means of establishing a communications link between the computers can be used.

When used in either a LAN or WAN networking environment, the computer1202can access cloud storage systems or other network-based storage systems in addition to, or in place of, external storage devices1216as described above. Generally, a connection between the computer1202and a cloud storage system can be established over a LAN1254or WAN1256e.g., by the adapter1258or modem1260, respectively. Upon connecting the computer1202to an associated cloud storage system, the external storage interface1226can, with the aid of the adapter1258and/or modem1260, manage storage provided by the cloud storage system as it would other types of external storage. For instance, the external storage interface1226can be configured to provide access to cloud storage sources as if those sources were physically connected to the computer1202.