Patent Publication Number: US-2023146076-A1

Title: Backing file system with cloud object store

Description:
TECHNICAL FIELD 
     The present disclosure relates generally to computer architecture software for a data management platform and, in some more particular aspects, to a system and method of backing a file system with a cloud-based object store. 
     BACKGROUND 
     Cloud providers support multiple types of storage for varying customer needs. Most software is built to store data in a file system format and use disk-based data storage on cloud instances. However, disk-based data storage suffers from issues of durability, reliability, and scalability. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Some example embodiments of the present disclosure are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like reference numbers indicate similar elements. 
         FIG.  1    depicts a networked computing environment in which the disclosed technology may be practiced, according to some example embodiments. 
         FIG.  2    depicts one embodiment of the server of  FIG.  1   , according to some example embodiments. 
         FIG.  3    depicts one embodiment of the storage appliance of  FIG.  1   , according to some example embodiments. 
         FIG.  4    is a block diagram illustrating components of a computer system, in accordance with some example embodiments. 
         FIG.  5    illustrates a workflow for writing data to a file in a cloud-based key-value object store, in accordance with some example embodiments. 
         FIG.  6    illustrates another workflow for writing data to a file in a cloud-based key-value object store, in accordance with some example embodiments. 
         FIG.  7    illustrates a workflow for reading data from a file in a cloud-based key-value object store, in accordance with some example embodiments. 
         FIG.  8    is a flowchart illustrating a method of backing a file system with a cloud-based object store, in accordance with some example embodiments. 
         FIG.  9    is a block diagram illustrating a representative software architecture, in accordance with some example embodiments. 
         FIG.  10    is a diagrammatic representation of a machine in the form of a computer system within which a set of instructions may be executed for causing the machine to perform any one or more of the methodologies discussed herein, in accordance with some example embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     Example methods and systems for backing a file system with a cloud-based object store are disclosed. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of example embodiments. It will be evident, however, to one skilled in the art that the present embodiments can be practiced without these specific details. 
     A portion of the disclosure of this patent document contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever. The following notice applies to the software and data as described below and in the drawings that form a part of this document: Copyright Rubrik, Inc., 2018-2021, All Rights Reserved. 
     The implementation of the features disclosed herein involves a non-generic, unconventional, and non-routine operation or combination of operations. By applying one or more of the solutions disclosed herein, some technical effects of the system and method of the present disclosure are to provide a computer system that is specially-configured to back a file system with a cloud-based object store. The computer system may be configured to provide a filesystem interface in which any data written to a disk-based filesystem is automatically stored directly on a cloud-based key-value object store, thereby achieving the benefit and advantages of the cloud-based object store. Additionally, a staging area may be implemented to make the writing to and reading from the cloud-based object store more efficient. For example, the staging area may buffer data writes until a period of inactivity, at which point the buffered data writes are written to the cloud-based object store. The staging area may also cache data reads from the cloud-based object store so that subsequent reads are processed more quickly. 
     In some example embodiments, the computer system is configured to implement user space file system that receives a first request to write a first set of data to a file, writes the first set of data to the file in a cloud-based key-value object store based on the receiving of the first request to write the first set of data to the file, receives a second request to read a second set of data from the file, and fetches the second set of data from the file in the cloud-based key-value object store based on the receiving of the second request to read the second set of data from the file. As a result of these and other features disclosed herein, the durability, reliability, scalability, efficiency, and speed of a computer system in backing up and recovering data is improved. Other technical effects will be apparent from this disclosure as well. 
     The methods or embodiments disclosed herein may be implemented as a computer system having one or more modules (e.g., hardware modules or software modules). Such modules may be executed by one or more hardware processors of the computer system. In some example embodiments, a non-transitory machine-readable storage device can store a set of instructions that, when executed by at least one processor, causes the at least one processor to perform the operations and method steps discussed within the present disclosure. 
     The details of one or more variations of the subject matter described herein are set forth in the accompanying drawings and the description below. Other features and benefits of the subject matter described herein will be apparent from the description and drawings, and from the claims. 
       FIG.  1    depicts one embodiment of a networked computing environment  100  in which the disclosed technology may be practiced. As depicted, the networked computing environment  100  includes a data center  104 , a storage appliance  102 , and a computing device  106  in communication with each other via one or more networks  128 . The networked computing environment  100  may also include a plurality of computing devices interconnected through one or more networks  128 . The one or more networks  128  may allow computing devices and/or storage devices to connect to and communicate with other computing devices and/or other storage devices. In some cases, the networked computing environment  100  may include other computing devices and/or other storage devices not shown. The other computing devices may include, for example, a mobile computing device, a non-mobile computing device, a server, a work-station, a laptop computer, a tablet computer, a desktop computer, or an information processing system. The other storage devices may include, for example, a storage area network storage device, a networked-attached storage device, a hard disk drive, a solid-state drive, or a data storage system. 
     The data center  104  may include one or more servers, such as server  200 , in communication with one or more storage devices, such as storage device  108 . The one or more servers may also be in communication with one or more storage appliances, such as storage appliance  102 . The server  200 , storage device  108 , and storage appliance  300  may be in communication with each other via a networking fabric connecting servers and data storage units within the data center  104  to each other. The storage appliance  300  may include a data management system for backing up virtual machines and/or files within a virtualized infrastructure. The server  200  may be used to create and manage one or more virtual machines associated with a virtualized infrastructure. 
     The one or more virtual machines may run various applications, such as a database application or a web server. The storage device  108  may include one or more hardware storage devices for storing data, such as a hard disk drive (HDD), a magnetic tape drive, a solid-state drive (SSD), a storage area network (SAN) storage device, or a Network-Attached Storage (NAS) device. In some cases, a data center, such as data center  104 , may include thousands of servers and/or data storage devices in communication with each other. The one or more data storage devices  108  may comprise a tiered data storage infrastructure (or a portion of a tiered data storage infrastructure). The tiered data storage infrastructure may allow for the movement of data across different tiers of a data storage infrastructure between higher-cost, higher-performance storage devices (e.g., solid-state drives and hard disk drives) and relatively lower-cost, lower-performance storage devices (e.g., magnetic tape drives). 
     The one or more networks  128  may include a secure network such as an enterprise private network, an unsecure network such as a wireless open network, a local area network (LAN), a wide area network (WAN), and the Internet. The one or more networks  128  may include a cellular network, a mobile network, a wireless network, or a wired network. Each network of the one or more networks  128  may include hubs, bridges, routers, switches, and wired transmission media such as a direct-wired connection. The one or more networks  128  may include an extranet or other private network for securely sharing information or providing controlled access to applications or files. 
     A server, such as server  200 , may allow a client to download information or files (e.g., executable, text, application, audio, image, or video files) from the server  200  or to perform a search query related to particular information stored on the server  200 . In some cases, a server may act as an application server or a file server. In general, server  200  may refer to a hardware device that acts as the host in a client-server relationship or a software process that shares a resource with or performs work for one or more clients. 
     One embodiment of server  200  includes a network interface  110 , processor  112 , memory  114 , disk  116 , and virtualization manager  118  all in communication with each other. Network interface  110  allows server  200  to connect to one or more networks  128 . Network interface  110  may include a wireless network interface and/or a wired network interface. Processor  112  allows server  200  to execute computer-readable instructions stored in memory  114  in order to perform processes described herein. Processor  112  may include one or more processing units, such as one or more CPUs and/or one or more GPUs. Memory  114  may comprise one or more types of memory (e.g., RAM, SRAM, DRAM, ROM, EEPROM, Flash, etc.). Disk  116  may include a hard disk drive and/or a solid-state drive. Memory  114  and disk  116  may comprise hardware storage devices. 
     The virtualization manager  118  may manage a virtualized infrastructure and perform management operations associated with the virtualized infrastructure. The virtualization manager  118  may manage the provisioning of virtual machines running within the virtualized infrastructure and provide an interface to computing devices interacting with the virtualized infrastructure. In one example, the virtualization manager  118  may set a virtual machine having a virtual disk into a frozen state in response to a snapshot request made via an application programming interface (API) by a storage appliance, such as storage appliance  300 . Setting the virtual machine into a frozen state may allow a point in time snapshot of the virtual machine to be stored or transferred. In one example, updates made to a virtual machine that has been set into a frozen state may be written to a separate file (e.g., an update file) while the virtual disk may be set into a read-only state to prevent modifications to the virtual disk file while the virtual machine is in the frozen state. 
     The virtualization manager  118  may then transfer data associated with the virtual machine (e.g., an image of the virtual machine or a portion of the image of the virtual disk file associated with the state of the virtual disk at the point in time it is frozen) to a storage appliance (for example, a storage appliance  102  or storage appliance  300  of  FIG.  1   , described further below) in response to a request made by the storage appliance. After the data associated with the point in time snapshot of the virtual machine has been transferred to the storage appliance  300  (for example), the virtual machine may be released from the frozen state (i.e., unfrozen) and the updates made to the virtual machine and stored in the separate file may be merged into the virtual disk file. The virtualization manager  118  may perform various virtual machine-related tasks, such as cloning virtual machines, creating new virtual machines, monitoring the state of virtual machines, moving virtual machines between physical hosts for load balancing purposes, and facilitating backups of virtual machines. 
     One embodiment of a storage appliance  300  (or storage appliance  102 ) includes a network interface  120 , processor  122 , memory  124 , and disk  126  all in communication with each other. Network interface  120  allows storage appliance  300  to connect to one or more networks  128 . Network interface  120  may include a wireless network interface and/or a wired network interface. Processor  122  allows storage appliance  300  to execute computer readable instructions stored in memory  124  in order to perform processes described herein. Processor  122  may include one or more processing units, such as one or more CPUs and/or one or more GPUs. Memory  124  may comprise one or more types of memory (e.g., RAM, SRAM, DRAM, ROM, EEPROM, NOR Flash, NAND Flash, etc.). Disk  126  may include a hard disk drive and/or a solid-state drive. Memory  124  and disk  126  may comprise hardware storage devices. 
     In one embodiment, the storage appliance  300  may include four machines. Each of the four machines may include a multi-core CPU, 64 GB of RAM, a 400 GB SSD, three 4 TB HDDs, and a network interface controller. In this case, the four machines may be in communication with the one or more networks  128  via the four network interface controllers. The four machines may comprise four nodes of a server cluster. The server cluster may comprise a set of physical machines that are connected together via a network. The server cluster may be used for storing data associated with a plurality of virtual machines, such as backup data associated with different point-in-time versions of the virtual machines. 
     The networked computing environment  100  may provide a cloud computing environment for one or more computing devices. Cloud computing may refer to Internet-based computing, wherein shared resources, software, and/or information may be provided to one or more computing devices on-demand via the Internet. The networked computing environment  100  may comprise a cloud computing environment providing Software-as-a-Service (SaaS) or Infrastructure-as-a-Service (IaaS) services. SaaS may refer to a software distribution model in which applications are hosted by a service provider and made available to end users over the Internet. In one embodiment, the networked computing environment  100  may include a virtualized infrastructure that provides software, data processing, and/or data storage services to end users accessing the services via the networked computing environment  100 . In one example, networked computing environment  100  may provide cloud-based work productivity or business-related applications to a computing device, such as computing device  106 . The storage appliance  102  may comprise a cloud-based data management system for backing up virtual machines and/or files within a virtualized infrastructure, such as virtual machines running on server  200  or files stored on server  200 . 
     In some cases, networked computing environment  100  may provide remote access to secure applications and files stored within data center  104  from a remote computing device, such as computing device  106 . The data center  104  may use an access control application to manage remote access to protected resources, such as protected applications, databases, or files located within the data center  104 . To facilitate remote access to secure applications and files, a secure network connection may be established using a virtual private network (VPN). A VPN connection may allow a remote computing device, such as computing device  106 , to securely access data from a private network (e.g., from a company file server or mail server) using an unsecure public network or the Internet. The VPN connection may require client-side software (e.g., running on the remote computing device) to establish and maintain the VPN connection. The VPN client software may provide data encryption and encapsulation prior to the transmission of secure private network traffic through the Internet. 
     In some embodiments, the storage appliance  300  may manage the extraction and storage of virtual machine snapshots associated with different point in time versions of one or more virtual machines running within the data center  104 . A snapshot of a virtual machine may correspond with a state of the virtual machine at a particular point-in-time. In response to a restore command from the storage device  108 , the storage appliance  300  may restore a point-in-time version of a virtual machine or restore point-in-time versions of one or more files located on the virtual machine and transmit the restored data to the server  200 . In response to a mount command from the server  200 , the storage appliance  300  may allow a point-in-time version of a virtual machine to be mounted and allow the server  200  to read and/or modify data associated with the point-in-time version of the virtual machine. To improve storage density, the storage appliance  300  may deduplicate and compress data associated with different versions of a virtual machine and/or deduplicate and compress data associated with different virtual machines. To improve system performance, the storage appliance  300  may first store virtual machine snapshots received from a virtualized environment in a cache, such as a flash-based cache. The cache may also store popular data or frequently accessed data (e.g., based on a history of virtual machine restorations, incremental files associated with commonly restored virtual machine versions) and current day incremental files or incremental files corresponding with snapshots captured within the past 24 hours. 
     An incremental file may comprise a forward incremental file or a reverse incremental file. A forward incremental file may include a set of data representing changes that have occurred since an earlier point-in-time snapshot of a virtual machine. To generate a snapshot of the virtual machine corresponding with a forward incremental file, the forward incremental file may be combined with an earlier point in time snapshot of the virtual machine (e.g., the forward incremental file may be combined with the last full image of the virtual machine that was captured before the forward incremental file was captured and any other forward incremental files that were captured subsequent to the last full image and prior to the forward incremental file). A reverse incremental file may include a set of data representing changes from a later point-in-time snapshot of a virtual machine. To generate a snapshot of the virtual machine corresponding with a reverse incremental file, the reverse incremental file may be combined with a later point-in-time snapshot of the virtual machine (e.g., the reverse incremental file may be combined with the most recent snapshot of the virtual machine and any other reverse incremental files that were captured prior to the most recent snapshot and subsequent to the reverse incremental file). 
     The storage appliance  300  may provide a user interface (e.g., a web-based interface or a graphical user interface) that displays virtual machine backup information such as identifications of the virtual machines protected and the historical versions or time machine views for each of the virtual machines protected. A time machine view of a virtual machine may include snapshots of the virtual machine over a plurality of points in time. Each snapshot may comprise the state of the virtual machine at a particular point in time. Each snapshot may correspond with a different version of the virtual machine (e.g., Version 1 of a virtual machine may correspond with the state of the virtual machine at a first point in time and Version 2 of the virtual machine may correspond with the state of the virtual machine at a second point in time subsequent to the first point in time). 
     The user interface may enable an end user of the storage appliance  300  (e.g., a system administrator or a virtualization administrator) to select a particular version of a virtual machine to be restored or mounted. When a particular version of a virtual machine has been mounted, the particular version may be accessed by a client (e.g., a virtual machine, a physical machine, or a computing device) as if the particular version was local to the client. A mounted version of a virtual machine may correspond with a mount point directory (e.g., /snapshots/VM5Nersion23). In one example, the storage appliance  300  may run an NFS server and make the particular version (or a copy of the particular version) of the virtual machine accessible for reading and/or writing. The end user of the storage appliance  300  may then select the particular version to be mounted and run an application (e.g., a data analytics application) using the mounted version of the virtual machine. In another example, the particular version may be mounted as an iSCSI target. 
       FIG.  2    depicts one embodiment of server  200  of  FIG.  1   . The server  200  may comprise one server out of a plurality of servers that are networked together within a data center (e.g., data center  104 ). In one example, the plurality of servers may be positioned within one or more server racks within the data center. As depicted, the server  200  includes hardware-level components and software-level components. The hardware-level components include one or more processors  202 , one or more memory  204 , and one or more disks  206 . The software-level components include a hypervisor  208 , a virtualized infrastructure manager  222 , and one or more virtual machines, such as virtual machine  220 . The hypervisor  208  may comprise a native hypervisor or a hosted hypervisor. The hypervisor  208  may provide a virtual operating platform for running one or more virtual machines, such as virtual machine  220 . Virtual machine  220  includes a plurality of virtual hardware devices including a virtual processor  210 , a virtual memory  212 , and a virtual disk  214 . The virtual disk  214  may comprise a file stored within the one or more disks  206 . In one example, a virtual machine  220  may include a plurality of virtual disks  214 , with each virtual disk of the plurality of virtual disks  214  associated with a different file stored on the one or more disks  206 . Virtual machine  220  may include a guest operating system  216  that runs one or more applications, such as application  218 . 
     The virtualized infrastructure manager  222 , which may correspond with the virtualization manager  118  in  FIG.  1   , may run on a virtual machine or natively on the server  200 . The virtual machine may, for example, be or include the virtual machine  220  or a virtual machine separate from the server  200 . Other arrangements are possible. The virtualized infrastructure manager  222  may provide a centralized platform for managing a virtualized infrastructure that includes a plurality of virtual machines. The virtualized infrastructure manager  222  may manage the provisioning of virtual machines running within the virtualized infrastructure and provide an interface to computing devices interacting with the virtualized infrastructure. The virtualized infrastructure manager  222  may perform various virtualized infrastructure related tasks, such as cloning virtual machines, creating new virtual machines, monitoring the state of virtual machines, and facilitating backups of virtual machines. 
     In one embodiment, the server  200  may use the virtualized infrastructure manager  222  to facilitate backups for a plurality of virtual machines (e.g., eight different virtual machines) running on the server  200 . Each virtual machine running on the server  200  may run its own guest operating system and its own set of applications. Each virtual machine running on the server  200  may store its own set of files using one or more virtual disks associated with the virtual machine (e.g., each virtual machine may include two virtual disks that are used for storing data associated with the virtual machine). 
     In one embodiment, a data management application running on a storage appliance, such as storage appliance  102  in  FIG.  1    or storage appliance  300  in  FIG.  1   , may request a snapshot of a virtual machine running on server  200 . The snapshot of the virtual machine may be stored as one or more files, with each file associated with a virtual disk of the virtual machine. A snapshot of a virtual machine may correspond with a state of the virtual machine at a particular point in time. The particular point in time may be associated with a time stamp. In one example, a first snapshot of a virtual machine may correspond with a first state of the virtual machine (including the state of applications and files stored on the virtual machine) at a first point in time and a second snapshot of the virtual machine may correspond with a second state of the virtual machine at a second point in time subsequent to the first point in time. 
     In response to a request for a snapshot of a virtual machine at a particular point in time, the virtualized infrastructure manager  222  may set the virtual machine into a frozen state or store a copy of the virtual machine at the particular point in time. The virtualized infrastructure manager  222  may then transfer data associated with the virtual machine (e.g., an image of the virtual machine or a portion of the image of the virtual machine) to the storage appliance  300  or storage appliance  102 . The data associated with the virtual machine may include a set of files including a virtual disk file storing contents of a virtual disk of the virtual machine at the particular point in time and a virtual machine configuration file storing configuration settings for the virtual machine at the particular point in time. The contents of the virtual disk file may include the operating system used by the virtual machine, local applications stored on the virtual disk, and user files (e.g., images and word processing documents). In some cases, the virtualized infrastructure manager  222  may transfer a full image of the virtual machine to the storage appliance  102  or storage appliance  300  of  FIG.  1    or a plurality of data blocks corresponding with the full image (e.g., to enable a full image-level backup of the virtual machine to be stored on the storage appliance). In other cases, the virtualized infrastructure manager  222  may transfer a portion of an image of the virtual machine associated with data that has changed since an earlier point in time prior to the particular point in time or since a last snapshot of the virtual machine was taken. In one example, the virtualized infrastructure manager  222  may transfer only data associated with virtual blocks stored on a virtual disk of the virtual machine that have changed since the last snapshot of the virtual machine was taken. In one embodiment, the data management application may specify a first point in time and a second point in time and the virtualized infrastructure manager  222  may output one or more virtual data blocks associated with the virtual machine that have been modified between the first point in time and the second point in time. 
     In some embodiments, the server  200  or the hypervisor  208  may communicate with a storage appliance, such as storage appliance  102  in  FIG.  1    or storage appliance  300  in  FIG.  1   , using a distributed file system protocol such as Network File System (NFS) Version 3, or Server Message Block (SMB) protocol. The distributed file system protocol may allow the server  200  or the hypervisor  208  to access, read, write, or modify files stored on the storage appliance as if the files were locally stored on the server  200 . The distributed file system protocol may allow the server  200  or the hypervisor  208  to mount a directory or a portion of a file system located within the storage appliance. 
       FIG.  3    depicts one embodiment of storage appliance  300  in  FIG.  1   . The storage appliance may include a plurality of physical machines that may be grouped together and presented as a single computing system. Each physical machine of the plurality of physical machines may comprise a node in a cluster (e.g., a failover cluster). In one example, the storage appliance may be positioned within a server rack within a data center. As depicted, the storage appliance  300  includes hardware-level components and software-level components. The hardware-level components include one or more physical machines, such as physical machine  314  and physical machine  324 . The physical machine  314  includes a network interface  316 , processor  318 , memory  320 , and disk  322  all in communication with each other. Processor  318  allows physical machine  314  to execute computer readable instructions stored in memory  320  to perform processes described herein. Disk  322  may include a hard disk drive and/or a solid-state drive. The physical machine  324  includes a network interface  326 , processor  328 , memory  330 , and disk  332  all in communication with each other. Processor  328  allows physical machine  324  to execute computer readable instructions stored in memory  330  to perform processes described herein. Disk  332  may include a hard disk drive and/or a solid-state drive. In some cases, disk  332  may include a flash-based SSD or a hybrid HDD/SSD drive. In one embodiment, the storage appliance  300  may include a plurality of physical machines arranged in a cluster (e.g., eight machines in a cluster). Each of the plurality of physical machines may include a plurality of multi-core CPUs, 108 GB of RAM, a 500 GB SSD, four 4 TB HDDs, and a network interface controller. 
     In some embodiments, the plurality of physical machines may be used to implement a cluster-based network fileserver. The cluster-based network file server may neither require nor use a front-end load balancer. One issue with using a front-end load balancer to host the IP address for the cluster-based network file server and to forward requests to the nodes of the cluster-based network file server is that the front-end load balancer comprises a single point of failure for the cluster-based network file server. In some cases, the file system protocol used by a server, such as server  200  in  FIG.  1   , or a hypervisor, such as hypervisor  208  in  FIG.  2   , to communicate with the storage appliance  300  may not provide a failover mechanism (e.g., NFS Version 3). In the case that no failover mechanism is provided on the client side, the hypervisor may not be able to connect to a new node within a cluster in the event that the node connected to the hypervisor fails. 
     In some embodiments, each node in a cluster may be connected to each other via a network and may be associated with one or more IP addresses (e.g., two different IP addresses may be assigned to each node). In one example, each node in the cluster may be assigned a permanent IP address and a floating IP address and may be accessed using either the permanent IP address or the floating IP address. In this case, a hypervisor, such as hypervisor  208  in  FIG.  2   , may be configured with a first floating IP address associated with a first node in the cluster. The hypervisor may connect to the cluster using the first floating IP address. In one example, the hypervisor may communicate with the cluster using the NFS Version 3 protocol. Each node in the cluster may run a Virtual Router Redundancy Protocol (VRRP) daemon. A daemon may comprise a background process. Each VRRP daemon may include a list of all floating IP addresses available within the cluster. In the event that the first node associated with the first floating IP address fails, one of the VRRP daemons may automatically assume or pick up the first floating IP address if no other VRRP daemon has already assumed the first floating IP address. Therefore, if the first node in the cluster fails or otherwise goes down, then one of the remaining VRRP daemons running on the other nodes in the cluster may assume the first floating IP address that is used by the hypervisor for communicating with the cluster. 
     In order to determine which of the other nodes in the cluster will assume the first floating IP address, a VRRP priority may be established. In one example, given a number (N) of nodes in a cluster from node(0) to node(N−1), for a floating IP address (i), the VRRP priority of nodeG) may be G-i) modulo N. In another example, given a number (N) of nodes in a cluster from node(0) to node(N−1), for a floating IP address (i), the VRRP priority of nodeG) may be (i-j) modulo N. In these cases, nodeG) will assume floating IP address (i) only if its VRRP priority is higher than that of any other node in the cluster that is alive and announcing itself on the network. Thus, if a node fails, then there may be a clear priority ordering for determining which other node in the cluster will take over the failed node&#39;s floating IP address. 
     In some cases, a cluster may include a plurality of nodes and each node of the plurality of nodes may be assigned a different floating IP address. In this case, a first hypervisor may be configured with a first floating IP address associated with a first node in the cluster, a second hypervisor may be configured with a second floating IP address associated with a second node in the cluster, and a third hypervisor may be configured with a third floating IP address associated with a third node in the cluster. 
     As depicted in  FIG.  3   , the software-level components of the storage appliance  300  may include data management system  302 , a virtualization interface  304 , a distributed job scheduler  308 , a distributed metadata store  310 , a distributed file system  312 , and one or more virtual machine search indexes, such as virtual machine search index  306 . In one embodiment, the software-level components of the storage appliance  300  may be run using a dedicated hardware-based appliance. In another embodiment, the software-level components of the storage appliance  300  may be run from the cloud (e.g., the software-level components may be installed on a cloud service provider). 
     In some cases, the data storage across a plurality of nodes in a cluster (e.g., the data storage available from the one or more physical machine (e.g., physical machine  314  and physical machine  324 )) may be aggregated and made available over a single file system namespace (e.g., /snapshots/). A directory for each virtual machine protected using the storage appliance  300  may be created (e.g., the directory for Virtual Machine A may be /snapshots/VM_A). Snapshots and other data associated with a virtual machine may reside within the directory for the virtual machine. In one example, snapshots of a virtual machine may be stored in subdirectories of the directory (e.g., a first snapshot of Virtual Machine A may reside in /snapshots/VM_A/s1/ and a second snapshot of Virtual Machine A may reside in /snapshots/VM_A/s2/). 
     The distributed file system  312  may present itself as a single file system, in which as new physical machines or nodes are added to the storage appliance  300 , the cluster may automatically discover the additional nodes and automatically increase the available capacity of the file system for storing files and other data. Each file stored in the distributed file system  312  may be partitioned into one or more chunks or shards. Each of the one or more chunks may be stored within the distributed file system  312  as a separate file. The files stored within the distributed file system  312  may be replicated or mirrored over a plurality of physical machines, thereby creating a load-balanced and fault tolerant distributed file system. In one example, storage appliance  300  may include ten physical machines arranged as a failover cluster and a first file corresponding with a snapshot of a virtual machine (e.g., /snapshots/VM_A/s1/s1.full) may be replicated and stored on three of the ten machines. 
     The distributed metadata store  310  may include a distributed database management system that provides high availability without a single point of failure. In one embodiment, the distributed metadata store  310  may comprise a database, such as a distributed document-oriented database. The distributed metadata store  310  may be used as a distributed key value storage system. In one example, the distributed metadata store  310  may comprise a distributed NoSQL key value store database. In some cases, the distributed metadata store  310  may include a partitioned row store, in which rows are organized into tables or other collections of related data held within a structured format within the key value store database. A table (or a set of tables) may be used to store metadata information associated with one or more files stored within the distributed file system  312 . The metadata information may include the name of a file, a size of the file, file permissions associated with the file, when the file was last modified, and file mapping information associated with an identification of the location of the file stored within a cluster of physical machines. In one embodiment, a new file corresponding with a snapshot of a virtual machine may be stored within the distributed file system  312  and metadata associated with the new file may be stored within the distributed metadata store  310 . The distributed metadata store  310  may also be used to store a backup schedule for the virtual machine and a list of snapshots for the virtual machine that are stored using the storage appliance  300 . 
     In some cases, the distributed metadata store  310  may be used to manage one or more versions of a virtual machine. Each version of the virtual machine may correspond with a full image snapshot of the virtual machine stored within the distributed file system  312  or an incremental snapshot of the virtual machine (e.g., a forward incremental or reverse incremental) stored within the distributed file system  312 . In one embodiment, the one or more versions of the virtual machine may correspond with a plurality of files. The plurality of files may include a single full image snapshot of the virtual machine and one or more incremental aspects derived from the single full image snapshot. The single full image snapshot of the virtual machine may be stored using a first storage device of a first type (e.g., a HDD) and the one or more incremental aspects derived from the single full image snapshot may be stored using a second storage device of a second type (e.g., an SSD). In this case, only a single full image needs to be stored and each version of the virtual machine may be generated from the single full image or the single full image combined with a subset of the one or more incremental aspects. Furthermore, each version of the virtual machine may be generated by performing a sequential read from the first storage device (e.g., reading a single file from a HDD) to acquire the full image and, in parallel, performing one or more reads from the second storage device (e.g., performing fast random reads from an SSD) to acquire the one or more incremental aspects. 
     The distributed job scheduler  308  may be used for scheduling backup jobs that acquire and store virtual machine snapshots for one or more virtual machines overtime. The distributed job scheduler  308  may follow a backup schedule to back up an entire image of a virtual machine at a particular point in time or one or more virtual disks associated with the virtual machine at the particular point in time. In one example, the backup schedule may specify that the virtual machine be backed up at a snapshot capture frequency, such as every two hours or every 24 hours. Each backup job may be associated with one or more tasks to be performed in a sequence. Each of the one or more tasks associated with a job may be run on a particular node within a cluster. In some cases, the distributed job scheduler  308  may schedule a specific job to be run on a particular node based on data stored on the particular node. For example, the distributed job scheduler  308  may schedule a virtual machine snapshot job to be run on a node in a cluster that is used to store snapshots of the virtual machine in order to reduce network congestion. 
     The distributed job scheduler  308  may comprise a distributed fault tolerant job scheduler, in which jobs affected by node failures are recovered and rescheduled to be run on available nodes. In one embodiment, the distributed job scheduler  308  may be fully decentralized and implemented without the existence of a master node. The distributed job scheduler  308  may run job scheduling processes on each node in a cluster or on a plurality of nodes in the cluster. In one example, the distributed job scheduler  308  may run a first set of job scheduling processes on a first node in the cluster, a second set of job scheduling processes on a second node in the cluster, and a third set of job scheduling processes on a third node in the cluster. The first set of job scheduling processes, the second set of job scheduling processes, and the third set of job scheduling processes may store information regarding jobs, schedules, and the states of jobs using a metadata store, such as distributed metadata store  310 . In the event that the first node running the first set of job scheduling processes fails (e.g., due to a network failure or a physical machine failure), the states of the jobs managed by the first set of job scheduling processes may fail to be updated within a threshold period of time (e.g., a job may fail to be completed within 30 seconds or within minutes from being started). In response to detecting jobs that have failed to be updated within the threshold period of time, the distributed job scheduler  308  may undo and restart the failed jobs on available nodes within the cluster. 
     The job scheduling processes running on at least a plurality of nodes in a cluster (e.g., on each available node in the cluster) may manage the scheduling and execution of a plurality of jobs. The job scheduling processes may include run processes for running jobs, cleanup processes for cleaning up failed tasks, and rollback processes for rolling-back or undoing any actions or tasks performed by failed jobs. In one embodiment, the job scheduling processes may detect that a particular task for a particular job has failed and in response may perform a cleanup process to clean up or remove the effects of the particular task and then perform a rollback process that processes one or more completed tasks for the particular job in reverse order to undo the effects of the one or more completed tasks. Once the particular job with the failed task has been undone, the job scheduling processes may restart the particular job on an available node in the cluster. 
     The distributed job scheduler  308  may manage a job in which a series of tasks associated with the job are to be performed atomically (i.e., partial execution of the series of tasks is not permitted). If the series of tasks cannot be completely executed or there is any failure that occurs to one of the series of tasks during execution (e.g., a hard disk associated with a physical machine fails or a network connection to the physical machine fails), then the state of a data management system may be returned to a state as if none of the series of tasks was ever performed. The series of tasks may correspond with an ordering of tasks for the series of tasks and the distributed job scheduler  308  may ensure that each task of the series of tasks is executed based on the ordering of tasks. Tasks that do not have dependencies with each other may be executed in parallel. 
     In some cases, the distributed job scheduler  308  may schedule each task of a series of tasks to be performed on a specific node in a cluster. In other cases, the distributed job scheduler  308  may schedule a first task of the series of tasks to be performed on a first node in a cluster and a second task of the series of tasks to be performed on a second node in the cluster. In these cases, the first task may have to operate on a first set of data (e.g., a first file stored in a file system) stored on the first node and the second task may have to operate on a second set of data (e.g., metadata related to the first file that is stored in a database) stored on the second node. In some embodiments, one or more tasks associated with a job may have an affinity to a specific node in a cluster. 
     In one example, if the one or more tasks require access to a database that has been replicated on three nodes in a cluster, then the one or more tasks may be executed on one of the three nodes. In another example, if the one or more tasks require access to multiple chunks of data associated with a virtual disk that has been replicated over four nodes in a cluster, then the one or more tasks may be executed on one of the four nodes. Thus, the distributed job scheduler  308  may assign one or more tasks associated with a job to be executed on a particular node in a cluster based on the location of data required to be accessed by the one or more tasks. 
     In one embodiment, the distributed job scheduler  308  may manage a first job associated with capturing and storing a snapshot of a virtual machine periodically (e.g., every 30 minutes). The first job may include one or more tasks, such as communicating with a virtualized infrastructure manager, such as the virtualized infrastructure manager  222  in  FIG.  2   , to create a frozen copy of the virtual machine and to transfer one or more chunks (or one or more files) associated with the frozen copy to a storage appliance, such as storage appliance  300  in  FIG.  1   . The one or more tasks may also include generating metadata for the one or more chunks, storing the metadata using the distributed metadata store  31010 , storing the one or more chunks within the distributed file system  312 , and communicating with the virtualized infrastructure manager  222  that the frozen copy of the virtual machine may be unfrozen or released from a frozen state. The metadata for a first chunk of the one or more chunks may include information specifying a version of the virtual machine associated with the frozen copy, a time associated with the version (e.g., the snapshot of the virtual machine was taken at 5:30 p.m. on Jun. 29, 2018), and a file path to where the first chunk is stored within the distributed file system  92  (e.g., the first chunk is located at /snapshotsNM_B/s1/s1.chunk1). The one or more tasks may also include deduplication, compression (e.g., using a lossless data compression algorithm such as LZ4 or LZ77), decompression, encryption (e.g., using a symmetric key algorithm such as Triple DES or AES-256), and decryption related tasks. 
     The virtualization interface  304  may provide an interface for communicating with a virtualized infrastructure manager managing a virtualization infrastructure, such as virtualized infrastructure manager  222  in  FIG.  2   , and requesting data associated with virtual machine snapshots from the virtualization infrastructure. The virtualization interface  304  may communicate with the virtualized infrastructure manager using an Application Programming Interface (API) for accessing the virtualized infrastructure manager (e.g., to communicate a request for a snapshot of a virtual machine). In this case, storage appliance  300  may request and receive data from a virtualized infrastructure without requiring agent software to be installed or running on virtual machines within the virtualized infrastructure. The virtualization interface  304  may request data associated with virtual blocks stored on a virtual disk of the virtual machine that have changed since a last snapshot of the virtual machine was taken or since a specified prior point in time. Therefore, in some cases, if a snapshot of a virtual machine is the first snapshot taken of the virtual machine, then a full image of the virtual machine may be transferred to the storage appliance. However, if the snapshot of the virtual machine is not the first snapshot taken of the virtual machine, then only the data blocks of the virtual machine that have changed since a prior snapshot was taken may be transferred to the storage appliance. 
     The virtual machine search index  306  may include a list of files that have been stored using a virtual machine and a version history for each of the files in the list. Each version of a file may be mapped to the earliest point-in-time snapshot of the virtual machine that includes the version of the file or to a snapshot of the virtual machine that includes the version of the file (e.g., the latest point in time snapshot of the virtual machine that includes the version of the file). In one example, the virtual machine search index  306  may be used to identify a version of the virtual machine that includes a particular version of a file (e.g., a particular version of a database, a spreadsheet, or a word processing document). In some cases, each of the virtual machines that are backed up or protected using storage appliance  300  may have a corresponding virtual machine search index. 
     In one embodiment, as each snapshot of a virtual machine is ingested, each virtual disk associated with the virtual machine is parsed in order to identify a file system type associated with the virtual disk and to extract metadata (e.g., file system metadata) for each file stored on the virtual disk. The metadata may include information for locating and retrieving each file from the virtual disk. The metadata may also include a name of a file, the size of the file, the last time at which the file was modified, and a content checksum for the file. Each file that has been added, deleted, or modified since a previous snapshot was captured may be determined using the metadata (e.g., by comparing the time at which a file was last modified with a time associated with the previous snapshot). Thus, for every file that has existed within any of the snapshots of the virtual machine, a virtual machine search index may be used to identify when the file was first created (e.g., corresponding with a first version of the file) and at what times the file was modified (e.g., corresponding with subsequent versions of the file). Each version of the file may be mapped to a particular version of the virtual machine that stores that version of the file. 
     In some cases, if a virtual machine includes a plurality of virtual disks, then a virtual machine search index may be generated for each virtual disk of the plurality of virtual disks. For example, a first virtual machine search index may catalog and map files located on a first virtual disk of the plurality of virtual disks and a second virtual machine search index may catalog and map files located on a second virtual disk of the plurality of virtual disks. In this case, a global file catalog or a global virtual machine search index for the virtual machine may include the first virtual machine search index and the second virtual machine search index. A global file catalog may be stored for each virtual machine backed up by a storage appliance within a file system, such as distributed file system  312  in  FIG.  3   . 
     The data management system  302  may comprise an application running on the storage appliance  300  that manages and stores one or more snapshots of a virtual machine. In one example, the data management system  302  may comprise a highest-level layer in an integrated software stack running on the storage appliance. The integrated software stack may include the data management system  302 , the virtualization interface  304 , the distributed job scheduler  308 , the distributed metadata store  310 , and the distributed file system  312 . 
     In some cases, the integrated software stack may run on other computing devices, such as a server or computing device  106  in  FIG.  1   . The data management system  302  may use the virtualization interface  304 , the distributed job scheduler  308 , the distributed metadata store  310 , and the distributed file system  312  to manage and store one or more snapshots of a virtual machine. Each snapshot of the virtual machine may correspond with a point-in-time version of the virtual machine. The data management system  302  may generate and manage a list of versions for the virtual machine. Each version of the virtual machine may map to or reference one or more chunks and/or one or more files stored within the distributed file system  312 . Combined together, the one or more chunks and/or the one or more files stored within the distributed file system  312  may comprise a full image of the version of the virtual machine. 
       FIG.  4    is a block diagram illustrating components of a computer system  400 , in accordance with some example embodiments. The computer system  400  may reside in the data center  104  (e.g., on the server  200  or the storage appliance  300 ) or may be external to the data center  104  (e.g., residing on the storage appliance  102 , the computing device  106 , or some other location). Alternatively, the computer system  400  may be distributed instead of residing on a single device. 
     In some example embodiments, the computer system  400  comprises one or more cloud computing platform nodes  410  (e.g., cloud computing platforms  410 - 1  to  410 -N). Each cloud computing platform node  410  may comprise one or more software applications  412 , a user space file system  414 , a file server  416 , a disk-based data storage  418 , and an object store connector  420 . Users of the cloud computing platform node  410  may use the application(s)  412 , resulting in the generation and modification of data, which may be persisted by the cloud computing platform node  410 . For example, in response to user actions on the application(s)  412 , the application(s)  412  may issue requests to the user space file system to write data to a file and read data from a file. The user space file system  414  may comprise a file system in which data and metadata are provided by an ordinary user space process. The user space file system  414  can be accessed normally through a kernel interface. In some example embodiments, the user space file system  414  comprises a software interface (e.g., a software interface for Unix and Unix-like computer operating systems) that lets non-privileged users create their own file systems without editing kernel code, which may be achieved by running file system code in user space while the software interface provides only a bridge to the actual kernel interfaces. 
     The user space file system  414  may provide an interface for file operations, passing the requested operations to one or more other layers for processing. In some example embodiments, the user space file system  414  is configured to receive a first request to write a first set of data to a file. The first request may originate and be received from the application(a)  412 . In some example embodiments, the first set of data comprises snapshot data. However, the first set of data may comprise other types of snapshot as well. 
     In some example embodiments, the user space file system  414  is configured to write the first set of data to the file in a cloud-based key-value object store  430  based on the receiving of the first request to write the first set of data to the file. For example, in response to receiving the first request, the user space file system  414  may use the identification of the file that is included in the first request to determine where to write the first set of data, and then write the first set of data to that determined location in the cloud-based key-value object store  430 . 
     The user space file system  414  may manage metadata and actual data. The metadata may comprise index node (inode) data. An inode is a data structure in a Unix-style file system that describes a file-system object such as a file or a directory. Each inode stores the attributes and disk block locations of the object&#39;s data. File system object attributes may include metadata (e.g., times of last change, access, modification), as well as owner and permission data. In some example embodiments, the user space file system  414  stores the metadata locally on the disk-based data storage  418  and stores the actual data on the cloud-based key value object store  430 . The disk-based data storage  418  may comprise a solid-state disk. However, other types of disk-based data storage  418  are also within the scope of the present disclosure. The user space file system  414  may write the metadata information of a file into a metadata store that resides in the disk-based data storage  418 , and all of the actual data of the file may be divided into chunks of 64 MB by the user space file system  414  and written into the cloud-based key-value object store  430 . 
     In some example embodiments, the user space file system  414  is configured to use the disk-based data storage  418  as a write buffer and a read cache for data being written to and read from the cloud-based key-value object store  430 . In this respect, the user space file system  414  may use the disk-based data storage  418  as a staging area to provide improvement to read and write throughput and reduce the number of read (e.g., GET) and write (e.g., PUT) calls to the cloud-based key-value object store  430 . 
     In some example embodiments, the writing of the first set of data to the file in the cloud-based object store comprises writing the first set of data to the disk-based data storage  418 , and then writing the first set of data from the disk-based data storage  418  to the file in the cloud-based key-value object store  430 . The user space file system  414  may divide the data of a file into chunks of 64 MB at the physical layer. These chunks may also be referred to as stripes. Each chunk may correspond to one key in the cloud-based key-value object store  430 . The user space file system  414  may write data to and read data from the disk-based data storage  418  by communicating instructions to the file server  416  to write and read the data to and from the disk-based data storage  418 . Additionally, the user space file system  414  may write data to and read data from the cloud-based key-value object store  430  by communicating instructions to the object store connector  420  to write and read date to and from the cloud-based key-value object store  430 . 
     In some example embodiment, the writing of the first set of data from the disk-based data storage  418  to the file in the cloud-based key-value object store  430  by the user space file system  414  comprises determining that a predetermined amount of time has passed since the first set of data has been written to the disk-based data storage  418  without a request to write data to the file having been received by the user space file system  414 , and then, in response to the determining the predetermined amount of time has passed, writing the first set of data from the disk-based data storage  418  to the file in the cloud-based key-value object store  430 . This feature of writing data to the cloud-based key-value object store  430  based on a determination of inactivity for the predetermined amount of time will be discussed in further detail below with respect to the workflow  500  of  FIG.  5   . 
     In some example embodiments, the writing the first set of data from the disk-based data storage  418  to the file in the cloud-based key-value object store  430  comprises the user space file system  414  determining that a stripe in the disk-based data storage  418  is closed, where the stripe includes the first set of data, and then, in response to the determining that the stripe in the disk-based data storage  418  is closed, appending the stripe to existing data in the file in the cloud-based key-value object store  430 . This feature of writing data to the cloud-based key-value object store  430  based on the stripe being closed will be discussed in further detail below with respect to the workflow  600  of  FIG.  6   . 
     In some example embodiments, the writing the first set of data to the file in the cloud-based key-value object store  430  comprises the user space file system  414  dividing the first set of data into chunks of data, and then writing the chunks of data to the file in the cloud-based key-value object store in parallel. For example, if the first set of data is divided into ten chunks of data, then the user space file system  414  may perform ten writes to the cloud-based key-value object store  430  in parallel, with each one of the ten writes writing a corresponding one of the ten chunks of data. 
     In some example embodiments, the user space file system  414  is configured to receive a second request to read a second set of data from the file. The second request to read the second set of data may be part of a data recovery process to recover the second set of data from the file. However, the second request may be part of some other type of process as well. In some example embodiments, the user space file system  414  is configured to fetch the second set of data from the file in the cloud-based key-value object store  430  based on the receiving of the second request to read the second set of data from the file. For example, in response to receiving the second request, the user space file system  414  may use the identification of the file that is included in the second request to determine from where to read the second set of data, and then read the second set of data from that determined location in the cloud-based key-value object store  430 . 
     In some example embodiments, the user space file system  414  is configured to store the fetched second set of data in a cache of a disk-based data storage  418 . The user space file system  414  may then transmit the fetched second set of data to the component from which the second request originated (e.g., from the requesting component), and also store the fetched second set of data in the cache of the disk-based data storage  418  for subsequent use in responding to a similar read request for that second set of data at a future time. For example, the user space file system  414  may receive a third request to read the second set of data from the file. The third request to read the second set of data may be part of a data recovery process to recover the second set of data from the file. However, the third request may be part of some other type of process as well. The user space file system  414  may read the second set of data from the cache of the disk-based data storage  418  based on the receiving of the third request to read the second set of data from the file. In some example embodiments, the user space file system  414  reads the second set of data from the cache of the disk-based data storage  418  instead of from the cloud-based key-value object store  430  in response to receiving the third request. The read second set of data may then be provided to the component from which the third request originated. 
     In some example embodiments, the user space file system  414  implements two types of writers—(1) an append-only writer that allows only append-only writes and (2) an in-place writer that allows writes in any pattern.  FIG.  5    illustrates a workflow  500  for writing data to a file in a cloud-based key-value object store, in accordance with some example embodiments. In the workflow  500  of  FIG.  5   , the writing of the data is in the form of an in-place write. In the example embodiment of  FIG.  5   , any incoming write is first buffered into a small in-memory buffer of the user space file system  414 . If the buffer is full or a sync is issued, the user space file system  414  writes the data onto the disk-based data storage  418 , which acts as a second layer buffer. If the second layer buffer of the disk-based data storage  418  is full or the chunk is inactive (e.g., has not been written to for a predetermined amount of time), then the user space file system  414  moves the chunk into the cloud-based key-value object store  430 . In some example embodiments, the writes to the disk-based data storage  418  are performed in a distributed manner utilizing capacity across all nodes. If there are new incoming writes after a long period of inactivity for the chunk, it is likely that the chunk will not be available on the staging area of the disk-based data storage  418 . In this case, the user space file system  414  may re-fetch the chunk from the cloud-based key-value object store  430  onto the staging area of the disk-based data storage  418  and delete the corresponding object in the cloud-based key-value object store  430  before starting the new writes. The re-fetched chunk may remain in the staging area of the disk-based data storage  418  again, until after another period of inactivity. 
       FIG.  6    illustrates another workflow  600  for writing data to a file in a cloud-based key-value object store, in accordance with some example embodiments. In the workflow  600  of  FIG.  6   , the writing of the data is in the form of an append-only write. In some example embodiments, append-only writes are sequential, and any writes to a particular inode are put into a single chunk at a time. The contents of the chunk may be in memory as part of a global memory pool and may be persisted to the staging area of the disk-based data storage  418  only if the chunk is synced or if the global in-memory pool of the user space file system  414  is full and needs to free up some data. If none of these conditions are satisfied for the lifetime of the stripe, the user space file system  414  may bypass the staging area of the disk-based data storage  418  and directly write the chunk from in-memory to the cloud-based key-value object store  430  on closing the stripe (e.g., when all 64 MB of the stripe has been written). This processing of an append-only write is different from the processing of in-place write because it is known with append-only files that the chunks are immutable once they have written all of their 64 MB. 
     In some example embodiments, if any of the above conditions are satisfied, then the chunk is kept in the staging area of the disk-based data storage  418 , and the chunk is persisted into the cloud-based key-value object store  430  when the stripe is closed. The upper layers may control when to close a stripe, such as when the file is finalized (e.g., made immutable) and the write is in the last stripe, or when the user space file system  414  has finished writing the 64 MB in the stripe. If either of these two conditions is satisfied, then the user space file system  414  closes the current stripe and moves on to the next stripe. 
       FIG.  7    illustrates a workflow  700  for reading data from a file in a cloud-based key-value object store, in accordance with some example embodiments. In some example embodiments, reads may be performed while an active stripe is being written, after a stripe is closed and put into the cloud-based key-value object store  430  or after a stripe is put into the cloud-based key-value object store  430  due to inactivity. In all of these cases, the read workflow  700  is identical. The workflow  700  always tries to read from the staging area of the disk-based data storage  418  (e.g., if the chunks are available), or otherwise fetches the data from the cloud-based key-value object store  430  using read ahead and puts it as an immutable read cache in the staging area of the disk-based data storage  418 . In some example embodiments, this read cache resides in a different location in the staging area of the disk-based data storage  418  from the write chunks, as it is purgeable, whereas the write chunks are persistent. 
     Reading from the cloud-based key-value object store  430  into the staging area of the disk-based data storage  418  for every single read is sub-optimal and costly, since the latency of reads from the cloud-based key-value object store  430  may be very high. Therefore, the user space file system  414  may employ a smart algorithm to prefetch selective data from the chunks in the cloud-based key-value object store onto the read cache in the staging area of the disk-based data storage  418 . In some example embodiments, the user space file system  414  always prefetches at least a minimum amount (e.g., 2 MB) of data from the cloud-based key-value object store  430  into the staging area of the dis-based data storage  418  for any reads and serves reads from the prefetched data in the staging area of the disk-based data storage  418 . 
     The staging area of the disk-based data storage  418  is a scarce resource, and the user space file system  414  may skip the use of the staging area wherever possible. For example, if the data is only being written, and not synced or read again, the user space file system  414  may directly put it from the memory of the user space file system  414  to the cloud-based key-value object store  430  without going through the staging area of the disk-based data storage  418 . Similarly, for reads, the user space file system  414  may read directly from the cloud-based key-value object store  430  to the memory of the user space file system  414 , if all of the prefetched data is read almost immediately. 
     In some example embodiments, priorities have been assigned to all of the read and write workloads based on their importance (e.g., BACKGROUND&lt;SLA_BASED&lt;USER_DRIVEN). The user space file system  414  may use these priorities when sending GET and PUT requests to the cloud-based key-value object store  430  and sends the requests in priority order and also throttles the additional requests that are determined to be beyond what the cloud-based key-value object store  430  can support per second. 
     Since the staging area of the disk-based data storage  418  is a scarce resource, the user space file system  414  may use a staging area space manager to control the reads and writes. The staging area space manager may operate on every node and implement the following features. The staging area space manager may know whether a chunk is read or write, so it does not evict the write chunks when full. The staging area space manager may use an LRU cache for chunks cached for reading on the staging area disk, and may implement eviction if more than 90% of the staging area size is being used. The staging area space manager may reserve a minimum of 20% of the staging area for reading chunks at any point of time, and beyond that use LRU. The staging area space manager may throttle writes when the staging area write buffer consumption goes beyond 50% to slow down clients when the staging area is under load. The throttling may be very low to start with and increase exponentially based on increasing the usage beyond 50%. The staging area space manager may persist inactive write chunks (chunks that have not been written to for over X mins) into the cloud-based key-value object store  430 . 
       FIG.  8    is a flowchart illustrating a method  800  of backing a file system with a cloud-based object store, in accordance with some example embodiments. The method  800  can be performed by processing logic that can comprise hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (e.g., instructions run on a processing device), or a combination thereof. In one example embodiment, one or more of the operations of the method  800  are performed by the user space file system  414  of  FIG.  4   . 
     At operation  810 , the user space file system  414  receives a first request to write a first set of data to a file. In some example embodiments, the first set of data comprises snapshot data. However, the first set of data may comprise other types of snapshot as well. 
     At operation  820 , the user space file system  414  writes the first set of data to the file in a cloud-based key-value object store based on the receiving of the first request to write the first set of data to the file. For example, in response to receiving the first request, the user space file system  414  may use the identification of the file that is included in the first request to determine where to write the first set of data, and then write the first set of data to that determined location. 
     In some example embodiments, the writing of the first set of data to the file in the cloud-based object store comprises writing the first set of data to a disk-based data storage, and then writing the first set of data from the disk-based data storage to the file in the cloud-based key-value object store. 
     In some example embodiments, the writing the first set of data from the disk-based data storage to the file in the cloud-based key-value object store comprises: determining that a predetermined amount of time has passed since the first set of data has been written to the disk-based data storage without a request to write data to the file having been received; and in response to the determining the predetermined amount of time has passed, writing the first set of data from the disk-based data storage to the file in the cloud-based key-value object store. 
     In some example embodiments, the writing the first set of data from the disk-based data storage to the file in the cloud-based key-value object store comprises: determining that a stripe in the disk-based data storage is closed, the stripe including the first set of data; and in response to the determining that the stripe in the disk-based data storage is closed, appending the stripe to existing data in the file in the cloud-based key-value object store. In some example embodiments, the disk-based data storage comprises a solid-state disk. However, other types of disk-based data storage are also within the scope of the present disclosure. 
     In some example embodiments, the writing the first set of data to the file in the cloud-based key-value object store comprises dividing the first set of data into chunks of data, and then writing the chunks of data to the file in the cloud-based key-value object store in parallel. For example, if the first set of data is divided into ten chunks of data, then the user space file system may perform ten writes to the cloud-based key-value object store in parallel, with each one of the ten writes writing a corresponding one of the ten chunks of data. 
     At operation  830 , the user space file system  414  receives a second request to read a second set of data from the file. The second request to read the second set of data may be part of a data recovery process to recover the second set of data from the file. However, the second request may be part of some other type of process as well. 
     At operation  840 , the user space file system  414  fetches the second set of data from the file in the cloud-based key-value object store based on the receiving of the second request to read the second set of data from the file. For example, in response to receiving the second request, the user space file system  414  may use the identification of the file that is included in the second request to determine from where to read the second set of data, and then read the second set of data from that determined location. 
     At operation  850 , the user space file system  414  stores the fetched second set of data in a cache of a disk-based data storage. In some example embodiments, the user space file system  414  transmits the fetched second set of data to the component from which the second request originated (e.g., from the requesting component), and also stores the fetched second set of data in the cache of the disk-based data storage for subsequent use in responding to a similar read request. 
     At operation  860 , the user space file system  414  receives a third request to read the second set of data from the file. The third request to read the second set of data may be part of a data recovery process to recover the second set of data from the file. However, the third request may be part of some other type of process as well. 
     At operation  870 , the user space file system  414  reads the second set of data from the cache of the disk-based data storage based on the receiving of the third request to read the second set of data from the file. In some example embodiments, the user space file system  414  reads the second set of data from the cache of the disk-based data storage instead of from the cloud-based key-value object store in response to receiving the third request. The read second set of data may then be provided to the component from which the third request originated. 
     It is contemplated that any of the other features described within the present disclosure can be incorporated into the method  800 . 
     In view of the disclosure above, various examples are set forth below. It should be noted that one or more features of an example, taken in isolation or combination, should be considered within the disclosure of this application. 
     Example 1 includes a computer-implemented method performed by a computer system having a memory and at least one hardware processor, the computer-implemented method comprising: receiving, by a user space file system, a first request to write a first set of data to a file; based on the receiving of the first request to write the first set of data to the file, writing, by the user space file system, the first set of data to the file in a cloud-based key-value object store; receiving, by the user space file system, a second request to read a second set of data from the file; and based on the receiving of the second request to read the second set of data from the file, fetching, by the user space file system, the second set of data from the file in the cloud-based key-value object store. 
     Example 2 includes the computer-implemented method of example 1, wherein the writing of the first set of data to the file in the cloud-based object store comprises: writing, by the user space file system, the first set of data to a disk-based data storage; and writing, by the user space file system, the first set of data from the disk-based data storage to the file in the cloud-based key-value object store. 
     Example 3 includes the computer-implemented method of example 1 or example 2, wherein the writing the first set of data from the disk-based data storage to the file in the cloud-based key-value object store comprises: determining that a predetermined amount of time has passed since the first set of data has been written to the disk-based data storage without a request to write data to the file having been received; and in response to the determining the predetermined amount of time has passed, writing the first set of data from the disk-based data storage to the file in the cloud-based key-value object store. 
     Example 4 includes the computer-implemented method of any one of examples 1 to 3, wherein the writing the first set of data from the disk-based data storage to the file in the cloud-based key-value object store comprises: determining that a stripe in the disk-based data storage is closed, the stripe including the first set of data; and in response to the determining that the stripe in the disk-based data storage is closed, appending the stripe to existing data in the file in the cloud-based key-value object store. 
     Example 5 includes the computer-implemented method of any one of examples 1 to 4, further comprising: storing, by the user space file system, the fetched second set of data in a cache of a disk-based data storage; receiving, by the user space file system, a third request to read the second set of data from the file; and based on the receiving of the third request to read the second set of data from the file, reading, by the user space file system, the second set of data from the cache of the disk-based data storage. 
     Example 6 includes the computer-implemented method of any one of examples 1 to 5, wherein the writing the first set of data to the file in the cloud-based key-value object store comprises: dividing the first set of data into chunks of data; and writing the chunks of data to the file in the cloud-based key-value object store in parallel. 
     Example 7 includes the computer-implemented method of any one of examples 1 to 6, wherein the first set of data comprises snapshot data. 
     Example 8 includes the computer-implemented method of any one of examples 1 to 7, wherein the disk-based data storage comprises a solid-state disk. 
     Example 9 includes a system comprising: at least one processor; and a non-transitory computer-readable medium storing executable instructions that, when executed, cause the at least one processor to perform the method of any one of examples 1 to 8. 
     Example 10 includes a non-transitory machine-readable storage medium, tangibly embodying a set of instructions that, when executed by at least one processor, causes the at least one processor to perform the method of any one of examples 1 to 8. 
     Example 11 includes a machine-readable medium carrying a set of instructions that, when executed by at least one processor, causes the at least one processor to carry out the method of any one of examples 1 to 8. 
     Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied on a machine-readable medium) or hardware modules. A “hardware module” is a tangible unit capable of performing certain operations and may be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein. 
     In some embodiments, a hardware module may be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware module may include dedicated circuitry or logic that is permanently configured to perform certain operations. For example, a hardware module may be a special-purpose processor, such as a Field-Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC). A hardware module may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware module may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware modules become specific machines (or specific components of a machine) uniquely tailored to perform the configured functions and are no longer general-purpose processors. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. 
     Accordingly, the phrase “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. As used herein, “hardware-implemented module” refers to a hardware module. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where a hardware module comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware modules) at different times. Software accordingly configures a particular processor or processors, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time. 
     Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules may be regarded as being communicatively coupled. Where multiple hardware modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information). 
     The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented module” refers to a hardware module implemented using one or more processors. 
     Similarly, the methods described herein may be at least partially processor-implemented, with a particular processor or processors being an example of hardware. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented modules. Moreover, the one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an Application Program Interface (API)). 
     The performance of certain of the operations may be distributed among the processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processors or processor-implemented modules may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the processors or processor-implemented modules may be distributed across a number of geographic locations. 
     The modules, methods, applications, and so forth described in conjunction with  FIGS.  1 - 8    are implemented in some embodiments in the context of a machine and an associated software architecture. The sections below describe representative software architecture(s) and machine (e.g., hardware) architecture that are suitable for use with the disclosed embodiments. 
     Software architectures are used in conjunction with hardware architectures to create devices and machines tailored to particular purposes. For example, a particular hardware architecture coupled with a particular software architecture will create a mobile device, such as a mobile phone, tablet device, or so forth. A slightly different hardware and software architecture may yield a smart device for use in the “internet of things.” While yet another combination produces a server computer for use within a cloud computing architecture. Not all combinations of such software and hardware architectures are presented here as those of skill in the art can readily understand how to implement the features of the present disclosure in different contexts from the disclosure contained herein. 
       FIG.  9    is a block diagram  900  illustrating a representative software architecture  902 , which may be used in conjunction with various hardware architectures herein described.  FIG.  9    is merely a non-limiting example of a software architecture  902  and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. The software architecture  902  may be executing on hardware such as a machine  1000  of  FIG.  10    that includes, among other things, processors  910 , memory/storage  930 , and I/O components  950 . A representative hardware layer  904  is illustrated in  FIG.  9    and can represent, for example, the machine  1000  of  FIG.  10   . The representative hardware layer  904  comprises one or more processing units  906  having associated executable instructions  908 . The executable instructions  908  represent the executable instructions of the software architecture  902 , including implementation of the methods, modules, and so forth of  FIGS.  1 - 8   . The hardware layer  904  also includes memory and/or storage modules  910 , which also have the executable instructions  908 . The hardware layer  904  may also comprise other hardware  912 , which represents any other hardware of the hardware layer  904 , such as the other hardware illustrated as part of the machine  900 . 
     In the example architecture of  FIG.  9   , the software architecture  902  may be conceptualized as a stack of layers where each layer provides particular functionality. For example, the software architecture  902  may include layers such as an operating system  914 , libraries  916 , frameworks/middleware  918 , applications  920 , and a presentation layer  944 . Operationally, the applications  920  and/or other components within the layers may invoke application programming interface (API) calls  924  through the software stack and receive a response, returned values, and so forth, illustrated as messages  926 , in response to the API calls  924 . The layers illustrated are representative in nature and not all software architectures have all layers. For example, some mobile or special purpose operating systems may not provide a frameworks/middleware  918 , while others may provide such a layer. Other software architectures may include additional or different layers. 
     The operating system  914  may manage hardware resources and provide common services. The operating system  914  may include, for example, a kernel  928 , services  930 , and drivers  932 . The kernel  928  may act as an abstraction layer between the hardware and the other software layers. For example, the kernel  928  may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services  930  may provide other common services for the other software layers. The drivers  932  may be responsible for controlling or interfacing with the underlying hardware. For instance, the drivers  932  may include display drivers, camera drivers, Bluetooth® drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audio drivers, power management drivers, and so forth depending on the hardware configuration. 
     The libraries  916  may provide a common infrastructure that may be utilized by the applications  920  or other components or layers. The libraries  916  typically provide functionality that allows other software modules to perform tasks in an easier fashion than to interface directly with the underlying operating system  914  functionality (e.g., kernel  928 , services  930 , and/or drivers  932 ). The libraries  916  may include system libraries  934  (e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematic functions, and the like. In addition, the libraries  916  may include API libraries  936  such as media libraries (e.g., libraries to support presentation and manipulation of various media formats such as MPEG4, H.264, MP3, AAC, AMR, JPG, PNG), graphics libraries (e.g., an OpenGL framework that may be used to render 2D and 3D graphic content on a display), database libraries (e.g., SQLite that may provide various relational database functions), web libraries (e.g., WebKit that may provide web browsing functionality), and the like. The libraries  916  may also include a wide variety of other libraries  938  to provide many other APIs to the applications  920  and other software components/modules. 
     The frameworks/middleware  918  may provide a higher-level common infrastructure that may be utilized by the applications  920  or other software components/modules. For example, the frameworks/middleware  918  may provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks/middleware  918  may provide a broad spectrum of other APIs that may be utilized by the applications  920  or other software components/modules, some of which may be specific to a particular operating system or platform. 
     The applications  920  include built-in applications  940  or third-party applications  942 . Examples of representative built-in applications  940  may include, but are not limited to, a contacts application, a browser application, a book reader application, a location application, a media application, a messaging application, or a game application. The third-party applications  942  may include any of the built-in applications  940  as well as a broad assortment of other applications. In a specific example, the third party application  942  (e.g., an application developed using the Android™ or iOS™ software development kit (SDK) by an entity other than the vendor of the particular platform) may be mobile software running on a mobile operating system such as iOS™, Android™, Windows® Phone, or other mobile operating systems. In this example, the third-party application  942  may invoke the API calls  924  provided by the mobile operating system such as the operating system  914  to facilitate functionality described herein. 
     The applications  920  may utilize built-in operating system functions (e.g., kernel  928 , services  930 , and/or drivers  932 ), libraries (e.g., system libraries  934 , API libraries  936 , and other libraries  938 ), and frameworks/middleware  918  to create user interfaces to interact with users of the system. Alternatively, or additionally, in some systems, interactions with a user may occur through a presentation layer, such as the presentation layer  944 . In these systems, the application/module “logic” can be separated from the aspects of the application/module that interact with a user. 
     Some software architectures utilize virtual machines. In the example of  FIG.  9   , this is illustrated by a virtual machine  948 . A virtual machine creates a software environment where applications/modules can execute as if they were executing on a hardware machine (e.g., the machine of  FIG.  10   ). A virtual machine is hosted by a host operating system (e.g., operating system  914 ) and typically, although not always, has a virtual machine monitor  946 , which manages the operation of the virtual machine  948  as well as the interface with the host operating system (e.g., operating system  914 ). A software architecture executes within the virtual machine  948  such as an operating system  950 , libraries  952 , frameworks  954 , applications  956 , or presentation layer  958 . These layers of software architecture executing within the virtual machine  948  can be the same as corresponding layers previously described or may be different. 
       FIG.  10    is a block diagram illustrating components of a machine  1000 , according to some example embodiments, able to read instructions from a machine-readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein. Specifically,  FIG.  10    shows a diagrammatic representation of the machine  1000  in the example form of a computer system, within which instructions  1016  (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine  1000  to perform any one or more of the methodologies discussed herein may be executed. For example, the instructions may cause the machine to execute the flow diagram of  FIG.  10   . Additionally, or alternatively, the instructions may implement any combination of one or more of the modules of  FIG.  4   , and so forth. The instructions transform the general, non-programmed machine into a particular machine programmed to carry out the described and illustrated functions in the manner described. In alternative embodiments, the machine  1000  operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine  1000  may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine  1000  may comprise, but not be limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), an entertainment media system, a cellular telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions  1016 , sequentially or otherwise, that specify actions to be taken by machine  1000 . Further, while only a single machine  1000  is illustrated, the term “machine” shall also be taken to include a collection of machines  1000  that individually or jointly execute the instructions  1016  to perform any one or more of the methodologies discussed herein. 
     The machine  1000  may include processors  1010 , memory  1030 , and I/O components  1050 , which may be configured to communicate with each other such as via a bus  1002 . In an example embodiment, the processors  1010  (e.g., a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Radio-Frequency Integrated Circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, processor  1012  and processor  1014  that may execute instructions  1016 . The term “processor” is intended to include multi-core processor that may comprise two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously. Although  FIG.  10    shows multiple processors, the machine  1000  may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core process), multiple processors with a single core, multiple processors with multiples cores, or any combination thereof. 
     The memory/storage  1030  may include a memory  1032 , such as a main memory, or other memory storage, and a storage unit  1036 , both accessible to the processors  1010  such as via the bus  1002 . The storage unit  1036  and memory  1032  store the instructions  1016  embodying any one or more of the methodologies or functions described herein. The instructions  1016  may also reside, completely or partially, within the memory  1032 , within the storage unit  1036 , within at least one of the processors  1010  (e.g., within the processor&#39;s cache memory), or any suitable combination thereof, during execution thereof by the machine  1000 . Accordingly, the memory  1032 , the storage unit  1036 , and the memory of processors  1010  are examples of machine-readable media. 
     As used herein, “machine-readable medium” means a device able to store instructions and data temporarily or permanently and may include, but is not be limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, optical media, magnetic media, cache memory, other types of storage (e.g., Erasable Programmable Read-Only Memory (EEPROM)) and/or any suitable combination thereof. The term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions  1016 . The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions (e.g., instructions  1016 ) for execution by a machine (e.g., machine  1000 ), such that the instructions, when executed by one or more processors of the machine  1000  (e.g., processors  1010 ), cause the machine  1000  to perform any one or more of the methodologies described herein. Accordingly, a “machine-readable medium” refers to a single storage apparatus or device, as well as “cloud-based” storage systems or storage networks that include multiple storage apparatus or devices. The term “machine-readable medium” excludes signals per se. 
     The I/O components  1050  may include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. The specific U/O components  1050  that are included in a particular machine will depend on the type of machine. For example, portable machines such as mobile phones will likely include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I/O components  1050  may include many other components that are not shown in  FIG.  10   . The I/O components  1050  are grouped according to functionality merely for simplifying the following discussion and the grouping is in no way limiting. In various example embodiments, the I/O components  1050  may include output components  1052  and input components  1054 . The output components  1052  may include visual components (e.g., a display such as a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), haptic components (e.g., a vibratory motor, resistance mechanisms), other signal generators, and so forth. The input components  1054  may include alphanumeric input components (e.g., a keyboard, a touch screen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instrument), tactile input components (e.g., a physical button, a touch screen that provides location and/or force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like. 
     In further example embodiments, the I/O components  1050  may include biometric components  1056 , motion components  1058 , environmental components  1060 , or position components  1062  among a wide array of other components. For example, the biometric components  1056  may include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram based identification), and the like. The motion components  1058  may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environmental components  1060  may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometer that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensors (e.g., gas detection sensors to detection concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components  1062  may include location sensor components (e.g., a Global Position System (GPS) receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like. 
     Communication may be implemented using a wide variety of technologies. The I/O components  1050  may include communication components  1064  operable to couple the machine  1000  to a network  1080  or devices  1070  via coupling  1082  and coupling  1072  respectively. For example, the communication components  1064  may include a network interface component or other suitable device to interface with the network  1080 . In further examples, communication components  1064  may include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components to provide communication via other modalities. The devices  1070  may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a Universal Serial Bus (USB)). 
     Moreover, the communication components  1064  may detect identifiers or include components operable to detect identifiers. For example, the communication components  1064  may include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional bar codes such as Universal Product Code (UPC) bar code, multi-dimensional bar codes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D bar code, and other optical codes), or acoustic detection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components  1064 , such as, location via Internet Protocol (IP) geo-location, location via Wi-Fi® signal triangulation, location via detecting a NFC beacon signal that may indicate a particular location, and so forth. 
     In various example embodiments, one or more portions of the network  1080  may be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a portion of the Internet, a portion of the Public Switched Telephone Network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a Wi-Fi® network, another type of network, or a combination of two or more such networks. For example, the network  1080  or a portion of the network  1080  may include a wireless or cellular network and the coupling  1082  may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or other type of cellular or wireless coupling. In this example, the coupling  1082  may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1×RTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard setting organizations, other long range protocols, or other data transfer technology. 
     The instructions  1016  may be transmitted or received over the network  1080  using a transmission medium via a network interface device (e.g., a network interface component included in the communication components  1064 ) and utilizing any one of a number of well-known transfer protocols (e.g., hypertext transfer protocol (HTTP)). Similarly, the instructions  1016  may be transmitted or received using a transmission medium via the coupling  1072  (e.g., a peer-to-peer coupling) to devices  1070 . The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding, or carrying instructions  1016  for execution by the machine  1000 , and includes digital or analog communications signals or other intangible medium to facilitate communication of such software. 
     Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein. 
     Although an overview of the inventive subject matter has been described with reference to specific example embodiments, various modifications and changes may be made to these embodiments without departing from the broader scope of embodiments of the present disclosure. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single disclosure or inventive concept if more than one is, in fact, disclosed. 
     The embodiments illustrated herein are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. The Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled. 
     As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Moreover, plural instances may be provided for resources, operations, or structures described herein as a single instance. Additionally, boundaries between various resources, operations, modules, engines, and data stores are somewhat arbitrary, and particular operations are illustrated in a context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within a scope of various embodiments of the present disclosure. In general, structures and functionality presented as separate resources in the example configurations may be implemented as a combined structure or resource. Similarly, structures and functionality presented as a single resource may be implemented as separate resources. These and other variations, modifications, additions, and improvements fall within a scope of embodiments of the present disclosure as represented by the appended claims. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. 
     Although an embodiment has been described with reference to specific example embodiments, it will be evident that various modifications and changes can be made to these embodiments without departing from the broader spirit and scope of the present disclosure. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. The accompanying drawings that form a part hereof show, by way of illustration, and not of limitation, specific embodiments in which the subject matter can be practiced. The embodiments illustrated are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed herein. Other embodiments can be utilized and derived therefrom, such that structural and logical substitutions and changes can be made without departing from the scope of this disclosure. This Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled. 
     Such embodiments of the inventive subject matter can be referred to herein, individually and/or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Thus, although specific embodiments have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose can be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description. 
     The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.