Patent Publication Number: US-11640461-B2

Title: Secure runtime for virtual machines

Description:
TECHNICAL FIELD 
     The present disclosure generally relates to virtual machines and more particularly, but not exclusively, to secure runtime for virtual machines. 
     BACKGROUND 
     Virtualization allows virtual hardware to be created and decoupled from the underlying physical hardware. For example, a hypervisor running on a host machine or server may be used to create one or more virtual machines that may each run the same operating system or different operating systems (e.g., a first virtual machine may run a Windows® operating system and a second virtual machine may run a Unix-like operating system such as OS X®). A virtual machine may comprise a software implementation of a physical machine. The virtual machine may include one or more virtual hardware devices, such as a virtual processor, a virtual memory, a virtual disk, or a virtual network interface card. The virtual machine may load and execute an operating system and applications from the virtual memory. The operating system and applications used by the virtual machine may be stored using the virtual disk. The virtual machine may be stored as a set of files including a virtual disk file for storing the contents of a virtual disk and a virtual machine configuration file for storing configuration settings for the virtual machine. The configuration settings may include the number of virtual processors (e.g., four virtual CPUs), the size of a virtual memory, and the size of a virtual disk (e.g., a 10 GB virtual disk) for the virtual machine. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       To more easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure (“FIG.”) number in which that element or act is first introduced. 
         FIG.  1 A  depicts a networked computing environment in which the disclosed technology may be practiced, according to some example embodiments. 
         FIG.  1 B  depicts a server of a networked computing environment, according to some example embodiments. 
         FIG.  1 C  depicts a storage appliance of a networked computing environment, according to some example embodiments. 
         FIG.  2    depicts a secure runtime system according to some example embodiments. 
         FIG.  3    depicts a flowchart illustrating a method of instantiating the secure runtime system according to some example embodiments. 
         FIG.  4    is a block diagram illustrating a representative software architecture, which may be used in conjunction with various hardware architectures herein described. 
         FIG.  5    is a block diagram illustrating components of a machine, 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. 
     
    
    
     DETAILED DESCRIPTION 
     The description that follows includes systems, methods, techniques, instruction sequences, and computing machine program products that embody illustrative embodiments of the disclosure. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide an understanding of various embodiments of the inventive subject matter. It will be evident, however, to those skilled in the art, that embodiments of the inventive subject matter may be practiced without these specific details. In general, well-known instruction instances, protocols, structures, and techniques are not necessarily shown in detail. 
     Embodiments provide a secure, extensible app runtime for virtual machines. The runtime sandboxes the execution of an app to prevent malicious code from affecting virtual machine operations. The runtime also safeguards data by giving apps access to a copy of the virtual machine data instead of direct access to the data. 
       FIG.  1 A  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 datacenter  150 , a storage appliance  140 , and a computing device  154  in communication with each other via one or more networks  180 . The networked computing environment  100  may include a plurality of computing devices interconnected through one or more networks  180 . The one or more networks  180  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 datacenter  150  may include one or more servers, such as server  160 , in communication with one or more storage devices, such as storage device  156 . The one or more servers may also be in communication with one or more storage appliances, such as storage appliance  170 . The server  160 , storage device  156 , and storage appliance  170  may be in communication with each other via a networking fabric connecting servers and data storage units within the datacenter  150  to each other. The storage appliance  170  may include a data management system for backing up virtual machines and/or files within a virtualized infrastructure. The server  160  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 (e.g., a web server hosting an auto-parts website). The storage device  156  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 networked attached storage (NAS) device. In some cases, a datacenter, such as datacenter  150 , may include thousands of servers and/or data storage devices in communication with each other. The data storage devices 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  180  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  180  may include a cellular network, a mobile network, a wireless network, or a wired network. Each network of the one or more networks  180  may include hubs, bridges, routers, switches, and wired transmission media such as a direct-wired connection. The one or more networks  180  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  160 , may allow a client to download information or files (e.g., executable, text, application, audio, image, or video files) from the server  160  or to perform a search query related to particular information stored on the server  160 . In some cases, a server may act as an application server or a file server. In general, a server 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  160  includes a network interface  165 , processor  166 , memory  167 , disk  168 , and virtualization manager  169  all in communication with each other. Network interface  165  allows server  160  to connect to one or more networks  180 . Network interface  165  may include a wireless network interface and/or a wired network interface. Processor  166  allows server  160  to execute computer-readable instructions stored in memory  167  in order to perform processes described herein. Processor  166  may include one or more processing units, such as one or more CPUs and/or one or more GPUs. Memory  167  may comprise one or more types of memory (e.g., RAM, SRAM, DRAM, ROM, EEPROM, Flash, etc.). Disk  168  may include a hard disk drive and/or a solid-state drive. Memory  167  and disk  168  may comprise hardware storage devices. 
     The virtualization manager  169  may manage a virtualized infrastructure and perform management operations associated with the virtualized infrastructure. The virtualization manager  169  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  169  may set a virtual machine into a frozen state in response to a snapshot request made via an application programming interface (API) by a storage appliance (e.g., agent installed on the storage appliance), such as storage appliance  140  or storage appliance  170 . 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 machine 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  169  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 a point in time is frozen) to a storage appliance in response to a request made by the storage appliance  170 . After the data associated with the point-in-time snapshot of the virtual machine has been transferred to the storage appliance  170 , 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  169  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 storage appliance  170  includes a network interface  175 , processor  176 , memory  177 , and disk  178  all in communication with each other. Network interface  175  allows storage appliance  170  to connect to one or more networks  180 . Network interface  175  may include a wireless network interface and/or a wired network interface. Processor  176  allows storage appliance  170  to execute computer-readable instructions stored in memory  177  in order to perform processes described herein. Processor  176  may include one or more processing units, such as one or more CPUs and/or one or more CPUs. Memory  177  may comprise one or more types of memory (e.g., RAM, SRAM, DRAM, ROM, EEPROM, NOR Flash, NAND Flash, etc.). Disk  178  may include a hard disk drive and/or a solid-state drive. Memory  177  and disk  178  may comprise hardware storage devices. 
     In one embodiment, the storage appliance  170  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  180  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 thousands of 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  154 . 
     The storage appliance  140  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  160  or files stored on server  160  (e.g., locally stored files, files stored in mounted directories), according to some example embodiments. 
     In some cases, networked computing environment  100  may provide remote access to secure applications and files stored within datacenter  150  from a remote computing device, such as computing device  154 . The datacenter  150  may use an access control application to manage remote access to protected resources, such as protected applications, databases, or files located within the datacenter  150 . 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  154 , 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  170  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 datacenter  150 . 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 server  160 , the storage appliance  170  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  160  in response to a mount command from the server  160 , the storage appliance  170  may allow a point-in-time version of a virtual machine to be mounted and allow the server  160  to read and/or modify data associated with the point-in-time version of the virtual machine. To improve storage density, the storage appliance  170  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  170  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  170  may provide a user interface 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  170  (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  170  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. A user (e.g., database administrator) of the storage appliance  170  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. 
     In some example embodiments, the storage appliance  140  is an external network connected database appliance comprising an agent  142 , an application  144 , and a storage device  146 . In some example embodiments, the application  144  is a database application for managing a database (e.g., Oracle database management system) that can store database data locally on the storage device  146 , or on remote storage locations, such as within the datacenter  150 . The agent  142  is a remote connection system for performing snapshots of database data (e.g., application  144 ), and can further implement bootstrapping, upgrade, and further include backup features to transfer data from the storage appliance  140  to datacenter  150  via networks  180 . 
     In some example embodiments, the agent  142  can be uploaded from the datacenter  150  and installed on the storage appliance  140 . After installation on storage appliance  140 , the agent  142  can be enabled or disabled by the storage appliance  140  over time. The agent  142  may acquire one or more electronic files or snapshot information associated with the one or more electronic files from the application  144 . The snapshot information may include full and/or differential snapshot data. In one example, the one or more electronic files may comprise a database file for a database and the snapshot information may comprise a differential backup of the database file. 
     In those embodiments in which the application  144  is a database application that manages a database, the agent  142  is configured to acquire one or more electronic files corresponding with a first point-in-time version of the database from the database application. The agent  142  can further acquire a database file for the database from the application  144  or acquire a fill or differential backup of the database from the computing application  144 . The determination of whether the agent  142  acquires the database file or the full or differential backup may depend on a file size of the database file. The database file may comprise a text file or a binary file. The agent  142  may transfer one or more changed data blocks corresponding with the first point-in-time version of the database to the storage appliance  140 . The one or more changed data blocks may be identified by the agent  142  by generating and comparing fingerprints or signatures for data blocks of the database file with previously generated fingerprints or signatures associated with earlier point-in-time versions of the database file captured prior to the first point in time. In some example embodiments, the agent  142  can perform automatic upgrades or downgrades the backup agent  142  to be in-sync with software changes to a plurality of nodes (e.g., nodes operating within storage appliance  170 ). 
     In some example embodiments, the agent  142  is further configured to interface with application  144  or storage device  146  to implement changes, such as creating directories, database instances, reads/writes, and other operations to provide database management functions between the storage appliance  140  and devices within datacenter  150 . For example, the application  144  can be a relational database management application with plugin functionality, in which third-party developed plugins or extensions can be integrated in the application  144  to perform actions, such as creation of a database instance. 
       FIG.  1 B  depicts one embodiment of server  160  in  FIG.  1 A . The server  160  may comprise one server out of a plurality of servers that are networked together within a datacenter  150 . In one example, the plurality of servers may be positioned within one or more server racks within the datacenter  150 . As depicted, the server  160  includes hardware-level components and software-level components. The hardware-level components include one or more processors  182 , one or more memory  184 , and one or more disks  185 . The software-level components include a hypervisor  186 , a virtualized infrastructure manager  199 , and one or more virtual machines, such as virtual machine  198 . The hypervisor  186  may comprise a native hypervisor or a hosted hypervisor. The hypervisor  186  may provide a virtual operating platform for running one or more virtual machines, such as virtual machine  198 . Virtual machine  198  includes a plurality of virtual hardware devices including a virtual processor  192 , a virtual memory  194 , and a virtual disk  195 . The virtual disk  195  may comprise a file stored within the one or more disks  185 . In one example, a virtual machine may include a plurality of virtual disks, with each virtual disk of the plurality of virtual disks associated with a different file stored on the one or more disks  185 . Virtual machine  198  may include a guest operating system  196  that runs one or more applications, such as application  197 . 
     The virtualized infrastructure manager  199 , which may correspond with the virtualization manager  169  in  FIG.  1 A , may run on a virtual machine or natively on the server  160 . The virtualized infrastructure manager  199  may provide a centralized platform for managing a virtualized infrastructure that includes a plurality of virtual machines. The virtualized infrastructure manager  199  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  199  may perform various virtualized infrastructure-related tasks, such as cloning virtual machines, creating new virtual machines (e.g., new virtual machines for new nodes of the cluster), monitoring the state of virtual machines, and facilitating backups of virtual machines. 
     In one embodiment, the server  160  may use the virtualized infrastructure manager  199  to facilitate backups for a plurality of virtual machines (e.g., eight different virtual machines) running on the server  160 . Each virtual machine running on the server  160  may run its own guest operating system and its own set of applications. Each virtual machine running on the server  160  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  140  in  FIG.  1 A  or storage appliance  170  in  FIG.  1 A , may request a snapshot of a virtual machine running on server  160 . 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  199  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  199  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. 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  199  may transfer a full image of the virtual machine to the storage appliance 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  199  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  199  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  199  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  160  or the hypervisor  186  may communicate with a storage appliance, such as storage appliance  140  in  FIG.  1 A  or storage appliance  170  in  FIG.  1 A , using a distributed file system protocol such as Network File System (NFS) Version 3. The distributed file system protocol may allow the server  160  or the hypervisor  186  to access, read, write, or modify files stored on the storage appliance as if the files were locally stored on the server  160 . The distributed file system protocol may allow the server  160  or the hypervisor  186  to mount a directory or a portion of a file system located within the storage appliance  140 . For example, the storage appliance  140  can include a standalone host of a database, where the server  1160  mounts the database directories as if the files were locally stored on server  160 . Further, the server  160  may function as a backup device for storage appliance  140  by backing up data in the mounted directories in a distributed database within the datacenter  150 , such as a cluster of nodes in the storage appliance  170 . 
       FIG.  1 C  depicts one embodiment of the storage appliance  170  in  FIG.  1 A . The storage appliance  170  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, a Cassandra cluster). In one example, the storage appliance  170  may be positioned within a server rack within a datacenter. As depicted, the storage appliance  170  includes hardware-level components and software-level components. The hardware-level components include one or more physical machines, such as physical machine  120  and physical machine  130 . The physical machine  120  includes a network interface  121 , processor  122 , memory  123 , and disk  124  all in communication with each other. Processor  122  allows physical machine  120  to execute computer-readable instructions stored in memory  123  to perform processes described herein. Disk  124  may include a hard disk drive and/or a solid-state drive. The physical machine  130  includes a network interface  131 , processor  132 , memory  133 , and disk  134  all in communication with each other. Processor  132  allows physical machine  130  to execute computer-readable instructions stored in memory  133  to perform processes described herein. Disk  134  may include a hard disk drive and/or a solid-state drive. In some cases, disk  134  may include a flash-based SSD or a hybrid HDD/SSD drive. In one embodiment, the storage appliance  170  may include a plurality of physical machines arranged in a cluster (e.g., four machines in a cluster). Each of the plurality of physical machines may include a plurality of multi-core CPUs, 128 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  160  in  FIG.  1 A , or a hypervisor, such as hypervisor  186  in  FIG.  1 B , to communicate with the storage appliance  170  may not provide a failover mechanism (e.g., NES 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  186  in  FIG.  1 B , may be configured with a first floating IP address associated with a first node in the cluster. The hypervisor  186  may connect to the cluster using the first floating IP address. In one example, the hypervisor  186  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  186  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.  1 C , the software-level components of the storage appliance  170  may include data management system  102 , a virtualization interface  104 , a distributed job scheduler  108 , a distributed metadata store  110 , a distributed file system  112 , and one or more virtual machine search indexes, such as virtual machine search index  106 . In one embodiment, the software-level components of the storage appliance  170  may be run using a dedicated hardware-based appliance. In another embodiment, the software-level components of the storage appliance  170  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 machines) may be aggregated and made available over a single file system namespace (e.g., /snap-50 shots/). A directory for each virtual machine protected using the storage appliance  170  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  112  may present itself as a single file system, in which, as new physical machines or nodes are added to the storage appliance  170 , the cluster may automatically discover the additional nodes and automatically increase the available capacity of the file system  112  for storing files and other data. Each file stored in the distributed file system  112  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  112  as a separate file. The files stored within the distributed file system  112  may be replicated or mirrored over a plurality of physical machines, thereby creating a load-balanced and fault-tolerant distributed file system  112 . In one example, storage appliance  170  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  110  may include a distributed database management system that provides high availability without a single point of failure. In one embodiment, the distributed metadata store  110  may comprise a database, such as a distributed document-oriented database. The distributed metadata store  110  may be used as a distributed key value storage system. In one example, the distributed metadata store  110  may comprise a distributed NoSQL key value store database. In some cases, the distributed metadata store  110  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  112 . 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  112  and metadata associated with the new file may be stored within the distributed metadata store  110 . The distributed metadata store  110  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  170 . 
     In some cases, the distributed metadata store  110  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  112  or an incremental snapshot of the virtual machine (e.g., a forward incremental or reverse incremental) stored within the distributed file system  112 . 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 incrementals 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 incrementals 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 incrementals. 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 incrementals. 
     The distributed job scheduler  108  may be used for scheduling backup jobs that acquire and store virtual machine snapshots for one or more virtual machines over time. The distributed job scheduler  108  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  108  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  108  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  108  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  108  may be fully decentralized and implemented without the existence of a master node. The distributed job scheduler  108  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  108  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  110 . 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  108  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  108  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 were ever performed. The series of tasks may correspond with an ordering of tasks for the series of tasks and the distributed job scheduler  108  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  108  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  108  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 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  108  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  108  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  199  in  FIG.  1 B , 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  170  in  FIG.  1 A . The one or more tasks may also include generating metadata for the one or more chunks, storing the metadata using the distributed metadata store  110 , storing the one or more chunks within the distributed file system  112 , and communicating with the virtualized infrastructure manager  199  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  112  (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  104  may provide an interface for communicating with a virtualized infrastructure manager managing a virtualization infrastructure, such as virtualized infrastructure manager  199  in  FIG.  1 B , and requesting data associated with virtual machine snapshots from the virtualization infrastructure. The virtualization interface  104  may communicate with the virtualized infrastructure manager using an 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  170  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  104  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  106  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  106  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  170  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  112  in  FIG.  1 C . 
     The data management system  102  may comprise an application running on the storage appliance (e.g., storage appliance  170 ) that manages and stores one or more snapshots of a virtual machine. In one example, the data management system  102  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  102 , the virtualization interface  104 , the distributed job scheduler  108 , the distributed metadata store  110 , and the distributed file system  112 . 
     In some cases, the integrated software stack may run on other computing devices, such as a server or computing device  154  in  FIG.  1 A . The data management system  102  may use the virtualization interface  104 , the distributed job scheduler  108 , the distributed metadata store  110 , and the distributed file system  112  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  102  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  112 . Combined together, the one or more chunks and/or the one or more files stored within the distributed file system  112  may comprise a full image of the version of the virtual machine. 
       FIG.  2    depicts a secure runtime system  200  according to some example embodiments. The system  200  may reside in the data center  150 , e.g., on the server  160  or the storage appliance  170  or external to the data center, e.g., the storage appliance  140  or other location. Alternatively, the system  200  may be distributed instead of residing a single device. The system  200  enables apps to utilize subsets of datacenter  150  data. The system  200  sandboxes the execution of the app to prevent malicious code from affecting datacenter  150  operations. The system  200  also safeguards the datacenter  150  data by giving apps access to a copy of the data instead of direct access to the data stored in the datacenter  150 . 
     The system  200  comprises a runtime  210 , APIs  220 , Apps  230  and a containerized runtime  240 . The runtime  210  generates the sandboxed containerized runtime  240  using Linux container APIs and instantiates apps  230  within the runtime  240 . The Apps  230  use the API  220  to access data sources outside the containerized runtime  240 . The APIs  220  include targeted APIs that integrate with each data source (e.g., databases, snapshots of virtual machines, input/output (I/O) from virtual machines, etc. The APIs can provide a copy of data or read-only access to data being ingested to the Apps  230 . In another embodiment, access control can limit which apps  230  have access to which data in which data sources. For example, it&#39;s not necessary for apps  230  to have read only access to all available data since it could be a security risk. Either way, the runtime  210  prevents apps  230  in the containerized runtime  240  from modifying the data source. The containerized runtime  240  can include network access or restrict access. The containerized runtime  240  can be allocated a maximum percentage of CPU use and/or maximum percentage (or absolute value) of memory use. Further, as the containerized runtime is outside of the virtual machine from which data can be coming, workloads on the virtual machine are not affected. 
       FIG.  3    depicts a flowchart illustrating a method  300  of instantiating the secure runtime system according to some example embodiments. The method  300  can be performed by a processor, such as the processor  166 , the processor  176 , and/or processors  710  ( FIG.  5   ). The runtime  210  generates ( 310 ) the containerized runtime  240  and instantiates ( 320 ) an App from the Apps  230 . The runtime  210  then receives ( 330 ) a request for data from the instantiated app. The runtime  210  determines ( 340 ) a data source that hosts the requested data (e.g., virtual machine, database, snapshot, etc.) and then identifies ( 350 ) an appropriate API from the APIs  220  for the determined data source. The determined API then retrieves ( 360 ) a copy of the data from the determined data source and transmits it to the requesting app. The requesting app then operates ( 370 ) on the copy of the data in the containerized runtime and outputs ( 380 ) results of the operation. 
     In an embodiment, the data is a snapshot of the virtual machine. In an embodiment, the method  300  further include restoring a database to a target location and the app performs queries on the restored database. In an embodiment, the data includes input and output from a virtual machine and the method  300  further includes disabling the virtual machine based on analysis of the input (e.g., if malware is present). 
     In an embodiment, the method  300  further comprises instantiating a second virtual machine and wherein the containerized runtime is within a section of the memory allocated to the second virtual machine. In an embodiment, the app includes a user interface and the operations further comprise generating a user interface to display indexed files. 
     In an embodiment, the app can run analysis on snapshots. For example, when a snapshot has been ingested and indexed, apps are given an internally mounted copy of the filesystem to run analysis. 
     In an embodiment, the app transforms database data during a recovery. After a database has been restored to its target location, apps are given a direct connection to the restored database and can perform queries/transformations. 
     In an embodiment, the app can run analysis on streaming virtual machine input/output (I/O). As IQs are streamed to the datacenter  150 , read-only access to the IOs are given to the app, so that analysis can be performed on the IO real-time. In an embodiment the app is also given permission to cease the VM, which is a security context that the customer will be made aware of. 
     In an embodiment, the app can provide a more general framework for custom integrations with data sources not natively supported. For example, a developer can code against an interface with the logic to backup and ingest a data source. 
     In an embodiment, the the system  200  can provide interactive preview for certain file extensions in snapshots. The system  200  can include user-interface (UI) related APIs which allow apps to give users an enriched experience with their data. An example includes support for viewing indexed .docx files directly in the UI. 
       FIG.  4    is a block diagram illustrating an example software architecture  606 , which may be used in conjunction with various hardware architectures herein described.  FIG.  4    is a non-limiting example of a software architecture, and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. The software architecture  606  may execute on hardware such as a machine  700  of  FIG.  5    that includes, among other things, processors, memory, and I/O components. A representative hardware layer  652  is illustrated and can represent, for example, the machine  700  of  FIG.  5   . The representative hardware layer  652  includes a processing unit  654  having associated executable instructions  604 . The executable instructions  604  represent the executable instructions of the software architecture  606 , including implementation of the methods, components, and so forth described herein. The hardware layer  652  also includes a memory/storage  656 , which also has the executable instructions  604 . The hardware layer  652  may also comprise other hardware  658 . 
     In the example architecture of  FIG.  5   , the software architecture  606  may be conceptualized as a stack of layers where each layer provides particular functionality. For example, the software architecture  606  may include layers such as an operating system  602 , libraries  620 , frameworks/middleware  618 , applications  616 , and a presentation layer  614 . Operationally, the applications  616  and/or other components within the layers may invoke API calls  608  through the software stack and receive a response in the form of messages  612 . 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  618 , while others may provide such a layer. Other software architectures may include additional or different layers. 
     The operating system  602  may manage hardware resources and provide common services. The operating system  602  may include, for example, a kernel  622 , services  624 , and drivers  626 . The kernel  622  may act as an abstraction layer between the hardware and the other software layers. For example, the kernel  622  may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services  624  may provide other common services for the other software layers. The drivers  626  are responsible for controlling or interfacing with the underlying hardware. For instance, the drivers  626  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  620  provide a common infrastructure that is used by the applications  616  and/or other components and/or layers. The libraries  620  provide functionality that allows other software components to perform tasks in an easier fashion than by interfacing directly with the underlying operating system  602  functionality (e.g., kernel  622 , services  624 , and/or drivers  626 ). The libraries  620  may include system libraries  644  (e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematical functions, and the like. In addition, the libraries  620  may include API libraries  646  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, or 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  620  may also include a wide variety of other libraries  648  to provide many other APIs to the applications  616  and other software components/modules. 
     The frameworks/middleware  618  provide a higher-level common infrastructure that may be used by the applications  616  and/or other software components/modules. For example, the frameworks/middleware  618  may provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks/middleware  618  may provide a broad spectrum of other APIs that may be utilized by the applications  616  and/or other software components/modules, some of which may be specific to a particular operating system  602  or platform. 
     The applications  616  include built-in applications  638  and/or third-party applications  640 . Examples of representative built-in applications  638  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, and/or a game application. The third-party applications  640  may include an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform, and may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS® Phone, or other mobile operating systems. The third-party applications  640  may invoke the API calls  608  provided by the mobile operating system (such as the operating system  602 ) to facilitate functionality described herein. 
     The applications  616  may use built-in operating system functions (e.g., kernel  622 , services  624 , and/or drivers  626 ), libraries  620 , and frameworks/middleware  618  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  614 . In these systems, the application/component “logic” can be separated from the aspects of the application/component that interact with a user. 
       FIG.  6    is a block diagram illustrating components of a machine  700 , 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.  6    shows a diagrammatic representation of the machine  700  in the example form of a computer system, within which instructions  716  (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine  700  to perform any one or more of the methodologies discussed herein may be executed. As such, the instructions  716  may be used to implement modules or components described herein. The instructions  716  transform the general, non-programmed machine  700  into a particular machine  700  programmed to carry out the described and illustrated functions in the manner described. In alternative embodiments, the machine  700  operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine  700  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  700  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 smartphone, 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  716 , sequentially or otherwise, that specify actions to be taken by the machine  700 . Further, while only a single machine  700  is illustrated, the term “machine” shall also be taken to include a collection of machines that individually or jointly execute the instructions  716  to perform any one or more of the methodologies discussed herein. 
     The machine  700  may include processors  710 , memory/storage  730 , and I/O components  750 , which may be configured to communicate with each other such as via a bus  702 . The memory/storage  730  may include a main memory  732 , static memory  734 , and a storage unit  736 , both accessible to the processors  710  such as via the bus  702 . The storage unit  736  and main memory  732  store the instructions  716  embodying any one or more of the methodologies or functions described herein. The instructions  716  may also reside, completely or partially, within the static memory  734 , within the storage unit  736  (e.g., on machine readable-medium  738 ), within at least one of the processors  710  (e.g., within the processor cache memory accessible to processors  712  or  714 ), or any suitable combination thereof, during execution thereof by the machine  700 . Accordingly, the main memory  732 , static memory  734 , the storage unit  736 , and the memory of the processors  710  are examples of machine-readable media. 
     The I/O components  750  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 I/O components  750  that are included in a particular machine  700  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  750  may include many other components that are not shown in  FIG.  6   . The I/O components  750  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  750  may include output components  752  and input components  754 . The output components  752  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  754  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 instruments), 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  750  may include biometric components  756 , motion components  758 , environment components  760 , or position components  762  among a wide array of other components. For example, the biometric components  756  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  758  may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environment components  760  may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometers 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), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components  762  may include location sensor components (e.g., a 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  750  may include communication components  764  operable to couple the machine  700  to a network  780  or devices  770  via a coupling  782  and a coupling  772 , respectively. For example, the communication components  764  may include a network interface component or other suitable device to interface with the network  780 . In further examples, the communication components  764  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  770  may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a USB). 
     Moreover, the communication components  764  may detect identifiers or include components operable to detect identifiers. For example, the communication components  764  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 barcodes such as Universal Product Code (UPC) barcode, multi-dimensional barcodes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF418, Ultra Code, MC RSS-2D barcode, 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  764 , such as location via Internet Protocol (IP) geolocation, location via Wi-Fi® signal triangulation, location via detecting an NFC beacon signal that may indicate a particular location, and so forth. 
     “CARRIER SIGNAL” in this context refers to any intangible medium that is capable of storing, encoding, or carrying instructions  716  for execution by the machine  700 , and includes digital or analog communications signals or other intangible media to facilitate communication of such instructions  716 . Instructions  716  may be transmitted or received over the network  780  using a transmission medium via a network interface device and using any one of a number of well-known transfer protocols. 
     “CLIENT DEVICE” in this context refers to any machine  700  that interfaces to a network  780  to obtain resources from one or more server systems or other client devices. A client device may be, but is not limited to, a mobile phone, desktop computer, laptop, PDA, smartphone, tablet, ultrabook, netbook, multi-processor system, microprocessor-based or programmable consumer electronics system, game console, set-top box, or any other communication device that a user may use to access a network  780 . 
     “COMMUNICATIONS NETWORK” in this context refers to one or more portions of a network  780  that 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, a network or a portion of a network  780  may include a wireless or cellular network and the coupling  782  may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or another type of cellular or wireless coupling. In this example, the coupling 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. 
     “MACHINE-READABLE MEDIUM” in this context refers to a component, a device, or other tangible media able to store instructions  716  and data temporarily or permanently and may include, but is not 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 (EPROM)), 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  716 . The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions  716  (e.g., code) for execution by a machine  700 , such that the instructions  716 , when executed by one or more processors  710  of the machine  700 , cause the machine  700  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. 
     “COMPONENT” in this context refers to a device, a physical entity, or logic having boundaries defined by function or subroutine calls, branch points, APIs, or other technologies that provide for the partitioning or modularization of particular processing or control functions. Components may be combined via their interfaces with other components to carry out a machine process. A component may be a packaged functional hardware unit designed for use with other components and a part of a program that usually performs a particular function of related functions. Components may constitute either software components (e.g., code embodied on a machine-readable medium) or hardware components. 
     A “hardware component” 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 components of a computer system (e.g., a processor  712  or a group of processors  710 ) may be configured by software (e.g., an application or application portion) as a hardware component that operates to perform certain operations as described herein. A hardware component may also be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware component may include dedicated circuitry or logic that is permanently configured to perform certain operations. A hardware component may be a special-purpose processor, such as a field-programmable gate array (FPGA) or an application-specific integrated circuit (ASIC). A hardware component may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware component may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware components become specific machines (or specific components of a machine  700 ) uniquely tailored to perform the configured functions and are no longer general-purpose processors  710 . 
     It will be appreciated that the decision to implement a hardware component 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 component” (or “hardware-implemented component”) 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. 
     Considering embodiments in which hardware components are temporarily configured (e.g., programmed), each of the hardware components need not be configured or instantiated at any one instance in time. For example, where a hardware component comprises a general-purpose processor  712  configured by software to become a special-purpose processor, the general-purpose processor  712  may be configured as respectively different special-purpose processors (e.g., comprising different hardware components) at different times. Software accordingly configures a particular processor  712  or processors  710 , for example, to constitute a particular hardware component at one instance of time and to constitute a different hardware component at a different instance of time. 
     Hardware components can provide information to, and receive information from, other hardware components. Accordingly, the described hardware components may be regarded as being communicatively coupled. Where multiple hardware components 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 components. In embodiments in which multiple hardware components are configured or instantiated at different times, communications between or among such hardware components may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware components have access. For example, one hardware component may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware component may then, at a later time, access the memory device to retrieve and process the stored output. Hardware components 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  710  that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors  710  may constitute processor-implemented components that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented component” refers to a hardware component implemented using one or more processors  710 . Similarly, the methods described herein may be at least partially processor-implemented, with a particular processor  712  or processors  710  being an example of hardware. For example, at least some of the operations of a method may be performed by one or more processors  710  or processor-implemented components. Moreover, the one or more processors  710  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  700  including processors  710 ), with these operations being accessible via a network  780  (e.g., the Internet) and via one or more appropriate interfaces (e.g., an API). The performance of certain of the operations may be distributed among the processors  710 , not only residing within a single machine  700 , but deployed across a number of machines  700 . In some example embodiments, the processors  710  or processor-implemented components 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  710  or processor-implemented components may be distributed across a number of geographic locations. 
     “PROCESSOR” in this context refers to any circuit or virtual circuit (a physical circuit emulated by logic executing on an actual processor  712 ) that manipulates data values according to control signals (e.g., “commands,” “op codes,” “machine code,” etc.) and which produces corresponding output signals that are applied to operate a machine  700 . A processor may, for example, be a central processing unit (CPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CNC) processor, a graphics processing unit (GPU), a digital signal processor (DSP), an ASIC, a radio-frequency integrated circuit (RFIC), or any combination thereof. A processor  710  may further be a multi-core processor  710  having two or more independent processors  712 ,  714  (sometimes referred to as “cores”) that may execute instructions  716  contemporaneously. 
     “TIMESTAMP” in this context refers to a sequence of characters or encoded information identifying when a certain event occurred, for example giving date and time of day, sometimes accurate to a small fraction of a second. 
     The following examples describe various embodiments of methods, machine-readable media, and systems (e.g., machines, devices, or other apparatus) discussed herein. 
     1. A data management system, comprising: 
     a server configured to host a virtual machine; 
     one or more processors in communication with the server, the one or more processors configured to perform operations including: 
     generating, with the one or more processors, a secure runtime in a memory in communication with the one or more processors; 
     instantiating, with the one or more processors, an app in the runtime; 
     receiving, with the one or more processors, a request from the app for data; 
     determining, with the one or more processors, a data source having the requested data; 
     identifying, with the one or more processors, an API to access the data source; and 
     providing, with the one or more processors, read-only access to the app to the data source via the API for the app to operate on. 
     2. The system of example 1, wherein the operations further comprise enabling, with the one or more processors, network access to the app. 
     3. The system of any of the previous examples, wherein the data source is a snapshot of the virtual machine. 
     4. The system of any of the previous examples, wherein the operations further include restoring a database to a target location and the app performs queries on the restored database. 
     5. The system of any of the previous examples, wherein the data includes input and output from the virtual machine and the operations further include disabling the virtual machine upon detection of malware. 
     6. The system of any of the previous examples, wherein the operations further comprise instantiating a second virtual machine and wherein the containerized runtime is within a section of the memory allocated to the second virtual machine. 
     7. The system of any of the previous examples, wherein the app includes a user interface and the operations further comprise generating a user interface to display indexed files. 
     8. A computer-implemented method at a data management system, the method comprising: 
     generating, with one or more processors, a secure runtime in a memory in communication with the one or more processors; 
     instantiating, with the one or more processors, an app in the runtime; 
     receiving, with the one or more processors, a request from the app for data; 
     determining, with the one or more processors, a data source having the requested data; 
     identifying, with the one or more processors, an API to access the data source; and 
     providing, with the one or more processors, read-only access to the app to the data source via the API for the app to operate on. 
     9. The method of example 8, further comprising enabling, with the one or more processors, network access to the app. 
     10. The method of example 8 or 9, wherein the data source is a snapshot of the virtual machine. 
     11. The method of example 8, 9, or 10, further comprising restoring a database to a target location and the app performs queries on the restored database. 
     12. The method of example 8, 9, 10, or 11 wherein the data includes input and output from the virtual machine and the operations further include disabling the virtual machine upon detection of malware. 
     13. The method of example 8, 9, 10, 11 or 12, further comprising instantiating a second virtual machine and wherein the containerized runtime is within a section of the memory allocated to the second virtual machine. 
     14. The method of example 8, 9, 10, 11, 12, or 13, wherein the app includes a user interface and the method further comprising generating a user interface to display indexed files. 
     15. A non-transitory, machine-readable medium storing instructions which, when read by a data management system, cause the data management system to perform operations comprising, at least: 
     generating, with one or more processors, a secure runtime in a memory in communication with the one or more processors; 
     instantiating, with the one or more processors, an app in the runtime; 
     receiving, with the one or more processors, a request from the app for data; 
     determining, with the one or more processors, a data source having the requested data; 
     identifying, with the one or more processors, an API to access the data source; and 
     providing, with the one or more processors, read-only access to the app to the data source via the API for the app to operate on. 
     16. The medium of example 15, wherein the operations further comprise enabling, with the one or more processors, network access to the app. 
     17. The medium of example 15 or 16, wherein the data source is a snapshot of the virtual machine. 
     18. The medium of example 15, 16, or 17, wherein the operations further include restoring a database to a target location and the app performs queries on the restored database. 
     19. The medium of example 15, 16, 17, or 18, wherein the data includes input and output from the virtual machine and the operations further include disabling the virtual machine upon detection of malware. 
     20. The medium of example 15, 16, 17, 18 or 19, wherein the operations further comprise instantiating a second virtual machine and wherein the containerized runtime is within a section of the memory allocated to the second virtual machine. 
     21. The medium of example 15, 16, 17, 18, 19 or 20 wherein the app includes a user interface and the operations further comprise generating a user interface to display indexed files.