Abstract:
A method of container and image scanning includes storing at a central scan store of a multi-tenant system, an image scan result for a container image, the container image for executing functionality of applications and comprising layers, wherein the image scan result generated by a scan process comprising scanning a top layer of the container image, the remaining layers of the container image are immutable, verifying a clean status of the remaining layers of the container image with the central scan store, and transmitting the image scan result for the container image, the image scan result being clean in response to a clean result returned for the scanning and successful verification of the clean status of the remaining layers. The method further includes responsive to receiving a container image scan result request for the container image, transmitting the image scan result for the container image.

Description:
REFERENCE TO RELATED APPLICATION 
       [0001]    This application is a continuation of and claims the benefit under 35 U.S.C. §120 of U.S. patent application Ser. No. 14/605,019, filed on Jan. 26, 2015, the entirety of which is incorporated herein by reference. 
     
    
     TECHNICAL FIELD 
       [0002]    The implementations of the disclosure relate generally to Platform-as-a-Service (PaaS) systems and, more specifically, relate to container and image scanning for a PaaS system. 
       BACKGROUND 
       [0003]    A variety of Platform-as-a-Service (PaaS) system offerings exists that include software and/or hardware facilities for facilitating the execution of web applications in a cloud-computing environment (the “cloud”). Cloud computing is a computing paradigm in which a customer pays a “cloud provider” to execute a program on computer hardware owned and/or controlled by the cloud provider. It is common for cloud providers to make virtual machines (VMs) hosted on its computer hardware available to customers for this purpose. 
         [0004]    The cloud provider typically provides an interface that a customer can use to requisition virtual machines and associated resources such as processors, storage, and network services, etc., as well as an interface a customer can use to install and execute the customer&#39;s program on the virtual machines that the customer requisitions, together with additional software on which the customer&#39;s program depends. For some such programs, this additional software can include software components, such as a kernel and an operating system, and/or middleware and a framework. Customers that have installed and are executing their programs “in the cloud” typically communicate with the executing program from remote geographic locations using Internet protocols. 
         [0005]    PaaS offerings facilitate deployment of web applications without the cost and complexity of buying and managing the underlying hardware and software and provisioning hosting capabilities, providing the facilities to support the complete life cycle of building and delivering web applications and services entirely available from the Internet. Typically, these facilities operate as one or more VMs running on top of a hypervisor in a host server. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0006]    The disclosure will be understood more fully from the detailed description given below and from the accompanying drawings of various implementations of the disclosure. The drawings, however, should not be taken to limit the disclosure to the specific implementations, but are for explanation and understanding only. 
           [0007]      FIG. 1  is a block diagram of a network architecture in which implementations of the disclosure may operate. 
           [0008]      FIG. 2  is a block diagram of a multi-tenant Platform-as-a-Service (PaaS) system architecture according to an implementation of the disclosure. 
           [0009]      FIG. 3  is a flow diagram illustrating a method for build-time image scanning in a multi-tenant PaaS system according to an implementation of the disclosure. 
           [0010]      FIG. 4  is a flow diagram illustrating a method for runtime container and image scanning in a multi-tenant PaaS system according to an implementation of the disclosure. 
           [0011]      FIG. 5  is a flow diagram illustrating a method for re-scanning application images in a multi-tenant PaaS system according to an implementation of the disclosure. 
           [0012]      FIG. 6  illustrates a block diagram of one implementation of a computer system. 
       
    
    
     DETAILED DESCRIPTION 
       [0013]    Implementations of the disclosure provide container and image scanning for a Platform-as-a-Service (PaaS) system. Implementations provide scan components located at multiple locations in the PaaS system, including at nodes, at an image repository, and at an image build system. The scan components may include one or more pluggable scanning processes installed to provide pattern detection in order to identify threats (e.g., viruses, malware, other unwanted processes, etc.) existing in the PaaS system. Implementations of the disclosure optimize scanning performed by scan component of images and runtime environments of applications of the PaaS. The multiple scan components are distributed throughout the PaaS system to provide for separate build-time, runtime and image repository scans. 
         [0014]    The multiple scan components are optimized to take advantage of the image-based model for application deployment utilized by the PaaS. Full application image scans may be performed by a scan component residing at the image build system. Each time an application image is built, scan component analyzes the output of the build to determine whether the application image is clean. A result of the built application image scan process is stored in a central scan data store maintained by the PaaS system controller. Similarly, when new scan definitions are released, a scan component residing in the image repository scans all existing application images and updates central scan data store with the results. 
         [0015]    Furthermore, scan components at each node in the system are configured to scan the running (e.g., top-most) layer of each application image instance on the node, while ignoring all other layers of the application image. Each application image includes multiple layers of files, with the top-most layer of an application image instance running in a node being configurable, while the remaining lower layer are immutable or unchangeable. As a result of running a scan of the built application image at build-time, the lower layer of an application image instance running on a node is assumed to be clean in terms of scanning. Consequently, the scan components at nodes scan just the top-most configurable layer of the running application components on the node, thus saving resources in the PaaS system that were previously consumed in running full image scans at the nodes. 
         [0016]    Previous solutions for providing image and container scanning for a PaaS system would run scans on entire images and application files maintained at the nodes in the PaaS system. Even when the previous scanning solutions provided for scanning of those application files that had not been modified or had been scanned recently, the previous solutions still had to perform full system scans of the application files at the nodes periodically to ensure security of the PaaS system. Implementations of the disclosure provide for efficient and optimized scanning of application images in a PaaS system by scanning a portion of an application image at a node without having to perform a full scan of the application image at any point in time at the node, thus conserving and reducing PaaS system resource usage. 
         [0017]      FIG. 1  is a block diagram of a network architecture  100  in which implementations of the disclosure may operate. The network architecture  100  includes a cloud  130  managed by a cloud provider system  104 . The cloud provider system  104  provides nodes  111 ,  112 ,  121 ,  122  to execute software and/or other processes. In some implementations these nodes are virtual machines (VMs) that are hosted on a physical machine, such as host  1   110  through host N  120 , configured as part of the cloud  130 . In some implementations, the host machines  110 ,  120  are often located in a data center. For example, nodes  111  and  112  are hosted on physical machine  110  in cloud  130  provided by cloud provider  104 . When nodes  111 ,  112 ,  121 ,  122  are implemented as VMs, they may be executed by OSes  115 ,  125  on each host machine  110 ,  120 . 
         [0018]    In some implementations, the host machines  110 ,  120  are often located in a data center. Users can interact with applications executing on the cloud-based nodes  111 ,  112 ,  121 ,  122  using client computer systems, such as clients  160 ,  170  and  180 , via corresponding client software  161 ,  171 ,  181 . Client software  161 ,  171 ,  181  may include an application such as a web browser. In other implementations, the applications may be hosted directly on hosts  1  through N  110 ,  120  without the use of VMs (e.g., a “bare metal” implementation), and in such an implementation, the hosts themselves are referred to as “nodes”. 
         [0019]    Clients  160 ,  170 , and  180  are connected to hosts  110 ,  120  in cloud  130  and the cloud provider system  104  via a network  102 , which may be a private network (e.g., a local area network (LAN), a wide area network (WAN), intranet, or other similar private networks) or a public network (e.g., the Internet). Each client  160 ,  170 ,  180  may be a mobile device, a PDA, a laptop, a desktop computer, a tablet computing device, a server device, or any other computing device. Each host  110 ,  120  may be a server computer system, a desktop computer or any other computing device. The cloud provider system  104  may include one or more machines such as server computers, desktop computers, etc. 
         [0020]    In one implementation, the cloud provider system  104  is coupled to a cloud controller  108  via the network  102 . The cloud controller  108  may reside on one or more machines (e.g., server computers, desktop computers, etc.) and may manage the execution of applications in the cloud  130 . In some implementations, cloud controller  108  receives commands from PaaS system controller  140 . Based on these commands, the cloud controller  108  provides data (e.g., such as pre-generated images) associated with different applications to the cloud provider system  104 . In some implementations, the data may be provided to the cloud provider  104  and stored in an image repository  106 , in an image repository (not shown) located on each host  110 ,  120 , or in an image repository (not shown) located on each VM  111 ,  112 ,  121 ,  122 . This data may be used for the execution of applications for a multi-tenant PaaS system managed by the PaaS provider controller  140 . 
         [0021]    In one implementation, the data used for execution of applications includes application images built from preexisting application components and source code of users managing the application. As discussed above, an image refers to data representing executables and files of the application used to deploy functionality for a runtime instance of the application. In one implementation, the image is built using a Docker™ tool, and is referred to as a Docker image. An application image may be built in the PaaS system using an image build system  190  of the PaaS system. The image build system  190  may be provided on components hosted by cloud  130 , on a server device external to the cloud  130 , or even run on nodes  111 ,  112 ,  121 ,  122  (not shown). The image build system  190  generates an application image for an application by combining preexisting ready-to-run application image corresponding to core functional components of the application (e.g., a web framework, database, etc.) with source code specific to the application provided by the user. The resulting application image may be pushed to image repository  106  for subsequent use in launching instances of the application images for execution in the PaaS system. 
         [0022]    Upon receiving a command identifying specific data (e.g., application data and files, such as application images, used to initialize an application on the cloud) from the PaaS provider controller  140 , the cloud provider  104  retrieves the corresponding data from the image repository  106 , creates an instance of it, and loads it to the hosts  110 ,  120  to run on nodes  111 ,  112 ,  121 ,  122 . In addition, a command may identify specific data to be executed on one or more of the nodes  111 ,  112 ,  121 , and  122 . The command may be received from the cloud controller  108 , from the PaaS system controller  140 , or a user (e.g., a system administrator) via a console computer or a client machine. The image repository  106  may be local or remote and may represent a single data structure or multiple data structures (databases, repositories, files, etc.) residing on one or more mass storage devices, such as magnetic or optical storage based discs, solid-state-drives (SSDs) or hard drives. 
         [0023]    In one implementation, multiple scan components  150  are located at nodes  111 ,  112 ,  121 ,  122 , image repository  106 , and an image build system  190 . Scan component  150  may include one or more pluggable scanning processes installed to provide pattern detection in order to identify threats (e.g., viruses, malware, other unwanted processes, etc.) existing in the PaaS system. Implementations of the disclosure optimize scanning performed by scan component  150  of images and runtime environments of applications of the PaaS. Multiple scan components  150  are distributed throughout the PaaS system to provide for separate build-time, runtime and image repository scans. The multiple scan components  150  are optimized to take advantage of the image-based model for application deployment utilized by the PaaS. Full application image scans may be performed by a scan component  150  residing at the image build system  190 . Each time an application image is built, scan component  150  analyzes the output of the build to determine whether the application image is clean. A result of the built application image scan process is stored in a central scan data store  145  maintained by the PaaS system controller  140 . Similarly, when new scan definitions are released, a scan component  150  residing in the image repository scans all existing application images and updates central scan data store  145  with the results. 
         [0024]    Scan components  150  at each of nodes  111 ,  112 ,  121 ,  122  are configured to scan the running (e.g., top-most) layer of each application image instance on the node  111 ,  112 ,  121 ,  122 , while ignoring all other layers of the application image. Each application image includes multiple layers of files, with the top-most layer of an application image instance running in a node  111 ,  112 ,  121 ,  122  being configurable, while the remaining lower layer are immutable or unchangeable. As a result of running a scan of the built application image at build-time, the lower layers of an application image instance running on a node are assumed to be clean in terms of scanning. Consequently, the scan components  150  at nodes  111 ,  112 ,  121 ,  122  scan just the top-most configurable layer of running application components on the node  111 ,  112 ,  121 ,  22 , thus saving resources in the PaaS system that were previously consumed in running full image scans at the nodes  111 ,  112 ,  121 ,  122 . Further details of scan components  150  and its related workflows can be found below with respect to  FIGS. 2 through 5 . 
         [0025]    While various implementations are described in terms of the environment described above, those skilled in the art will appreciate that the facility may be implemented in a variety of other environments including a single, monolithic computer system, as well as various other combinations of computer systems or similar devices connected in various ways. For example, the data from the image repository  106  may run directly on a physical host  110 ,  120  instead of being instantiated on nodes  111 ,  112 ,  121 ,  122 . In some implementations, an environment other than a VM may be used to execute functionality of PaaS applications. As such, in some implementations, a “node” providing computing functionality may provide the execution environment for an application of the PaaS system. The “node” may refer to a VM or any other type of computing environment. 
         [0026]      FIG. 2  is a block diagram of a multi-tenant PaaS system architecture  200  according to an implementation of the disclosure. The PaaS architecture  200  allows users to launch software applications in a cloud computing environment, such as cloud computing environment provided in network architecture  100  described with respect to  FIG. 1 . The PaaS system architecture  200 , in one implementation, includes a client layer  210 , a PaaS master layer  220 , and a node layer  230 . 
         [0027]    In one implementation, the components of the PaaS system architecture are in communication with each other via a network (not shown). The network may include, for example, the Internet in one implementation. In other implementations, other networks, wired and wireless, such as an intranet, local area network (LAN), wide area network (WAN), or broadcast network may be used. 
         [0028]    In one implementation, the client layer  210  resides on a client machine, such as a workstation of a software developer, and provides an interface to a user of the client machine to the PaaS master layer  220  of the PaaS system  200 . In one implementation, the client machine can be a client  160 ,  170 ,  180  described with respect to  FIG. 1 . The PaaS master layer  220  may facilitate the creation and deployment on the cloud (via node layer  230 ) of software applications being developed by an end user at client layer  210 . 
         [0029]    In one implementation, the client layer  210  includes a source code management system  212 , sometimes referred to as “SCM” or revision control system. One example of such an SCM or revision control system is Git, available as open source software. Another example of an SCM or revision control system is Mercurial, also available as open source software. Git, Mercurial, and other such distributed SCM systems typically include a working directory for making changes, and a local software repository for storing the changes for each application associated with the end user of the PaaS system  200 . The packaged software application can then be “pushed” from the local SCM repository to a remote SCM repository, such as repositories  233   a,    233   b,    233   c,  at the node(s)  232   a,    232   b,    232   c  running the associated application. From the remote SCM repository  233   a,    233   b,    233   c,  the code may be edited by others with access, or the application may be executed by a machine. Other SCM systems work in a similar manner. 
         [0030]    The client layer  210 , in one implementation, also includes a set of command line tools  214  that a user can utilize to create, launch, and manage applications. In one implementation, the command line tools  214  can be downloaded and installed on the user&#39;s client machine, and can be accessed via a command line interface or a graphical user interface, or some other type of interface. In one implementation, the command line tools  214  expose an application programming interface (“API”) of the PaaS master layer  220  and perform other applications management tasks in an automated fashion using other interfaces, as will be described in more detail further below in accordance with some implementations. 
         [0031]    In one implementation, the PaaS master layer  220  acts as middleware between the client layer  210  and the node layer  230 . The node layer  230  includes the nodes  232   a - c  on which applications  235   a - c  are provisioned and executed. In one implementation, each node  232   a - c  is a VM. In some implementations, the VMs are provisioned by an Infrastructure as a Service (IaaS) provider. In other implementations, the nodes  232   a - c  may be physical machines or VMs residing on a single physical machine. In one implementation, the PaaS master layer  220  is implemented on one or more machines, such as server computers, desktop computers, etc. In some implementations, the PaaS master layer  220  may be implemented on one or more machines separate from machines implementing each of the client layer  210  and the node layer  230 , or may be implemented together with the client layer  210  and/or the node layer  230  on one or more machines, or some combination of the above. 
         [0032]    In one implementation, the PaaS master layer  220  includes a PaaS master component  222  that coordinates requests from the client layer  210  with actions to be performed at the node layer  230 . Examples of the requests can include a request to create an application, a request to perform an action on a container (e.g., creating, removing, and/or managing a container), a request to deploy source code of an application, a request to designate a system to host a remote SCM repository (e.g., an indication that a system has been designated by a user to host a remote SCM repository), etc. 
         [0033]    In one implementation, a user, using the command line tools  214  at client layer  210 , can request the creation of a new application  235   a - c,  deployment of source code of the application  235   a - c,  the designation of a system that hosts a remote SCM repository, etc. In response to receiving such a request, the PaaS master component  222  may first authenticate the user using an authentication service  224 . In one implementation, the authentication service  224  may comprise custom authentication methods, or standard protocols such as SAML, Oauth, etc. Once the user has been authenticated and allowed access to the system by authentication service  224 , the PaaS master component  222  uses a server orchestration system  226  to collect information and configuration information about the nodes  232   a - c.    
         [0034]    In one implementation, the PaaS master component  222  uses the ETCD™ service available from CoreOS™ as the server orchestration system  226 , but other server orchestration systems may also be used. The server orchestration system  226 , in one implementation, functions to coordinate server-client interaction between multiple (sometimes a large number of) servers. In one implementation, the servers being orchestrated are nodes  232   a - c,  which are acting as application servers and web servers. 
         [0035]    In one implementation, the PaaS master component  222  manages the business logic and model representing the nodes  232   a - c  and the applications  235   a - c  residing on the nodes, and acts as a controller that generates the actions requested by users via an API of the command line tools  214 . The server orchestration system  226  then takes the actions generated by the PaaS master component  222  and orchestrates their execution on the many nodes  232   a - c  managed by the system. 
         [0036]    In one implementation, the information collected about the nodes  232   a - c  can be stored in a data store  228 . In one implementation, the data store  228  can be a locally-hosted database or file store, or it can be a cloud-based storage service provided by a Software-as-a-Service (SaaS) provider. The PaaS master component  222  uses the information about the nodes  232   a - c  and their applications  235   a - c  to model the application hosting service and to maintain records about the nodes. In one implementation, data of a node  232   a - c  is stored in the form of a JavaScript™ Object Notation (JSON) blob or string that maintains key-value pairs to associate a unique identifier, a hostname, a list of applications, and other such attributes with the node. 
         [0037]    In implementations of the disclosure, the PaaS system architecture  200  of  FIG. 2  is a multi-tenant PaaS environment. In a multi-tenant PaaS environment, each node  232   a - c  runs multiple applications  235   a - c  that may be owned or managed by different users and/or organizations. As such, a first customer&#39;s deployed applications  235   a - c  may co-exist with any other customer&#39;s deployed applications on the same node  232  that is hosting the first customer&#39;s deployed applications  235   a - c.  In some implementations, portions of an application execute on multiple different nodes  232   a - c.  For example, as shown in  FIG. 2 , components of application  1   235   a  run in both node  232   a  and node  232   b.  Similarly, components of application  2   235   b  may run in node  232   a  and node  232   c,  while components of application  3   235   c  may run in node  232   b  and  232   c.    
         [0038]    In one implementation, each node  232   a - c  is implemented as a VM and has an operating system  234   a - c  that can execute applications  235   a - c  using the repositories  233   a - c  that are resident on the nodes  232   a - c.  Each node  232   a - c  also includes a server orchestration system agent (not shown) configured to track and collect information about the node  232   a - c  and to perform management actions on the node  232   a - c.  The server orchestration system agent may operate in tandem with the server orchestration system  226  to send requests, queries, and commands between the node  232   a - c  and the PaaS master layer  220 . 
         [0039]    As discussed above, node  232   a - c  runs multiple applications  235   a - c.  A node  232   a - c  runs an application by launching an instance of an application image as a container  240  in the node  232   a - c.  An application image includes the underlying support software that implements the functionality of applications  235   a - c.  An application image for an application may be built by build system  260 , which may be separate from or part of node layer  230 . Build system  260  may be the same as image build system  190  described with respect to  FIG. 1 . 
         [0040]    As discussed above, build system  260  may generate an application image from a combination of preexisting ready-to-run application images related to core functionality of the application and source code provided by a user of the application. For example, the preexisting ready-to-run application images may include support software providing functionality (e.g., configuration templates, scripts, dependencies, etc.) used to run the application  235   a - c  and/or add a feature to the application  235   a - c.  For example, the images may support languages such as, but not limited to, Java™, PHP, Ruby, Python, Perl, and so on. In addition, application images may be generated that support databases, such as MySQL™, PostgreSQL™, Mongo™, and others. Preexisting ready-to-run application images may also include those that support the build and continuous integration environments, such as a Jenkins-based image. Lastly, preexisting ready-to-run application images may be used to support management capabilities and/or tools, such as PHPmyadmin, RockMongo™, 10gen-mms-agent, cron scheduler, HAProxy, Maven, and Gradle, for example. 
         [0041]    Each application image built by build system  260  may map to a functional component of the application  235   a - c.  As such, an application may have more than one application image associated with the application. Built application images may be pushed to image repository  270  for storage and accessibility for subsequent use in launching instances of the application images at containers  240  in nodes  232   a - c.  Image repository  270  may be the same image repository  106  described with respect to  FIG. 1 . 
         [0042]    A container  240  is a resource-constrained process space on the node  232   a - c  to execute functionality of an application  235   a - c.  In some implementations, a container  240  is established by the node  232   a - c  with resource boundaries, including a limit and/or designation of the amount of memory, amount of storage, and security types and/or labels to be applied to any functions executed by the container  240 . In one implementation, containers  240  may be established using the Linux Containers (LXC) method. In further implementations, containers  240  may also be established using cgroups, SELinux™, and kernel namespaces, to name a few examples. 
         [0043]    Application image instances for an application  235   a - c  may be launched in containers  240  dispersed over more than one node  232   a - c.  In other implementations, application image instances for an application  235   a - c  may run in one or more containers  240  on the same node  232   a - c.  Furthermore, an application  235   a - c  may use more than one application image  240  as part of providing functionality for the application  235   a - c.  One example of this is a JavaEE™ application that uses a JBoss™ application server-based application image with a supporting MySQL™ database provided by a MySQL™-based application image. 
         [0044]    In one implementation, multiple scan components  250  are located at nodes  232   a - c,  image build system  260 , and image repository  270 . Scan components  250  may be the same as scan component  150  described with respect to  FIG. 1 . Each scan component  250  may include one or more pluggable scanning processes (e.g., clamav, rkhunter, malware finder, etc.) installed to provide pattern detection in order to identify threats (e.g., viruses, malware, other unwanted processes, etc.) existing in the PaaS system  200 . Implementations of the disclosure optimize scanning by scan components  250  of images and runtime environments of applications of the PaaS system  200 . 
         [0045]    Multiple scan components  250  are distributed throughout the PaaS system to provide for separate build-time, runtime and image repository scans. The multiple scan components  250  are optimized to take advantage of the image-based model for application deployment utilized by the PaaS. Full application image scans may be performed by a scan component  250  residing at the image build system  260 . Each time an application image is built by build system  260 , scan component  250  analyzes the output of the build to determine whether the application image is clean. For example, the scan component  250  may run pattern detection according to a definition file configured at the scan component  250  on each layer of the built application image. 
         [0046]    A result of the built application image scan process is stored in a central scan database  280  maintained by the PaaS master layer  220 , for example in data store  228 . Central scan database  280  may be the same as central scan data store  145  described with respect to  FIG. 1 . In one implementation, the information maintained in central scan database  280  includes, but is not limited to, a unique identifier of the layer of the image being scanned (e.g., a checksum of the layer), the scan process (e.g., clamav, rkhunter, etc.), a definition version of the scan process run against the image layer, and a result of the scan (e.g., clean, failed, etc.). 
         [0047]    In some implementations, the scan component  250  at the build system  260  may utilize previous scan results to streamline the scan process of a built application image by skipping a scan of the layers of the built application image that have already been scanned in previous scans (as documented in the central scan database  280 ). For example, previous scans of the application image layers corresponding to the previously-existing ready-to-run application images used to build the new application image may be used to skip the scan process for those layers in the newly built image. In one implementation, a “diff” process may be utilized between the previously-existing ready-to-run image and the newly-built image in order to identify the differences that should be scanned by scan component  250 . 
         [0048]    In one implementation, if an application image layer fails the scan process (e.g., a defined pattern is detected by the scan component  250 ), then the scan component  250  alerts a monitoring component  290  of the PaaS master component  222 . The monitoring component  290  may begin a takedown process to remove the application image from the PaaS system. 
         [0049]    When new scan definitions are released, a scan component  250  residing in the image repository  270  scans all existing application images and updates central scan database  280  with the scan results. If a pattern is detected in any of the application images maintained at image repository  270 , then the scan component provides a list of images affected by the failed scan to the monitoring component  290 . The monitoring component  290  then determines which running containers  240  include any of the images in the list, and initiates a takedown process for those containers  240  as well as the affected images in the image repository  270 . 
         [0050]    Scan components  250  at each of nodes  232   a - c  are configured to scan the running (e.g., top-most) layer of each application image instance on containers  240  of the node  232   a - c,  while ignoring all other layers of the application image. Each application image includes multiple layers of files, with the top-most layer of an application image instance running as a container  240  being configurable, while the remaining lower layers are immutable or unchangeable. As a result of running a scan of the built application image at build-time as described above, the lower layer of an application image instance running on a node  232   a - c  is assumed to be clean in terms of scanning. Consequently, the scan components  250  at nodes  232   a - c  scan just the top-most configurable layer of running application components on the node  232   a - c,  thus saving resources in the PaaS system that were previously consumed in running full image scans at the nodes  232   a - c.  The scan components  250  at each node may be configured to run on an iterative time period (e.g., once a day, etc.) to examine all running containers  240  on the node. 
         [0051]      FIG. 3  is a flow diagram illustrating a method  300  for build-time image scanning in a multi-tenant PaaS system according to an implementation of the disclosure. Method  300  may be performed by processing logic that may comprise hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (such as instructions run on a processing device), firmware, or a combination thereof. In one implementation, method  300  is performed by scan component  250  of build system  260  of  FIG. 2 . 
         [0052]    Method  300  begins at block  310  where an indication of a completion of a build process for a new application image is received. Then, at block  320 , a scan process is invoked on the new application image. At block  330 , the portions of the new application image corresponding to previously-scanned and clean application image layers are identified. In one implementation, the previously-scanned and clean application image layers may correspond to core functionality base image(s) of the PaaS system used to build the application in combination with source code provided by an owner of the application. A central scan data store of the PaaS system may include information indicating which application images have been scanned with a clean result. 
         [0053]    At block  340 , the remaining portions of the new application image that are not part of the identified portions are scanned. In some implementations, a diff process between the previously-scanned and clean application images and the new application image may be used to determine the remaining portions of the new application image for scanning. The scanning process may detect patterns in the remaining portions of the new application image that are defined in a configured definition file for the scan process. 
         [0054]    At block  350 , information pertaining to the scan results is stored in a central scan data store maintained by the PaaS system. In one implementation, the information may include, but is not limited to, a unique ID for the application image layer scanned (e.g., a checksum of the application layer), a scan process run against the application image layer, a definition file version run against the application image layer, and result of the scan (e.g., clean, failed, etc.). At decision block  360 , it is determined whether the scan results were clean. If so, method  300  ends. On the other hand, if the scan results failed, then method  300  continues to block  370  where the failed scan results are reported to a monitoring component of the PaaS system in order to initiate a takedown process for the new application image. Then method  300  ends. 
         [0055]      FIG. 4  is a flow diagram illustrating a method  400  for runtime container and image scanning in a multi-tenant PaaS system according to an implementation of the disclosure. Method  400  may be performed by processing logic that may comprise hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (such as instructions run on a processing device), firmware, or a combination thereof. In one implementation, method  400  is performed by scan component  250  of nodes  232   a - c  of  FIG. 2 . 
         [0056]    Method  400  begins at block  410  where an indication is received to begin a scan process at a node of the PaaS system. In one implementation, the scan process is configured to run on the node on a recurring and iterative basis (e.g., once a day, etc.). At block  420 , for each running container on the node, a top-most configurable layer of an instance of the application image used to launch the container is scanned. The scanning process may detect patterns in the remaining portions of the new application image that are defined in a configured definition file for the scan process. 
         [0057]    At decision block  430 , it is determined whether the scan results are clean. If so, then at block  440 , the scan process for each of the running containers with clean scans is terminated. On the other hand, if the scan results failed at decision block  430 , then at block  450  the failed scan results are reported to a monitoring component of the PaaS system. The monitoring component may then initiate a takedown process for any of the containers with failed scan results. 
         [0058]      FIG. 5  is a flow diagram illustrating a method  500  for re-scanning application images in a multi-tenant PaaS system according to an implementation of the disclosure. Method  500  may be performed by processing logic that may comprise hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (such as instructions run on a processing device), firmware, or a combination thereof. In one implementation, method  500  is performed by scan component  250  of image repository  270  of  FIG. 2 . 
         [0059]    Method  500  begins at block  510  where a new definition file is received for a scan process of a scan component installed at an image repository of a PaaS system. At block  520 , the scan process is configured with the new definition file. Then, at block  530 , the scan process is invoked for each application image stored in the image repository. In one implementation, the invoked scan process detects patterns defined in the new configured definition file for the scan process. 
         [0060]    At block  540 , information pertaining to the scan results is stored in a central scan data store maintained by the PaaS system. In one implementation, the information may include, but is not limited to, a unique ID for the application image layer scanned (e.g., a checksum of the application layer), a scan process run against the application image layer, a definition file version run against the application image layer, and result of the scan (e.g., clean, failed, etc.). 
         [0061]    Then, at decision block  550 , it is determined whether the scan results are clean. If so, method  500  ends. Other the other hand, if the scan results failed, then method  500  continues to block  560  where the failed scan results and a list of affected application images are reported to a monitoring component of the PaaS system. In one implementation, the monitoring component uses the reporting information to identify running containers utilizing the affected application images and to initiate a takedown process for the running containers at their nodes. In addition, the monitoring component initiates a takedown process for the affected application images themselves. Then, method  500  ends. 
         [0062]      FIG. 6  illustrates a diagrammatic representation of a machine in the example form of a computer system  600  within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative implementations, the machine may be connected (e.g., networked) to other machines in a LAN, an intranet, an extranet, or the Internet. The machine may operate in the capacity of a server or a client device in a client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a server, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. 
         [0063]    The computer system  600  includes a processing device  602 , a main memory  604  (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) (such as synchronous DRAM (SDRAM) or DRAM (RDRAM), etc.), a static memory  606  (e.g., flash memory, static random access memory (SRAM), etc.), and a data storage device  618 , which communicate with each other via a bus  608 . 
         [0064]    Processing device  602  represents one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like. More particularly, the processing device may be complex instruction set computing (CISC) microprocessor, reduced instruction set computer (RISC) microprocessor, very long instruction word (VLIW) microprocessor, or processor implementing other instruction sets, or processors implementing a combination of instruction sets. Processing device  602  may also be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. The processing device  602  is configured to execute the processing logic  625  for performing the operations and steps discussed herein. 
         [0065]    The computer system  600  may further include a network interface device  622  communicably coupled to a network  664 . The computer system  600  also may include a video display unit  610  (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)), an alphanumeric input device  612  (e.g., a keyboard), a cursor control device  614  (e.g., a mouse), and a signal generation device  616  (e.g., a speaker). 
         [0066]    The data storage device  618  may include a machine-readable (or machine-accessible) storage medium  624  on which is stored software  626  embodying any one or more of the methodologies of functions described herein. The software  626  may also reside, completely or at least partially, within the main memory  604  as instructions  626  and/or within the processing device  602  as processing logic  625  during execution thereof by the computer system  600 ; the main memory  604  and the processing device  602  also constituting machine-readable storage media. 
         [0067]    The machine-readable storage medium  624  may also be used to store instructions  626  to implement a scan component  250  to provide image and container scanning for a PaaS system in a computer system, such as the computer system described with respect to  FIG. 1 , and/or a software library containing methods that call the above applications. While the machine-readable storage medium  624  is shown in an example implementation to be a single medium, the term “machine-readable storage medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “machine-readable storage medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instruction for execution by the machine and that cause the machine to perform any one or more of the methodologies of the disclosure. The term “machine-readable storage medium” shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media. 
         [0068]    In the foregoing description, numerous details are set forth. It will be apparent, however, that the disclosure may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the disclosure. 
         [0069]    Some portions of the detailed descriptions which follow are presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of steps leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. 
         [0070]    It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise, as apparent from the following discussion, it is appreciated that throughout the description, discussions utilizing terms such as “sending”, “receiving”, “attaching”, “forwarding”, “caching”, “referencing”, “determining”, “initiating”, “scanning” , “terminating” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system&#39;s registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices. 
         [0071]    The disclosure also relates to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, or it may comprise a general purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a machine readable storage medium, such as, but not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any type of media suitable for storing electronic instructions, each coupled to a computer system bus. 
         [0072]    The algorithms and displays presented herein are not inherently related to any particular computer or other apparatus. Various general purpose systems may be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will appear as set forth in the description below. In addition, the disclosure is not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the disclosure as described herein. 
         [0073]    The disclosure may be provided as a computer program product, or software, that may include a machine-readable medium having stored thereon instructions, which may be used to program a computer system (or other electronic devices) to perform a process according to the disclosure. A machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer). For example, a machine-readable (e.g., computer-readable) medium includes a machine (e.g., a computer) readable storage medium (e.g., read only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices, etc.), etc. 
         [0074]    The terms “first”, “second”, “third”, “fourth”, etc. as used herein are meant as labels to distinguish among different elements and may not necessarily have an ordinal meaning according to their numerical designation. 
         [0075]    Whereas many alterations and modifications of the disclosure will no doubt become apparent to a person of ordinary skill in the art after having read the foregoing description, it is to be understood that any particular implementation shown and described by way of illustration is in no way intended to be considered limiting. Therefore, references to details of various implementations are not intended to limit the scope of the claims, which in themselves recite only those features regarded as the disclosure.