Patent Description:
This disclosure is generally concerned with edge device platforms. More specifically, this disclosure relates to composing these platforms utilizing a corresponding manifest that specifies the configuration for that device.

In cloud computing, processing and storage are generally performed by one or more service providers implemented at a centralized location. Data can be received from customers at the centralized location, processed there, and then the processed (or other) data can be transmitted back to customers. However, having a centralized location for cloud infrastructure components may not be ideal in various scenarios. For example, when there are hundreds or thousands of Internet of Things (IoT) devices transmitting data to the central servers, and especially when those IoT devices are not geographically close to the cloud infrastructure computing devices, conventional centralized systems are not ideal. These IoT devices may be considered on the "edge," as in they are not close to the central servers.

Additionally, there may be other instances when the centralized location for cloud components is less than ideal. For example, if the data is collected (e.g., by IoT devices) in a disconnected region or a location with no Internet connectivity (e.g., remote locations). Current centralized cloud computing environments may not meet time sensitivity requirements when streaming data due to the inherent latency of their wide-area network connections. Remotely generated data may need to be processed more quickly (e.g., to detect anomalies) than conventional centralized cloud computing systems allow. Thus, there are challenges with managing a traditional cloud computing environment that relies on centralized components. For example, a centralized workflow manager may be suboptimal for managing workflows at geographically remote devices.

Relevant background is described in "<NPL>, and in "<NPL>.

Techniques are provided (e.g., a method, a system, non-transitory computer-readable medium storing code or instructions executable by one or more processors) for composing various platforms such as a cloud-infrastructure edge computing device (e.g., a computing device configured to deliver computing and storage at remote locations separate from the centralized data center and lacking a public/private network connection). In some embodiments, composing these platforms may utilize a corresponding manifest that specifies the configuration for that device.

The invention is defined by the independent claims, dependent claims define preferred embodiments.

In some examples, a cloud-integrated edge service (e.g., implemented in an edge computing device) may be integral in addressing the desire to run time-sensitive cloud infrastructure application outside of a centralized data center (e.g., a datacenter of a cloud infrastructure service provider). Such an edge computing device may deliver computing and storage at the edge and/or in disconnected locations (e.g., remote locations separate from the centralized data center and lacking a public/private network connection (e.g., an Internet connection, a VPN connection, a dedicated connection, etc.) to enable low-latency processing at or near the point of data generation and ingestion. In some instances, a fleet of portable (which may be ruggedized for protection) server nodes (e.g., a fleet of edge devices) may be configured to physically bring the cloud infrastructure service to remote locations where cloud technology has been considered technologically infeasible or too cost prohibitive to implement.

To a customer (e.g., a user), the edge computing device can act as an extension of their cloud infrastructure: including virtual machines (VMs), containers, functions and data files, block volumes or object store services can also be delivered from the cloud infrastructure tenancy (e.g., a tenancy of the centralized cloud computing environment) with little to no modifications, and the customer experience may remain unchanged from that of the centralized cloud computing experience. Additionally, the edge computing device may be configured to implement both a control plane and a data plane that are part of a cloud infrastructure service provider. The data plane can be configured to manage data storage, migration, processing, etc., while the control plan can be configured for controlling the various services and architecture components of the computing device. Once the edge computing device is properly connected to a customer computing device (e.g., via a local area network (LAN)), the customer may be able to utilize the IaaS service (or at least a subset of it) using the same SDK and API used with the centralized cloud service.

The edge computing device can be delivered to a customer in a pre-configured form, such that the only action that might be required of the customer is to connect the nodes to a network (e.g., a local/on premise network that is accessible by a user computing device), power them up, and/or log in. The device can be pre-configured in various ways based on customer preference/request, or it can be in one of various configurations (e.g., storage-centric, compute-centric, etc.). The node or cluster of nodes can be portable and is intended to be mobile - when moved and set up again (or used while in motion), the deployment continues to run from where it turned off (or continuously). The edge computing device can also monitor for wide area network (WAN) connection availability (e.g., the Internet or the like), and can synchronize customer and management data with the cloud once connected to a WAN.

Some potential use cases for the edge computing device include: storage and processing, compute and input/output (I/O) intensive applications, machine learning, remote computing, low latency database and analytics, and data collection and migration. More specifically, the edge device can be used for storage and processing of large volumes of images, video, audio, and IoT sensor data generated in environments where WAN connection is latent or unavailable (e.g., in remote areas, an oil off-shore platform, or the like). Once this data is pre-processed, filtered, compressed, and/or secured it may be transported or transferred to the cloud service provider, where it can be further processed by the centralized server (e.g., traditional cloud service provider). The device can also be used for compute and I/O intensive applications, where low latency is paramount, such as tactical reconnaissance or <NUM> communications. The device can also be used for machine learning, with models trained in the cloud and running in disconnected locations to improve efficiency, intelligence, and/or productivity in manufacturing, document management, transportation, oil and gas mining, and/or telecommunications. It can also be used for remote computing requiring elevated security and airtight containment of data. Additionally, the device can be used for low latency database and analytics workloads, with more applications optimized over time. Further, the device can also be used for data collection and migration of large sets of object and database management system (DBMS) data into a cloud service provider, e.g., at faster speeds and lower cost than a WAN transfer.

The edge device can natively support distributed cloud paradigms, where complex, multi-stage compute workflows can be separated into individual components, which in turn can be deployed to the infrastructure of the edge device, on premise, and/or in the cloud. An example of such distributed workflow is represented in the following scenario. Massive amounts of data can be collected by an edge computing node deployed on an airplane (e.g., a military jet) in a reconnaissance operation with no Internet access (e.g., a disconnected edge computing device), where this data is be pre-processed in near real time by a machine learning model previously trained by the cloud service provider that provided the edge device. Even the first pass of processing the data with the models can detect significant anomalies and can alert personnel immediately - for example, a bridge may be destroyed and therefore the troops should be rerouted. When the airplane lands, the edge computing device can be physically connected to a network (e.g., an edge station potentially deployed at the airstrip). The pre-processed, filtered, smaller dataset can be loaded for final processing to a cluster of edge computing device nodes at the edge station. The original edge computing device can be released and can be loaded on another (or the same) airplane, for example to support the next mission. When processing at the edge station is complete, a 3D map update can be issued for immediate use. Change sets can then be uploaded by the edge station cluster to a datacenter and can be used to build future models providing intelligent tactical forecasts to the reconnaissance operation, or the like.

It should be appreciated that the following techniques may be employed in a variety of contexts such as telecommunications, oil and gas, healthcare, hospitality, agriculture, transportation, and logistics, and the like.

Embodiments described herein address these and other problems, individually and collectively. Specifically, embodiments of the present disclosure provide for a cloud infrastructure edge computing device.

An edge computing device (sometimes referred to as "a cloud-computing edge device," a "cloud infrastructure edge computing device," or an "edge device," for brevity), extends a user's centralized cloud computing tenancy by physically putting customer infrastructure and platform services where data is generated - on the edge, on premise, or completely disconnected. Each deployment is created to address specific customer needs by provisioning VM instance images and data from the customer's centralized cloud tenancy. These workloads remain fully functional offline as the edge device adapts to the connection state, operates in harsh environmental conditions, and is ready to sync with the cloud whenever the connection is re-established.

<FIG> is a block diagram of an example high-level architecture for a cloud infrastructure edge computing device (e.g., edge device <NUM>), according to at least one embodiment. An overview of the software and hardware component of the edge device <NUM> is provided below.

In some examples, the edge device <NUM> may include containerization engine <NUM> (e.g., Docker, Kubernetes, etc.) configured to implement one or more containers (e.g., corresponding to container(s) 104A, 104B, 104C, to 104N, collectively referred to as "container(s) <NUM>"). A containerization engine (e.g., the containerization engine <NUM>) may be container-orchestration system for automating computer application deployment, scaling, and management. In some embodiments, the containerization engine may be configured to provide OS-level virtualization to deliver software in packages called containers. These containers can be isolated from one another and utilize respective software, libraries, and configuration files, and can communicate with each other through well-defined channels. In some embodiments, service(s) <NUM> may include any suitable number of services (e.g., one or more). These services may implement at least some portion of centralized cloud capabilities. Each service may be stand-alone or operate as a distributed cluster. The edge device <NUM> may further include a hypervisor <NUM> configured to implement one or more virtual machines (e.g., virtual machines 108A, 108B, 108C, to 108N, collectively referred to as "virtual machine(s) <NUM>" or "VMs <NUM>").

In some examples, the edge device <NUM> includes storage <NUM> (e.g., object and/or block storage for storing local data). The edge device <NUM> includes operating system (OS) <NUM>. In some embodiments, the OS <NUM> may be optimized for executing on an edge device and/or specific to execution on an edge device. OS <NUM> may be configured to manage the hardware of edge device <NUM> and supports a data plane of the services running on the edge device <NUM>. The OS <NUM> may be configured to support a specific deployment type (e.g., a single edge device deployment, or a specific edge device cluster configuration). The OS <NUM> may be configured to secure the edge device by disallowing or otherwise blocking direct access by customers.

In some embodiments, the edge device <NUM> may include hardware such as any suitable number of central processing units (CPUs) and/or storage drives. For example, the edge device <NUM> depicted in <FIG> may have one, two, or more CPUs, with various numbers of cores per processing unit, and it may include any number of storage drives (e.g., <NUM> terabyte (TB) drives, or the like). As a non-limiting example, the edge device <NUM> may include block and/or object storage of any suitable size. The edge device <NUM> may include any suitable number of central processing units (CPUs), graphics processing units (GPUs), random access memory (RAM) of any suitable size, one or more ports (e.g., QSFP28, RJ45, dual ports, etc.), tamper-evident seals, or any suitable combination of the above components.

In some examples, the basic system functionality/services can be accessed via RESTful APIs which have a custom load of software based on Linux. The virtual machine(s) <NUM> may individually be a Kernel-based Virtual Machines (KVM) (e.g., a virtual machine managed by a virtualization module in the Linux kernel that allows the kernel to function as a hypervisor) and/or a hardware-based Virtual Machine (e.g., a virtual machine managed by a virtualizer, such as Quick EMUlator (QEMU), that can perform hardware virtualization to enable virtual machines to emulate of number of hardware architectures). Although storage <NUM> is represented as a separate component from the service(s) <NUM> and VM(s) <NUM>, it can run as a container (e.g., container 104A) or in a VM (e.g., VM 108A). In some examples, it may be favorable to implement the storage <NUM> (e.g., object storage, block storage, etc.) as a container.

<FIG> depicts an example architecture <NUM> for connecting the edge device described herein (e.g., edge device <NUM> from <FIG>) to a computing device <NUM> (e.g., a user computing device). The computing device <NUM> can be any type of computing device including, but not limited to, a laptop computer, a desktop computer, or the like. The edge device <NUM> (an example of the edge device <NUM> of <FIG>) may include containerization engine <NUM> (an example of the containerization engine <NUM> of <FIG>), hypervisor <NUM> (an example of the hypervisor <NUM> of <NUM>), and storage <NUM> (an example of the storage <NUM> of <NUM>).

Additionally, as mentioned briefly above, the edge device <NUM> may include an API proxy <NUM> for managing the RESTful API calls received from the computing device <NUM>. The API calls may enter the edge device <NUM> via network interface card (NIC) <NUM> that is internal to the edge device <NUM>. The NIC <NUM> may be used to connect the edge device <NUM> to the computing device <NUM> via a local area network (e.g., the LAN <NUM>). The API calls received by the NIC <NUM> may be transmitted to an exposed endpoint that may implement a Web server (e.g., endpoint <NUM>). The web server can transmit the requests to the API proxy <NUM>, which can route the requests to the appropriate service (e.g., containerization engine <NUM>, hypervisor <NUM>, and/or storage <NUM>). The exposed endpoint/web server may also be configured to implement the lightweight console that is for use by the customer (e.g., the user interface displayed on the computing device <NUM>).

The lightweight console can run within a web browser (e.g., Mozilla Firefox, or the like) on a laptop computer, desktop computer, or other network-accessible device (e.g., connected to the local area network (LAN <NUM>)) that is network-connected to the edge device <NUM> (e.g., via a router, cable, etc.). The edge device <NUM> can expose the endpoint <NUM> for the console connection, and the web server can transmit data to the web browser of the computing device <NUM> over the LAN <NUM>.

<FIG> illustrates an example physical enclosure <NUM> of the edge device described herein (e.g., edge device <NUM> from <FIG>). Various different form factors, shapes, colors, etc., can be employed to build a box (e.g., ruggedized) that can house the edge computing device. The physical enclosure can include handle <NUM>, as shown, and may include tamper evident elements, so that if anyone breaks the enclosure open, it will be evident. In this way, the service provider that provides the edge computing device can ensure that the device is not modified. In some examples, the physical enclosure <NUM> may not be possible to open. However, in some cases, it might be possible, but it would require extreme measures.

<FIG> illustrates an exploded view of the cloud infrastructure edge computing device described herein (e.g., edge device <NUM>, an example of the edge device <NUM> of <FIG>), in accordance with at least one embodiment. The various components described with respect to <FIG> and <FIG> can be communicatively attached to one or more motherboards and/or interface cards within the edge device <NUM>. The illustrated configuration of components is but just one implementation. The specific locations of components shown is not intended to be limiting, and as noted, any configuration that is capable of implementing the functionality described herein is acceptable. Once the components are installed, the entire box can be closed, sealed, and locked with tamper-evident components.

The edge device <NUM> is a single enclosure. The enclosure may be designed to house any suitable number of serially attached SCSI (SAS) solid-state drives (SSDs) and all other components (e.g., CPU, memory, GPU, etc.) within the enclosure. The system may include one or more (e.g., <NUM> Gb) SAS connections to each drive in a fully contained sheet metal enclosure designed to fit within a standard <NUM>" rack resting on an L bracket/shelf, on a table top or upright next to a desk with the use of a floor stand.

The system may include a tamper evident enclosure, front security plugs covering screws holding a front bezel in place with rear security interlock features. In some embodiments, the system may include a dual socket motherboard and any suitable amount of DRAM. In some embodiments, the system may include any suitable number (e.g., <NUM>, <NUM>, etc.) SATA SSDs, storage controllers, embedded network connections, one or more ports (e.g., dual ports, serial ports, etc.), one or more fans as part of a cooling system, or any suitable combination of the above.

As a non-limiting example, the edge device <NUM> may be made up of an external extruded aluminum case secured in the front with a vented bezel and rear panel only exposing I/O connections required for data transfer and management. Mounting can be designed to mount the any suitable motherboard, fans, and power supply.

<FIG> is a block diagram of an example computer architecture of a cloud infrastructure edge computing device (e.g., edge device <NUM>, an example of the edge devices <NUM> and <NUM>, of <FIG> and <FIG>, respectively), according to at least one embodiment. The edge device <NUM> can be thought of as a cloud-integrated service that extends some or all of conventional cloud capabilities to locations that may not be accessible by or have access to cloud data centers. This can be achieved via portable ruggedized server nodes that provide cloud-like functionality in locations with no WAN connectivity. This allows customers to shift select cloud workloads to remote locations and enable intensive data processing operations close to the data ingestion points at the edge of their cloud infrastructure.

The edge device <NUM> may include any suitable number of services (e.g., service(s) <NUM>). Each service may run as a container (e.g., a Docker container) locally on the edge device <NUM>. The service(s) <NUM> may be communicatively connected via a substrate network <NUM> such that the communications between services are encrypted (e.g., in accordance with a security protocol such as MACsec). Each container may be assigned a substrate IP address (e.g., a static address) with which traffic can be addressed. In some embodiments, a security protocol (e.g., MACsec) is configured at provisioning time (e.g., before the edge device <NUM> is shipped to the user). The edge device's system software (including service(s) <NUM>) may execute in the secure environments protected by boot security software (e.g., Trenchboot Secure Launch). Users may be restricted from accessing the secure environment and/or the substrate network <NUM>. To minimize the amount of resources used by these services, the service code may be compiled and saved to disk to decrease RAM space as well as decrease the CPU load on the edge device <NUM>.

Some example services included in service(s) <NUM> may include a UI console service, an identity control plane (CP) service, an identity data plane (DP) service, a compute application programming interface (API) service, a compute worker thread service, a virtual network (VN) API service, a block storage API service, a function-as-a-service service, an events service, an object storage management service (e.g., implementing a storage platform such as Ceph Storage or the like), a compute DP service (e.g., an example of hypervisor <NUM> of <FIG>), a VN DP service, a block storage management service, a function-as-a-service API service, a function-as-a-service load balancing (LB) service, a function-as-a-service process thread service, a distributed data store management service (e.g., etcd3), a dynamic host configuration protocol service, a domain name system service, a network time protocol (NTP) service, to name a few. Some example functionality provided by these services is discussed below.

By way of example, compute DP service may be configured (e.g., preconfigured and provisioned onto the edge device <NUM>) to isolate the VM(s) <NUM> on the same hypervisor host. The compute DP service can utilize any suitable container engine (e.g., Docker container, MicroContainer, or the like) to isolate the VM(s) <NUM> on the same hypervisor host from each other. The compute DP service may utilize any suitable hypervisor (e.g., Quick EMUlator (QEMU), Kernel-based Virtual Machine (KVM), etc.) to provide virtual hardware emulation for VM(s) <NUM>. In some embodiments, VNIC(s) <NUM> are attached to subnets of any suitable number of virtual networks (e.g., private virtual network(s) (PVN(s))) <NUM> and are assigned private Internet Protocol (IP) addresses. One VM may have multiple VNICs from different VCNs and different subnets. The maximum number of VNICs can be limited by predefined thresholds (e.g., configuration data referred to as "VM shape" that defines VNICs per VM count, VNIC shape, etc.). In some embodiments, the predefined thresholds are applied to each of the VM(s) <NUM>. The subnets utilized by the VNIC(s) <NUM> may be isolated by VLANs. In some embodiments, some or all of the VNIC(s) <NUM> may be assigned public and/or private IP addresses. A public IP address is an address in the network <NUM>, while a private IP address refers to an IP address of the PVN(s) <NUM>.

In some embodiments, the edge device <NUM> implements various networking functionality via a number of services such as a network address translation (NAT) service, a dynamic host configuration protocol (DHCP) service, a domain name system (DNS) service, a network time protocol (NTP) service, a metadata service, and a public API service. The metadata service may provide initialization data and other metadata to all VM(s) <NUM>. In some embodiments, DHCP service assigns private IP addresses to each of the VNIC(s) <NUM>, each of the VM(s) <NUM> having one or more VNICS. DNS service may provide domain name resolution to VM(s) <NUM> on the edge device <NUM>. NTP may provide time synchronization to VM(s) <NUM>. In some embodiments, a public IP service executing as part of service(s) <NUM> may enable a VM to access a public API without assigning the VM a public IP and without configuring a service gateway.

In some embodiments, at least one of the VM(s) <NUM> may implement block (or object) storage. In some embodiments, the hypervisor associated with a virtual machine may include a library that enables the hypervisor to use a distributed data storage platform (e.g., Ceph). The library may utilize a protocol associated with that storage platform (e.g., RADOS Block Device (RBD) to facilitate storage of block-based data. The distributed data storage platform may be implemented over multiple virtual machines. In some embodiments, the distributed data storage platform supports making snapshots and copying block volumes. VM images and VM block volumes can be Ceph block devices. In some embodiments, the VM(s) implementing the distributed data storage platform will use system-reserved resources (e.g., eight CPU cores, or any subset of the total number of CPUs available on the edge device <NUM>). For example in order to provision a boot volume, a block device image may be copied to a boot volume of the block device. The distributed data storage platform may use block devices that include multiple nodes for redundancy. If some node fails then the block device can continue to operate. In some embodiments, the distributed data storage platform (e.g., Ceph or the like), automatically recovers the block device data in case of a few node failures. Block storage may be utilized to store images for any suitable deployable resource. By way of example, an image may be utilized for launching VMs. In some embodiments, the image may correspond to a particular VM shape (e.g., a compute heavy VM, a GPU optimized VM, a storage VM, and the like).

Compute API service may support the following operations: <NUM>) VM launch and terminate, <NUM>) VM stop, start, reboot, <NUM>) List VMs and/or get information on a specific VM, <NUM>) obtain VM console history API, <NUM>) obtain a VM snapshot, <NUM>) attach/detach block volumes, and the like. In some embodiments, Compute API service can be used to call other services (e.g., compute DP service, identity DP service for authentication and authorization, etc.).

Some of the functionality of other services will be discussed in connection with <FIG>. In general, although each service may not be discussed in detail herein, the general functionality provided by the service(s) <NUM> may include the functionality of cloud services provided by a remote cloud service provider. In some embodiments, the edge device <NUM> may be associated with a predefined region and/or realm such that some of the service(s) <NUM> may operate as if they were operating in a cloud computing environment, despite the fact they are operating on one or more local device(s) (one or more edge devices) as a single instance or as part of a distributed service that may have no or intermittent public network access to a cloud computing environment associated with the customer. A "region" refers to a geographic location at which a service center resides. A "realm" refers to a logical collection of regions. Realms may be isolated from each other and do not share data.

In some embodiments, the edge device <NUM> may provide any suitable number of virtual networks (e.g., PVN(s) <NUM>) using compute, memory, and networking resources (e.g., virtual network interface card(s) (VNIC(s) <NUM>)). A virtual network is a logical network that runs on top of a physical substrate network. Using the service(s) <NUM>, one or more customer resources or workloads, such as virtual machines (e.g., virtual machine(s) (VM(s)) <NUM>, executing a compute instance) can be deployed on these private virtual networks. Any suitable combination of VM(s) <NUM> can execute functionality (e.g., a compute instance, storage, etc.) which is individually accessible through a virtual NIC (e.g., one of the virtual NIC(s) <NUM>). Each VM that is part of a PVN is associated with a VNIC that enables the VM (e.g., a compute instance) to become a member of a subnet of the PVN. The VNIC associated with a VM facilitates the communication of packets or frames to and from the VM. A VNIC can be associated with a VM when the VM is created. PVN(s) <NUM> can take on many forms, including peer-to-peer networks, IP networks, and others. In some embodiments, substrate network traffic of the service(s) <NUM> may be encrypted and/or isolated (e.g., by virtue of different PVNs or subnets) from network traffic of one or more the VM(s) <NUM> executing on the edge device <NUM>.

The edge device <NUM> thus provides infrastructure and a set of complementary services that enable customers to build and run a wide range of applications (e.g., compute instances), services, and/or storage in a highly available, physically local, and virtual hosted environment. The customer does not manage or control the underlying physical resources provided by the edge device <NUM> but has control over expanding or reducing virtual machines (e.g., compute instances, virtual NICs, block or object storage, etc.), deploying applications to those virtual machines, and the like. All workloads on the edge device <NUM> may be split into different CPU sets (e.g., VM and non-VM). One set (e.g., non-VM such as workloads performed by the service(s) <NUM>) may utilize a subset of CPU cores (e.g., <NUM>) of the edge device <NUM>, while the other set (e.g., VM workloads performed by the VM(s).

The edge device <NUM> may be communicatively connected to a user device (e.g., the computing device <NUM> of <FIG>) via one or more network interfaces (e.g., NIC2 and/or NIC <NUM>) and network <NUM> to interact and/or manage the VM(s) <NUM>. In certain embodiments, a lightweight console can be provided at the user device via a web-based user interface that can be used to access and manage the edge device <NUM>. In some implementations, the console is a web-based application (e.g., one of the service(s) <NUM>) provided by the edge device <NUM>.

<FIG> depicts a single edge device. However, it should be appreciated that more than one edge device may be utilized as a distributed computing cluster.

<FIG> is a block diagram depicting a distributed computing cluster <NUM> that includes one or more edge computing devices (e.g., edge device <NUM> and <NUM>, each an example of the edge device <NUM> of <FIG>), according to at least one embodiment.

Each edge device of the distributed computing cluster <NUM> may be connected via substrate network <NUM> (an example of the substrate network <NUM> of <FIG>. In some embodiments, the edge devices of the distributed computing cluster <NUM> (sometimes referred to as "edge computing nodes" or "edge nodes") may be connected by the substrate network <NUM> using one or more switches (e.g., switch <NUM> and/or <NUM>). In some embodiments, NIC1 and NIC5 may include a particular connector (e.g., RJ45 connector) while NIC3 and NIC8 may include the same or a different connector (e.g., a QSFP28 <NUM> GbE connector). In some embodiments, only one edge device of the distributed computing cluster <NUM> is connected to a customer network such as network(s) <NUM> (an example of the network <NUM> of <FIG>). Thus, not only may traffic between services of an edge device be encrypted and isolated from other traffic of a given edge device, but traffic between distributed services operating across multiple edge devices may also be encrypted and isolated from other traffic of the computing cluster. In some embodiments, each edge device is preconfigured as a particular node in the distributed computing cluster <NUM>. In other embodiments, the user can configure the number and topology of the edge devices of the distributed computing cluster <NUM>.

<FIG> is a block diagram depicting a flow <NUM> for executing a workflow by one or more components of a cloud infrastructure edge computing device, according to at least one embodiment. Components that execute the flow <NUM> may include API service <NUM>, database (DB) <NUM>, service <NUM>, hypervisor service <NUM>, PVN CP service, Block storage CP service <NUM>, although more or fewer services may be included. In some embodiments, each of the services of <FIG> are an example of a service of the service(s) <NUM> of <FIG>. In some embodiments, at least some of the functionality discussed in connection with the services of <FIG> may be combined in any suitable combination and provided as a single service or instances of the same service. By way of example, in some embodiments, the functionality of services <NUM>-<NUM> may be provided by a single service (e.g., compute CP service discussed above in connection with <FIG>). In some embodiments, the functionality provided by the services <NUM>-<NUM> may be provided by a single edge device (e.g., edge device <NUM> of <FIG>) or by two or more edge devices (e.g., by edge device <NUM> and edge device <NUM> of <FIG>).

In some embodiments, the API service <NUM> may be configured to accept work requests that include intended state data that describes an intended state of a set of data plane resources (e.g., VM(s) <NUM> of <FIG>). As a non-limiting example, user <NUM> may utilize a user device (e.g., the user device <NUM> of <FIG>) to access a user interface with which he can make various selections indicating a desire to launch a VM. The user input may be received by the API service <NUM> (an example of the compute CP service of <FIG>) which may generate a work request (WR) (e.g., WR <NUM>) and utilize a predefined Launch VM API to store the work request in a distributed database (e.g., DB <NUM>). In some embodiments, the DB <NUM> may be a computing cluster, which is configured to use etcd3 as an immediately consistent, highly-available, transactional, distributed database. Generally, a work request indicates a desire and information needed to create and/or modify data plane resources such as VM(s) <NUM>. In some embodiments, the work request includes state information indicating a desired state for the data plane resource. In some embodiments, the DB <NUM> may be accessible to all services operating on any edge device (and by services operating on any suitable edge device of an edge device cluster such as distributed computing cluster <NUM>).

Service <NUM> (e.g., an example of the compute CP service of <FIG>) may be configured to execute one or more worker processes (e.g., one or more computing threads, such as computing thread <NUM>). Some of these worker processes may be configured by the service <NUM> at any suitable time to execute a continuous and/or ongoing predefined workflow. By way of example, the service <NUM> may configure one or more worker threads (e.g., including computing thread <NUM>) to monitor the DB <NUM> for new work requests (e.g., WR <NUM>). The computing thread may be configured to determine if a work request WR <NUM> is already being attended to. In some embodiments, this entails checking a predefined storage bucket within DB <NUM> for a unique identifier associated with WR <NUM>. If the unique ID included within WR <NUM> does not appear in the bucket (or the WR is otherwise indicated as having not been picked up for processing), the computing thread <NUM> (e.g., a nanny thread) may initialize a workflow thread (e.g., another instance of a computing thread <NUM>) which may then be configured by the computing thread <NUM> to execute a workflow corresponding to launching a VM corresponding to the WR <NUM>.

The initialized workflow thread may be communicatively coupled (e.g., via the substrate network <NUM> of <FIG>) to a workflow service (not depicted). The workflow service may be configured to identify, from one or more predefined workflows, a predefined workflow that corresponds to launching a VM, and therefore, to the WR <NUM>. These predefined workflows identify one or more steps/operations to be taken, and a sequence to those steps, in order to achieve a predefined goal (e.g., launching a virtual machine, stopping/starting a virtual machine, terminating a virtual machine, creating a block volume, removing a block volume, etc.). The workflow thread may launch the VM workflow and oversee its execution by various other entities. In some embodiments, the workflow thread may pass any suitable portion of the intended state data of the DP resource to any suitable combination of services.

As a non-limiting example, as part of the workflow for launching a virtual machine (e.g., a VM to be hosted by hypervisor service <NUM>), one or more APIs can be called for creating and attaching the VNIC. Similarly, a number of APIs may be provided for creating and/or attaching a block storage volume API. In some embodiments, the workflow thread may perform any suitable call to one or more APIs to invoke the functionality of PVN CP Service <NUM>, which in turn may be configured to create and attach a VNIC. The workflow thread may then call block storage CP service <NUM> which may then execute any suitable operations to create and attach a block storage volume. The worker thread overseeing the workflow may ensure a designated order (e.g., create the VNIC first before creating the block volume). This worker thread may be configured to catch any errors and/or exceptions from one or more services it has invoked. If no exceptions/errors are encountered, the worker thread overseeing the workflow can provide any suitable data to the hypervisor service <NUM> (via the substrate network), which in turn, execute functionality for creating the VM requested. The hypervisor service <NUM> may provide actual state data for the newly launched VM. In some embodiments, the worker thread overseeing the workflow can store the actual state data in the DB <NUM> for later reference (e.g., when a monitor may determine whether the actual state data matches the requested state data indicating no changes needed or when the actual state data fails to match the requested state data, indicating a change of the data plane resources is needed).

In some embodiments, the workflow thread may be communicatively coupled to a cluster manager (not depicted). The cluster manager may be configured to manage any suitable number of computing clusters. In some embodiments, the cluster manager may be configured to manage any suitable type of computing cluster (e.g., a Kubernetes cluster, a set of computing nodes used to execute containerized applications, etc.). The workflow thread may be configured to execute any suitable operations to cause the cluster manager to execute any suitable orchestration operation on the DP resource(s) (e.g., a VM) in accordance with the instructions identified to bring the DP resource(s) in line with the intended state data. In some embodiments, a monitoring entity (e.g., the workflow thread, a thread launched by the workflow thread) may be communicatively coupled to DP resource(s) <NUM> and configured to monitor the health of DP resource(s). In some embodiments, the monitoring entity may be configured to store any suitable health data in the DB <NUM>.

The specific operations and services discussed in connection with <FIG> is illustrative in nature and is not intended to limit the scope of this disclosure. The particular operations performed and services utilized may vary depending on the particular workflow associated with the requested operations.

<FIG> is a block diagram depicting a flow <NUM> for generating a manifest from a user request, according to at least one embodiment. <FIG> depicts a service provider computer (e.g., service provider computer <NUM>). Service provider computer <NUM> can be operated by or on behalf of a cloud-computing provider. In some embodiments, the service provider computers of <FIG> implement a cloud-computing service for generating a manifest from which one or more edge devices can be configured. The service provider computers of <FIG> may be communicatively connected to or operate as part of a cloud-computing environment operated by the cloud-computing provider. The user device <NUM> may be any suitable electronic device (e.g., a laptop, desktop, smartphone, or the like) and communicatively connected to the service provider computer <NUM> via a network (e.g., a public or private network). Service provider computer <NUM> may be configured to host one or more interfaces from which user input may be provided. These user interfaces may relate to configured one or more edge devices.

The flow <NUM> may begin at <NUM>, where the service provider computer <NUM> exposes one or more user interfaces from which user input may be obtained. In some embodiments, these user interfaces enable a user to select various services and/or data plane resources to be configured at one or more edge devices (of which edge device <NUM> is an example). By way of example, these interfaces may be used to define a configuration (e.g., a particular set of services, a particular number and/or type of virtual machines, or any suitable attribute of the edge device <NUM>). In some embodiments, the user may define a cluster of edge devices and their corresponding configurations. Thus, via these interfaces, the user can indicate the edge device <NUM> is to be compute intensive (e.g., where a majority of virtual machines executing at the edge device <NUM> are providing computing resources), storage intensive (e.g., where a majority of virtual machines executing at the edge device <NUM> are providing storage resources), GPU intensive (e.g., where a majority of virtual machines executing at the edge device <NUM> are providing GPU resources), or the like (e.g., based at least in part on a number of virtual machines requested and the specific configuration of these virtual machines as selected by the user). The user interfaces may be in any suitable format that allows the user to select and/or define these attributes of one or more edge devices (e.g., the edge device <NUM>).

At <NUM>, the user device <NUM> may submit the user input in a user request that is received by the service provider computer <NUM>. The service provider computer <NUM> may be hosting a build service within the cloud-computing environment.

At <NUM>, the service provider computer <NUM> may generate a manifest <NUM> (e.g., a record, a file, etc.) corresponding to the user request. The manifest <NUM>, once complete, may be utilized to configure the edge device according to the user request. In some embodiments, the service provider computer <NUM> may generate manifest <NUM> based at least in part on a predefined template. In some embodiments, manifest <NUM> may be in any suitable format (e.g., JSON, XML, etc.). Once generated, the service provider computer <NUM> may begin to modify the manifest <NUM> to correspond to the user request. By way of example, the manifest <NUM> may be modified to include configuration information for one or more edge devices.

<FIG> is a block diagram depicting an example manifest <NUM> (an example of the manifest <NUM> of <FIG>), in accordance with at least one embodiment. The manifest <NUM> include sections <NUM> and <NUM>. Section <NUM> corresponds to one edge device while section <NUM> corresponds to another edge device. Manifest <NUM> may define the configuration of multiple edge devices to be operated as a cluster. In some embodiments, manifest <NUM> may define a cluster identifier at <NUM>. Any suitable number of nodes may be provided in section <NUM>. In some embodiments, a node may be assigned a name as depicted at <NUM>. The manifest <NUM> may indicate a set of device attributes for a given node (e.g., a particular edge device) at <NUM>.

A manifest may include any suitable information pertaining to one or more network interface cards. A network interface card may be defined as having a media access control (MAC) address or another suitable identifier such as a name. In some embodiments the manifest <NUM> may identify a driver for a network interface card within section <NUM>. Section <NUM> may include any suitable number of NIC definitions.

A manifest may identify any suitable number of services. Manifest <NUM> depicts at least one service. Within the manifest, various service level attributes may be identified. By way of example, section <NUM> may include a name for the service, a location at which the image for the service can be found, a default network name within which the service will operate, an indicator indicating whether the service will start on boot, and an IP address for the service. The manifest <NUM> may include any suitable number of services within section <NUM>.

Although the manifest <NUM> is depicted as including a certain attributes of a cluster, a node, or a device, it should be appreciated that a manifest may identify any suitable attribute of a cluster, node, or a device. Thus, the example attributes depicted in <FIG> are not intended to be considered an exhaustive list of the possible attributes that may be included in any given manifest.

Returning to <FIG>, at <NUM>, the service provider computer <NUM> may generate a list of services from the user input and execute any suitable operations for collecting artifacts (e.g., Container images, OStree commit, etc.) corresponding to that list of services. In some embodiments, the service provider computer <NUM> may collect these artifacts from one or more storage locations of the cloud-computing environment to which service provider computer <NUM> belongs. In some embodiments, some of these artifacts may include containers of each of the set of services requested for a given edge device. The service provider computer <NUM> may be configured to collect any suitable number of artifacts corresponding to a number of edge devices defined in the user request.

At <NUM>, the manifest <NUM> may be modified to indicate configuration attributes/details for a particular service to be operated at the edge device. By way of example, each artifact collected at <NUM> may include an executable script that, when executed modifies a manifest file to include entries corresponding to the service to which the artifact relates. The service provider computer <NUM> may be configured to execute each script of each artifact. Each script may be configured to modify the manifest file to include configuration information corresponding to a respective service. Each script may modify the manifest to include any suitable entity definition, where the entity definition defines attributes of a device or a service.

At <NUM>, the service provider computer <NUM> may execute a predefined rule set for assigning one or more network addresses to any suitable number of devices/entities/services identified within the manifest <NUM>. By way of example, an IP address may be assigned to each node of the cluster (e.g., each edge device that will operate as a node in a cluster of edge devices).

At <NUM>, the service provider computer <NUM> may generate an Edge Device (ED) Image based at least in part on the artifacts collected at <NUM>. In some embodiments, an ED Image may be an uber-tarball that contains the entirety of the Container and OStree on-box repositories for a given edge device.

At <NUM>, the service provider computer <NUM> may be configured to collect any suitable predefined configuration files, credentials (e.g., an API key, a data volume password, a Macsec key or other suitable encryption key, etc.) agents (e.g., a netboot agent), or the like.

At <NUM>, the service provider computer <NUM> may provision the edge device <NUM> by providing the ED Image, manifest, configuration files, credentials, and agents to edge device <NUM>. It should be appreciated that, in some embodiments, another service provider computer other than the one that created the manifest (e.g., a service provider computer located at a provisioning center) could execute the provisioning operations.

At <NUM>, the edge device <NUM> may perform any suitable operations for provisioning the edge device <NUM> in accordance with the manifest <NUM>. By way of example, a netboot agent executing on the edge device <NUM> may perform the following operations: PXE boot, partition, setup dmcrypt, and format the file system. ask a service provider computer for an artifact URL, fetch artifacts using the URL, commit the root file system to OStree repository, load containers into a container repository, deploy OStree commit, fetch remote keys and install local keys, install Trenchboot and seal OS partition LUKS key (e.g., in a trusted platform module such as a chip, a hardware security module, an integrated circuit platform, or other hardware, firmware, and/or software for providing secure initialization of the edge device and security management of stored secrets, including encryption key(s)) using a customer password provided as a credential.

After the edge device(s) (of which edge device <NUM> is an example) are configured, the cloud-computing provider may ship or otherwise deliver the edge device(s) to the customer. The edge devices may be configured in accordance with the user input provided at <NUM>.

<FIG> is a block diagram depicting another flow <NUM> for generating a manifest <NUM> from a user request, according to at least one embodiment. <FIG> depicts a service provider computer <NUM> (e.g., an example of service provider computer <NUM> of <FIG>). Service provider computer <NUM> can be operated by or on behalf of a cloud-computing provider. In some embodiments, the service provider computers of <FIG> implements a cloud-computing service for generating a manifest (e.g., manifest <NUM>) from which one or more edge devices can be configured (edge devices <NUM> and <NUM>, each an example of the edge device <NUM> of <FIG>). The service provider computer of <FIG> may be communicatively connected to or operate as part of a cloud-computing environment operated by the cloud-computing provider. The user
device <NUM> may be any suitable electronic device (e.g., a laptop, desktop, smartphone, or the like) and communicatively connected to the service provider computer <NUM> via a network (e.g., a public or private network, not depicted). Service provider computer <NUM> may be configured to host one or more interfaces from which user input may be provided. These user interfaces may relate to configured one or more edge devices. In some embodiments, the user may desire to operate a distributed computing cluster <NUM> using, at least, the edge devices <NUM> and <NUM>. Any suitable number of edge devices may be utilized in distributed computing cluster <NUM>.

The flow <NUM> may begin at <NUM>, where the service provider computer <NUM> exposes one or more user interfaces from which user input may be obtained (e.g., from the user device <NUM>). In some embodiments, these user interfaces enable a user to select various services and/or data plane resources to be configured at edge devices <NUM> and <NUM>. By way of example, these interfaces may be used to define a configuration (e.g., a particular set of services, a particular number and/or type of virtual machines, or any suitable attribute of the edge devices <NUM> and <NUM>). In some embodiments, the user may desire that edge devices <NUM> and <NUM> have the same configuration/set of services. In other embodiments, the user may specify different configurations and/or sets of services for a respective edge device (e.g., one may be compute intensive and one storage intensive, for example). The user interfaces may be in any suitable format that allows the user to select and/or define these attributes of one or more edge devices (e.g., the edge device <NUM>).

At <NUM>, the user device <NUM> may submit the user input in a user request that is received by the service provider computer <NUM>. The service provider computer <NUM> may be hosting a build service within the cloud-computing environment. The build service may be configured to receive the user request.

At <NUM>, the service provider computer <NUM> may generate a manifest <NUM> (e.g., a record, a file, etc.) corresponding to the user request. The manifest <NUM>, once complete, may be utilized to configure the edge devices <NUM> and <NUM> according to the user request. In some embodiments, the service provider computer <NUM> may generate manifest <NUM> based at least in part on a predefined template. As discussed above, manifest <NUM> may be in any suitable format (e.g., JSON, XML, etc.). Once generated, the service provider computer <NUM> may begin to modify the manifest <NUM> to correspond to the user request. By way of example, the manifest <NUM> may be modified to include configuration information for one or more edge devices.

At <NUM>, any suitable combination of the operations discussed with respect to steps <NUM>-<NUM> of <FIG> may be performed to modify the manifest <NUM> according to the user request and to generate an ED Image based at least in part on obtaining artifacts corresponding to the services specified by the user request, credentials, configuration files, agents, and the like.

At <NUM>, the service provider computer <NUM> may provision the edge devices <NUM> and <NUM> by providing the ED Image, manifest, configuration files, credentials, and agents to edge devices. It should be appreciated that, in some embodiments, another service provider computer other than the one that created the manifest (e.g., a service provider computer located at a provisioning center) could execute the provisioning operations for the edge devices of the distributed computing cluster <NUM> (in this case, edge devices <NUM> and <NUM>).

At <NUM>, each edge device may perform any suitable operations for provisioning one or more data plane resources in accordance with the manifest <NUM>. By way of example, a netboot agent executing on the edge device <NUM> (and/or edge device1008) may perform the following operations: PXE boot, partition, setup dmcrypt, and format the file system, request an artifact URL (e.g., from a service provider computer)for an artifact URL, fetch artifacts from data store using the URL, commit the root file system to OStree repository, load containers into a container repository, deploy OStree commit, fetch remote keys (e.g., a customer password for accessing object store disks) and install local keys, install Trenchboot and seal OS partition LUKS key into a boot partition.

After the edge device(s) <NUM> and <NUM> are configured, the cloud-computing provider may ship or otherwise deliver the edge device(s) to the customer. The edge devices may be configured to operate as distributed computing cluster <NUM>, in accordance with the user input provided at <NUM>.

Subsequently, edge device <NUM> may cease operating for some reason (e.g., a system failure has occurred at <NUM>). At <NUM>, the user device <NUM> (or any suitable user device) can be used to request a replacement device (e.g., edge device <NUM>, an example of the edge devices <NUM> of <FIG> and edge devices <NUM> and <NUM>).

At <NUM>, the service provider computer <NUM> may update the manifest <NUM> to include configuration information needed to configure edge device <NUM> according to the user request. In some embodiments, the user request may specify that the edge device <NUM> is to be configured as an exact replacement for edge device <NUM>, with the same configuration (e.g., set of services, data plane resources, etc.) or, in some embodiments, the user request can indicate a different configuration is to be used.

At <NUM>, any suitable combination of the operations discussed with respect to steps <NUM>-<NUM> of <FIG> and at <NUM> may be performed to modify the manifest <NUM> according to the user request and to generate an ED Image based at least in part on obtaining artifacts corresponding to the services specified by the user request, credentials, configuration files, agents, and the like.

At <NUM>, the service provider computer <NUM> may provision the edge device <NUM> providing the ED Image, manifest, configuration files, credentials, and agents to edge devices. It should be appreciated that, in some embodiments, another service provider computer other than the one that created the manifest (e.g., a service provider computer located at a provisioning center) could execute the provisioning operations for edge device <NUM>. Once configured, edge device <NUM> may operate as part of distributed computing cluster <NUM>.

Although not depicted, at any suitable time, the edge device <NUM> (or any edge device of the distributed computing cluster <NUM>) may be physically shipped back to the service provider and reconfigured with the same and/or different configuration than previously provided using the same or different manifest (e.g., manifest <NUM>).

<FIG> is a block diagram illustrating an architecture <NUM> and flow for provisioning one or more data plane resources at an edge computing device (an example of the edge devices of <FIG>, <FIG>, and <FIG>), according to at least one embodiment. Architecture <NUM> may include control plane <NUM> and data plane <NUM>.

In some embodiments, the control plane <NUM> may be responsible for accepting work requests that include intended state data that describes an intended state of a set of one or more data plane resources. For example, a work request may be received by control plane application programming interface (API) <NUM>. In some embodiments, the work request may be in the form of a manifest (e.g., manifest <NUM>, and example of a manifest generated by the flow <NUM> of <FIG> or flow <NUM> of <FIG>). In some embodiments, control plane API <NUM> may be an example of one of the service(s) <NUM> of <FIG>. Control plane API <NUM> may be configured to receive any suitable number of work requests (e.g., manifest <NUM>) corresponding to one or more data resources (e.g., a virtual machine, a cluster of virtual machines, etc.) from a user device.

In some embodiments, the manifest <NUM> may include an identifier that may uniquely identify it as a work request such that the manifest <NUM> can be distinguishable from other work requests. The request identifier can be an alphanumeric string of characters of any suitable length that is unique to that work request and with which that work request can be identified. Intended state data may include any suitable number of parameters. These parameters may define attributes of the data plane resource requested including, but not limited to, an identifier for the resource, an availability domain, a shape corresponding to the node, a number of processing units of the resource, an amount of random access memory (RAM) of the resource, an amount of disk memory, a role (e.g., a data node, a master node, etc.), a status (e.g., healthy), or the like. In some embodiments, the control plane API <NUM> may be configured to store all received work requests (e.g., the manifest <NUM>) in a data store (e.g., control plane (CP) data store <NUM>, a distributed data store implemented by a cluster of edge devices in which the edge device executing the components of <FIG> operates).

In some embodiments, CP data store <NUM> may be configured to store work requests and/or an intended state data corresponding to an intended state of the data plane <NUM>. In some embodiments, the CP data store <NUM> may be configured to store a mapping of one or more data plane identifiers (DPIDs) of DP resource(s) <NUM> with intended state data and/or current state data. Intended state data refers to data that specifies one or more aspects of a DP resource which has been requested and to which the DP resource is intended to be modified. Current state data (sometimes referred to as "actual state data") corresponds to one or more parameters that identify one or more current aspects of a DP resource as currently operating.

The control plane <NUM> may include a control plane (CP) monitoring component <NUM>. The CP monitoring component <NUM> may be configured to periodically (e.g., according to a predetermined frequency, schedule, etc.) determine whether the intended state data received by the control plane API <NUM> and stored in the CP data store <NUM> (e.g., from a previously received work request) matches current state data stored for a corresponding DP resource (if that DP resource currently exists). CP monitoring component <NUM> may be communicatively coupled to non-compute service(s) <NUM> (e.g., via substrate network <NUM> of <FIG>) which may include any suitable number of cloud computing services configured to manage billing, identity, authorization, and the like. In some embodiments, CP monitoring component <NUM>, in-memory workflow manager <NUM>, and CP worker(s) <NUM> are provided by a common service (e.g., service <NUM> of <FIG>). Service <NUM> may be one of the service(s) <NUM> of <FIG>. Non-compute service(s) <NUM> may be the remaining set of services of service(s) <NUM>, excluding control plane API <NUM> and a service (e.g., service <NUM>) that implements CP monitoring component <NUM>, in-memory workflow manager <NUM>, and CP worker(s) <NUM>. In some embodiments, CP monitoring component <NUM> may be communicatively coupled to in-memory workflow manager <NUM> and may be configured to invoke the functionality provided by the in-memory workflow manager <NUM>. By way of example, if the CP monitoring component <NUM> determines that the current state data of a DP resource is not in line with (e.g., does not match) the intended state data stored in CP data store <NUM>, CP monitoring component <NUM> may invoke the functionality of in-memory workflow manager <NUM> to rectify the discrepancy.

In some embodiments, in-memory workflow manager <NUM> may be configured to identify one or more predefined workflows which individually identify operations to perform to configure DP resource(s) <NUM> in accordance with corresponding intended state data. In some embodiments, the in-memory workflow manager <NUM> may be configured to initiate one or more workers (e.g., computing threads) of control plane (CP) worker(s) <NUM> and forward the workflow instructions and/or intended state data to a given CP worker to perform the operations related to configuring the corresponding DP resource(s) in accordance with the received intended state data. In some embodiments, the CP worker(s) <NUM> may provide service-specific orchestration operations. The CP worker(s) <NUM> may be communicatively coupled to any suitable number of services (e.g., non-compute service(s) <NUM>) including any suitable combination of a compute service, a storage service, etc. In some embodiments, the CP worker(s) <NUM> may be configured to provide instructions to data plane (DP) manager <NUM> for configuring one or more DP resources. DP manager <NUM> (e.g., an example of the hypervisor service <NUM> of <FIG>) may be configured to create, modify, and/or remove or delete any suitable DP resource.

In some embodiments, DP manager <NUM> may be configured to manage any suitable number of computing components (e.g., the DP resource(s) <NUM> which may be, collectively, an example of a computing cluster). In some embodiments, the DP manager <NUM> may be configured to manage any suitable type of computing cluster (e.g., a Kubernetes cluster, a set of computing nodes used to execute containerized applications, etc.). The CP worker(s) <NUM> may be configured to execute any suitable operations to cause the DP manager <NUM> to execute any suitable orchestration operation on the DP resource(s) <NUM> in accordance with the instructions identified by in-memory workflow manager <NUM> to configure the DP resource(s) <NUM> in accordance with the intended state data. In some embodiments, CP monitoring component <NUM> may be communicatively coupled to DP resource(s) <NUM> and configured to monitor the health of DP resource(s) <NUM>. In some embodiments, CP monitoring component <NUM> may be configured to transmit (e.g., to a user device using any suitable form of electronic communication) any suitable health data indicating the health of one or more of the DP resource(s) <NUM>. By way of example, CP monitoring component <NUM> may transmit any suitable health data via Control plane API <NUM> to a user device.

In some embodiments, the CP monitoring component <NUM> may be configured to monitor and assess current state data of the DP resource(s) <NUM>. In some embodiments, the CP monitoring component <NUM> may receive current state data store/update current state data of the DP resource(s) <NUM> within CP data store <NUM>. Current state data may be provided by DP manager <NUM> to a corresponding CP worker, which in turn may provide the current state data to the in-memory workflow manager <NUM>, which may then provide the current state data to the CP monitoring component <NUM>. In some embodiments, CP worker(s) <NUM> and/or in-memory workflow manager <NUM> may update CP data store <NUM> directly with the current state data of any suitable DP resource such that the current state data of a given DP resource may be retrieved by the CP monitoring component <NUM> at any suitable time.

Although CP monitoring component <NUM>, in-memory workflow manager <NUM>, and CP worker(s) <NUM> are depicted as separate components of control plane <NUM>, in some embodiments, any suitable combination of CP monitoring component <NUM>, in-memory workflow manager <NUM>, and/or CP worker(s) <NUM> may be provided by one service (e.g., service <NUM> of <FIG>, an example of one of the services of service(s) <NUM> of <FIG>).

<FIG> is a block diagram illustrating an example method <NUM> for providing in-memory workflow management at an edge computing device, in accordance with at least one embodiment. The method <NUM> may be performed by any suitable number of service provider computers (e.g., the service provider computers of <FIG>). In some embodiments, the method <NUM> may include more or fewer steps than the number depicted in <FIG>. It should be appreciated that the steps of method <NUM> may be performed in any suitable order.

The method <NUM> may begin at <NUM>, where a first user request specifying a first set of services to be executed at a first cloud-computing edge device may be received by a computing device operated by a cloud computing provider. An example of this computing device may include the service provider computer <NUM> of <FIG>. In some embodiments, a cloud-computing edge device may be a device configured to selectively execute within an isolated computing environment having no access to a public network while executing within the isolated computing environment. For example, the cloud-computing edge device may be an example of the edge devices discussed above with respect to <FIG>, <FIG>, and <FIG>.

At <NUM>, a first manifest may be generated based at least in part on the first user request. The first manifest may specify a first configuration for the first cloud-computing edge device. In some embodiments, the first configuration comprises the first set of services in accordance with the first user request. The first manifest may be an example of the manifest <NUM> of <FIG>.

At <NUM>, the first cloud-computing edge device may be provisioned with the first set of services in accordance with the first manifest.

At <NUM>, a second user request specifying a second set of services to be executed at a second cloud-computing edge device may be received by the computing device. In some embodiments, the second set of services may differ from the first set of services;.

At <NUM>, a second manifest may be generated based at least in part on the second user request. In some embodiments, the second manifest specifies a second configuration for the second cloud-computing edge device, the second configuration comprising the second set of services. The second manifest may be another example of the manifest <NUM> of <FIG>.

At <NUM>, the second cloud-computing edge device may be provisioned with the second set of services in accordance with the second manifest. In some embodiments, the second cloud-computing edge device may be provisioned with different services than those provisioned at the first cloud-computing edge device.

Although specific embodiments have been described, various modifications, alterations, alternative constructions, and equivalents are also encompassed within the scope of the disclosure. Embodiments are not restricted to operation within certain specific data processing environments, but are free to operate within a plurality of data processing environments. Additionally, although embodiments have been described using a particular series of transactions and steps, it should be apparent to those skilled in the art that the scope of the present disclosure is not limited to the described series of transactions and steps. Various features and aspects of the above-described embodiments may be used individually or jointly.

Further, while embodiments have been described using a particular combination of hardware and software, it should be recognized that other combinations of hardware and software are also within the scope of the present disclosure. Embodiments may be implemented only in hardware, or only in software, or using combinations thereof. The various processes described herein can be implemented on the same processor or different processors in any combination. Accordingly, where components or modules are described as being configured to perform certain operations, such configuration can be accomplished, e.g., by designing electronic circuits to perform the operation, by programming programmable electronic circuits (such as microprocessors) to perform the operation, or any combination thereof. Processes can communicate using a variety of techniques including but not limited to conventional techniques for inter process communication, and different pairs of processes may use different techniques, or the same pair of processes may use different techniques at different times. Embodiments may be implemented by using a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform any of the methods described in this disclosure.

The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. It will, however, be evident that additions, subtractions, deletions, and other modifications and changes may be made thereunto without departing from the broader spirit and scope as set forth in the claims. Thus, although specific disclosure embodiments have been described, these are not intended to be limiting. Various modifications and equivalents are within the scope of the following claims.

The use of the terms "a" and "an" and "the" and similar referents in the context of describing the disclosed embodiments (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The term "connected" is to be construed as partly or wholly contained within, attached to, or joined together, even if there is something intervening. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein and each separate value is incorporated into the specification as if it were individually recited herein. The use of any and all examples, or exemplary language (e.g., "such as") provided herein, is intended merely to better illuminate embodiments and does not pose a limitation on the scope of the disclosure unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the disclosure.

Disjunctive language such as the phrase "at least one of X, Y, or Z," unless specifically stated otherwise, is intended to be understood within the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present.

Claim 1:
A computer-implemented method, comprising:
receiving (<NUM>), by a computing device operated by a cloud computing provider, a first user request specifying a first set of services to be executed at a first cloud-computing edge device (<NUM>), a cloud-computing edge device being a device configured to selectively execute within an isolated computing environment having no access to a public network while executing within the isolated computing environment;
generating (<NUM>), by the computing device based at least in part on the first user request, a first manifest that specifies a first configuration for the first cloud-computing edge device, the first configuration comprising the first set of services, wherein generating the first manifest comprises executing one or more executable scripts individually associated with an artifact corresponding to a service of the first set of services, wherein executing the one or more executable scripts modifies the first manifest to include one or more entity definitions, and wherein each entity definition corresponds to a device or service, and assigning a network address to one or more entities defined within the manifest;
provisioning (<NUM>), by the computing device, the first cloud-computing edge device with the first set of services in accordance with the first manifest;
receiving (<NUM>), by the computing device, a second user request specifying a second set of services to be executed at a second cloud-computing edge device (<NUM>);
generating (<NUM>), by the computing device based at least in part on the second user request, a second manifest that specifies a second configuration for the second cloud-computing edge device, the second configuration comprising the second set of services; and
provisioning (<NUM>), by the computing device, the second cloud-computing edge device with the second set of services in accordance with the second manifest.