Techniques are provided for managing resources among clusters of computing devices in a computing system. Resource reassignment message are generated for indicating that servers are reassigned and in response to resource compute loads exceed or fall below certain thresholds. Techniques also include establishing communications with the reassigned servers to assign compute loads without physically relocating the servers from one cluster to another cluster.

Provided is an electronic device for managing computing resources of at least one cloud server that provides a cloud service by using a virtual machine instance including a communicator configured to receive, from a client device, at least one service request for a service provided by the virtual machine instance; and a controller configured to select one of a plurality of modes of the virtual machine instance for management of the computing resources, based on the at least one service request, and control the computing resources allocated to the virtual machine instance according to the selected mode of the virtual machine instance, wherein the virtual machine instance is generated by the at least one cloud server.

Techniques for adjusting a compute capacity of a cloud computing system. In an example, a compute scaling application accesses, from a cloud computing system, a compute capacity indicating a number of allocated compute instances of a cloud computing system and usage metrics indicating pending task requests in a queue of the cloud computing system. The compute scaling application determines, for the cloud computing system, a compute scaling adjustment by applying a machine learning model to the compute capability of the cloud computing system and the usage metrics. The compute scaling adjustment indicates an adjustment to a number of compute instances of the cloud computing system. The compute scaling application provides the compute scaling adjustment to the cloud computing system. The cloud computing system adjusts a number of allocated compute instances.

Techniques for adjusting a compute capacity of a cloud computing system. In an example, a compute scaling application accesses, from a cloud computing system, a compute capacity indicating a number of allocated compute instances of a cloud computing system and usage metrics indicating pending task requests in a queue of the cloud computing system. The compute scaling application determines, for the cloud computing system, a compute scaling adjustment by applying a machine learning model to the compute capability of the cloud computing system and the usage metrics. The compute scaling adjustment indicates an adjustment to a number of compute instances of the cloud computing system. The compute scaling application provides the compute scaling adjustment to the cloud computing system. The cloud computing system adjusts a number of allocated compute instances.

The subject technology selects a particular zone among multiple zones based on a target skew to meet a global balancing of cluster instances. The subject technology deploys a particular type of cluster instance to the particular zone. The subject technology, for each zone from the multiple zones, determines a respective number of cluster instances. The subject technology identifies a second particular type of cluster instance to remove based on a total number of the second particular type of cluster instance in the multiple zones and a second total number of the particular type of cluster instance in the multiple zones. The subject technology removes the second particular type of cluster instance from a second particular zone to meet the global balancing of cluster instances in the multiple zones.

Example methods are provided to deploy an Internet of Things (IoT) solution in a hybrid environment. The methods include deploying a first agent application on a first edge gateway of a first vendor by the first edge gateway. The first agent application is configured to collect a first set of information associated with the first edge gateway. The methods include deploying a second agent application on a second edge gateway of a second vendor by the second edge gateway. The second agent application is configured to collect a second set of information associated with the second edge gateway. In response to a determination of a first virtualized computing environment on the first edge gateway or a second virtualized computing environment on the second edge gateway fulfils a first requirement of a template to deploy the IoT solution, the methods include deploying the IoT solution in the first virtualized computing environment, the second virtualized computing environment, or both.

Techniques for preventing concurrent execution of an infrastructure orchestration service are described. Worker nodes can receive instructions, or tasks, for deploying infrastructure resources and can provide heartbeat notifications to scheduler nodes, also considered a lease. A signing proxy can track the heartbeat notifications sent from the worker nodes to the scheduler node. The signing proxy can receive requests corresponding to a performance of the tasks assigned to the worker nodes. The signing proxy can determine whether the lease between each worker node and the scheduler is valid. If the lease is valid, the signing proxy may make a call to services on behalf of the worker node, and if the lease is not valid, the signing proxy may not make a call to services on behalf of the worker node. Instead, the signing proxy may cut off all outgoing network traffic, blocking access of the worker node to services.

Techniques for preventing concurrent execution of an infrastructure orchestration service are described. Worker nodes can receive instructions, or tasks, for deploying infrastructure resources and can provide heartbeat notifications to scheduler nodes, also considered a lease. A signing proxy can track the heartbeat notifications sent from the worker nodes to the scheduler node. The signing proxy can receive requests corresponding to a performance of the tasks assigned to the worker nodes. The signing proxy can determine whether the lease between each worker node and the scheduler is valid. If the lease is valid, the signing proxy may make a call to services on behalf of the worker node, and if the lease is not valid, the signing proxy may not make a call to services on behalf of the worker node. Instead, the signing proxy may cut off all outgoing network traffic, blocking access of the worker node to services.

Various example implementations are directed to circuits, apparatuses, and methods for providing virtual computing services. According to an example embodiment, an apparatus includes a computing server configured to provide a respective group of virtual servers for each of a plurality of accounts. Each of the accounts has a respective set of domain names and a respective settings file. The apparatus also includes a domain name server (DNS). The DNS is to dynamically map a respective set of domain names for each account to network addresses of the respective group of virtual servers, provided for the account. The DNS performs the mapping according to a mapping function indicated in the respective settings file of the account. The respective settings file of a first account accounts includes a mapping function that is different from a mapping function included in the respective settings file of a second account.

A system and method for generating and representing a consolidated resolution tree of a network are provided. The method includes receiving a target fully qualified domain name (FQDN); creating at least one tentative equivalence class (TEC) containing all the internet root domain name servers (DNS); processing the at least one TEC to determine respective consolidated edges and vertices; retrieving nameservers from domain registration records; determining whether additional TECs are to be generated for the retrieved nameserver(s); processing all new TECs to determine respective consolidated edges and vertices, when it is determined that new TECs are to be generated; and generating a resolution tree for display based on the consolidated edges and vertices.