Abstract: Examples described herein relate to a scheduling assistance sub-system for deploying a container in a cluster comprising member nodes. The scheduling assistance sub-system receives a container deployment request to deploy the container and forwards it to a container scheduler after determining the resource requirements of the container. In some examples, at the time of receiving the container deployment request, the member nodes collectively host a plurality of already-deployed containers. Responsive to receiving the container deployment request, the scheduling assistance sub-system determines if the container deployment request is assigned a pending status by the container scheduler. Further, the scheduling assistance sub-system may identify a set of preemptable containers on a single member node based on the resource requirements of the container.

Abstract: In some examples, a system associates, with a plurality of virtual resources deployed in a cloud environment, properties representative of characteristics of the virtual resources, the properties comprising a performance level of a virtual resource. The system receives a request to create a virtual resource in the cloud environment, and, in response to determining that properties of the virtual resource to be created for the request satisfy a criterion with respect to properties of a given virtual resource of the plurality of virtual resources, selects the given virtual resource as a candidate virtual resource for the request.

Abstract: In some examples, a system associates, with a plurality of virtual resources deployed in a cloud environment, properties representative of characteristics of the virtual resources, the properties comprising a performance level of a virtual resource. The system receives a request to create a virtual resource in the cloud environment, and, in response to determining that properties of the virtual resource to be created for the request satisfy a criterion with respect to properties of a given virtual resource of the plurality of virtual resources, selects the given virtual resource as a candidate virtual resource for the request.

Abstract: Examples relate to preventing scheduling or executing a resource on an inconsistent host node in a networked system. Some examples track a taint status of the host node and identify whether the host node is inconsistent based on the taint status of the host node over a predefined period of time. Upon identifying that the host node is inconsistent, a master taint is applied on the inconsistent host node, which prevents scheduling or executing a resource on the identified inconsistent host node.

Abstract: Examples described relate to determining a future operation failure in a cloud system. In an example, a historical utilization of resources for performing an operation in a cloud system may be determined. A current utilization of resources in the cloud system may be determined. Based on the historical utilization of resources for performing the operation in the cloud system and the current utilization of resources in the cloud system, a determination may be made whether a future performance of the operation in the cloud system is likely to be a failure. In response to a determination that the future performance of the operation in the cloud system is likely to be a failure, an alert may be generated.

Abstract: In some examples, a system associates, with a plurality of virtual resources deployed in a cloud environment, properties representative of characteristics of the virtual resources, the properties comprising a performance level of a virtual resource. The system receives a request to create a virtual resource in the cloud environment, and, in response to determining that properties of the virtual resource to be created for the request satisfy a criterion with respect to properties of a given virtual resource of the plurality of virtual resources, selects the given virtual resource as a candidate virtual resource for the request.

Abstract: Examples described herein relate to a method and a system, for example, a workload controller, for accessing purged workloads. An alert indicative of an attempt to access a purged workload of workloads deployed in a workload environment may be received by the workload controller. The purged workload may include one or both of a deactivated workload or an archived workload. The workload controller may detect the attempt to access the purged workload based on port mirrored data traffic. Further, in some examples, the workload controller may activate the purged workload based on the alert.

Abstract: Examples relate to preventing scheduling or executing a resource on an inconsistent host node in a networked system. Some examples track a taint status of the host node and identify whether the host node is inconsistent based on the taint status of the host node over a predefined period of time. Upon identifying that the host node is inconsistent, a master taint is applied on the inconsistent host node, which prevents scheduling or executing a resource on the identified inconsistent host node.

Abstract: Examples relate to comparing sets of tags for determining whether a VM image matches another VM image. Some examples generate a first set of tags corresponding to a first VM image that is to be created, compare a second set of tags corresponding to a second VM image available in an image store, with the first set of tags to determine whether the second VM image matches the first VM image, and send the result of the comparison to an image builder.

Abstract: Examples relate to preventing scheduling or executing a resource on an inconsistent host node in a networked system. Some examples track a taint status of the host node and identify whether the host node is inconsistent based on the taint status of the host node over a predefined period of time. Upon identifying that the host node is inconsistent, a master taint is applied on the inconsistent host node, which prevents scheduling or executing a resource on the identified inconsistent host node.

Abstract: Virtual machine images available across a plurality of cloud networks may be identified. A catalog of the virtual machine images may be generated. The catalog may comprise, for each virtual machine image, a mapping information, comprising: a name of a virtual machine image, a name of a virtual machine instance based on the virtual machine image, a name of a cloud network providing the virtual machine image, a cost of deploying the virtual machine instance on the cloud network, a tag identifying a feature of the virtual machine image, and an identification tag assigned to the virtual machine image. For a given virtual machine instance, the catalog of the virtual machine images may be analyzed to identify a least cost cloud network.

Abstract: Examples described relate to managing a containerized application in a cloud system based on usage. In an example, a determination may be made whether a containerized application in a cloud system has not been used for a pre-defined period of time. In response to the determination, the containerized application may be deleted. The information related to the containerized application in a database may be stored in a database. In response to a future user request to access the containerized application, a new containerized application may be created in the cloud system based on the information related to the containerized application in the database. A new public service endpoint may be associated with the new containerized application in the cloud system. User access to the new containerized application in the cloud system may be allowed via the new public service endpoint.

Abstract: Examples described relate to managing a public service endpoint to a workload in a public cloud system. In an example, a determination may be made whether a public service endpoint to a workload in a public cloud system has not been accessed for a pre-defined period of time. In response to a determination that the public service endpoint to the workload in the public cloud system has not been accessed for the pre-defined period of time, the public service endpoint to the workload may be deleted. In response to a determination that an alias service endpoint associated with the public service endpoint has been accessed, a new public service endpoint may be associated with the workload in the public cloud system. Access to the workload in the public cloud system may be allowed via the new public service endpoint.

Abstract: Examples described relate to determining a future operation failure in a cloud system. In an example, a historical utilization of resources for performing an operation in a cloud system may be determined. A current utilization of resources in the cloud system may be determined. Based on the historical utilization of resources for performing the operation in the cloud system and the current utilization of resources in the cloud system, a determination may be made whether a future performance of the operation in the cloud system is likely to be a failure. In response to a determination that the future performance of the operation in the cloud system is likely to be a failure, an alert may be generated.

Abstract: Examples described relate to identifying a least cost cloud network for deploying a virtual machine instance. In an example, virtual machine images available across a plurality of cloud networks may be identified. A catalog of the virtual machine images may be generated. The catalog may comprise, for each virtual machine image, a mapping information, comprising: a name of a virtual machine image, a name of a virtual machine instance based on the virtual machine image, a name of a cloud network providing the virtual machine image, a cost of deploying the virtual machine instance on the cloud network, a tag identifying a feature of the virtual machine image, and an identification tag assigned to the virtual machine image. For a given virtual machine instance, the catalog of the virtual machine images may be analyzed to identify a least cost cloud network.

Abstract: In some examples, a system associates, with a plurality of virtual resources deployed in a cloud environment, properties representative of characteristics of the virtual resources, the properties comprising a performance level of a virtual resource. The system receives a request to create a virtual resource in the cloud environment, and, in response to determining that properties of the virtual resource to be created for the request satisfy a criterion with respect to properties of a given virtual resource of the plurality of virtual resources, selects the given virtual resource as a candidate virtual resource for the request.

Abstract: Examples disclosed herein relate to creation of a storage area network (SAN) zone based on a service level agreement (SLA). In an example, provisioning of a server in a cloud may be determined. Further, a Service Level Agreement (SLA) for the provisioned server may be determined. The SLA may define desired states of SAN configuration parameters to be met in configuring a SAN zone for the provisioned server. Network components and storage components in the cloud that meet the desired states of SAN configuration parameters defined in the SLA may be identified. A SAN zone for the provisioned server may be created based on the identified network components and storage components.

Abstract: In one example, mapping information corresponding to a container running on a private data center may be generated in a public cloud by a processor-based disaster recovery manager. Further, volume data associated with the container may be synchronized to the public cloud based on the mapping information by the disaster recovery manager. Furthermore, a failure of the container running on the private data center may be determined by the disaster recovery manager. In response to the failure of the container running on the private data center, the container may be deployed in the public cloud using the synchronized volume data and the mapping information by the disaster recovery manager.

Abstract: In one example, mapping information corresponding to a container running on a private data center may be generated in a public cloud by a processor-based disaster recovery manager. Further, volume data associated with the container may be synchronized to the public cloud based on the mapping information by the disaster recovery manager. Furthermore, a failure of the container running on the private data center may be determined by the disaster recovery manager. In response to the failure of the container running on the private data center, the container may be deployed in the public cloud using the synchronized volume data and the mapping information by the disaster recovery manager.

Abstract: In one example in accordance with the present disclosure, a priority is determined for each element in a plurality of elements connected to a network. The plurality of elements may include a source element, a destination element and a first element selected for downtime. A reliability index is determined for each element in the plurality of elements and a plurality of alternate paths between the source element and destination element are determined, each alternate path including a corresponding plurality of elements. For each alternate path in the plurality, a total utilization of the corresponding plurality of elements of the alternate path may be determined for each of a plurality of time slots and a best time slot to be used as a time period for the downtime of the first element may be determined based on the total utilizations.