Abstract: Examples can include (1) identifying, on a network, a source node and a destination node, the source node including at least one source node virtual machine (“VM”) to be replicated as a destination node VM on the destination node, (2) performing a full synchronization by copying disks used by the source node VM in a current operational state to the destination node VM, (3) scheduling start times for multiple update synchronizations of changed data between the source node VM and the destination node VM, the start times being scheduled at different time intervals, wherein a first time interval is greater than a second time interval, and (4) performing, at a switch-over time, a shutdown of the source node VM and transmitting data changes that are pending on the disk to the destination node. Various corresponding systems, methods, and non-transitory computer-readable media are also disclosed.

Abstract: An example method of deploying an application by a telecommunications platform in a multi-cloud computing system includes: receiving, at the telecommunications platform executing in a first software-defined data center (SDDC), an application deployment specification for a first application; receiving, at the telecommunications platform, selection of a virtual infrastructure (VI) template for the first application, the VI template defining a configuration of SDDC resources in the multi-cloud computing system; and deploying the first application based on the application deployment specification of the first application and the VI template.

Abstract: Systems, methods, devices and non-transitory, computer-readable storage mediums are disclosed for simulating nodes of a container orchestration system. An example method includes: deploying a mock node for taking on a role of actual worker nodes, wherein the mock node is provided with a first set of resources providing a first compute capacity and the mock node includes an interface for interacting with an API server of the container orchestration system; configuring the interface to present to the container orchestration system an available compute capacity of a second compute capacity; registering the mock node as an actual worker node of the cluster with the API server based on the interface of the mock node; causing the container orchestration system to deploy a plurality of application pods to the mock node; and obtaining events generated by the interface in the mock node indicating deployment and running statuses of the application pods.

Abstract: A system and method for backing up workloads for multiple tenants of a cloud computing system are disclosed. A method of backing up workloads for multiple tenants of a computing system includes triggering an archival process according to an archival policy set by a tenant, and executing the archival process by reading backup data of the tenant stored in a backup storage device of the computer system and transmitting the backup data to an archival store designated in the archival policy, and then deleting or invalidating the backup data stored in the backup storage device.

Abstract: An orchestrator process can efficiently distribute images of virtual network functions (“VNFs”) in a telco network. The images can be accompanied by metadata that describes VNF requirements, such as computing requirements and functional characteristics. Based on the image metadata and location of a virtual infrastructure manager (“VIM”), the orchestrator can select a storage location and deploy the image to the storage location. The VIM can instantiate a corresponding VNF by retrieving the image. The orchestrator can track the storage location and cause the VIM to delete the image if the image is not used for a threshold period of time.

Abstract: Techniques disclosed herein manage and resolve incidents in hybridity manager applications, without the back-and-forth manual steps of the traditional software support lifecycle. In one embodiment, a virtual network operations center (NOC) with a centralized view of distributed, cross-cloud hybridity manager installations is responsible for tracking incident reports relating to hybridity managers and associated bugs, and the virtual NOC automatically publishes notifications of upgrade builds that fix the tracked bugs to the appropriate hybridity managers. When the same bug is encountered again with another hybridity manager instance, the virtual NOC may also publish an upgrade notification to the other hybridity manager instance, without requiring a support ticket to be filed, etc.

Abstract: An orchestrator process can efficiently distribute images of virtual network functions (“VNFs”) in a telco network. The images can be accompanied by metadata that describes VNF requirements, such as computing requirements and functional characteristics. Based on the image metadata and location of a virtual infrastructure manager (“VIM”), the orchestrator can select a storage location and deploy the image to the storage location. The VIM can instantiate a corresponding VNF by retrieving the image. The orchestrator can track the storage location and cause the VIM to delete the image if the image is not used for a threshold period of time.

Abstract: A system and method for backing up virtual machines are disclosed. To better use the backup resources, an optimal set of virtual machines needing backup during a time window is generated. The optimal set depends on a total time for backing up each virtual machine needing backup and a cost metric that indicates a cost of not backing up the virtual machine during the time window. The optimal set also meets various system constraints that reflect the backup resource limitations. Performing backups according to the optimal set limits the number of missed backups and the number of service level agreement violations, thereby improving the backup performance without costly additions to its infrastructure.

Abstract: System and method for managing public internet protocol (IP) addresses for a group of virtual data centers utilize a virtual overlay network to route communications between the virtual data centers and a public network through a virtual edge router of one of the virtual data centers using a public IP address assigned to that virtual edge router.

Abstract: Examples can include (1) identifying, on a network, a source node and a destination node, the source node including at least one source node virtual machine (“VM”) to be replicated as a destination node VM on the destination node, (2) performing a full synchronization by copying disks used by the source node VM in a current operational state to the destination node VM, (3) scheduling start times for multiple update synchronizations of changed data between the source node VM and the destination node VM, the start times being scheduled at different time intervals, wherein a first time interval is greater than a second time interval, and (4) performing, at a switch-over time, a shutdown of the source node VM and transmitting data changes that are pending on the disk to the destination node. Various corresponding systems, methods, and non-transitory computer-readable media are also disclosed.

Abstract: A system and method for backing up workloads for multiple tenants of a cloud computing system are disclosed. A method of backing up workloads for multiple tenants of a computing system, includes determining that a first tenant has elected to maintain a copy of backups in an off-site location and a second tenant has elected to not maintain a copy of backups in an off-site location, directing first backup data of the first tenant to a backup storage device within the computing system and to a backup storage device at the off-site location, and directing second backup data of the second tenant to the backup storage device within the computing system, and not to the backup storage device at the off-site location.

Abstract: Backups of workloads in a multi-tenant cloud computing environment are efficiently queued and scheduled. A method of backing up workloads for multiple tenants of a cloud computing system, includes the steps of determining a pool of workloads to be backed up during a time window, the workloads including workloads for a first tenant and workloads for a second tenant, placing a backup task for backing up each of the workloads in the pool in a scheduling queue and prioritizing the backup tasks according to backup parameters specified by the tenants, sizes of workload data to be backed up, and hardware constraints of a backup storage device executing the backups, and instructing the backup storage device to execute the backup tasks according to an order of the backup tasks in the scheduling queue.

Abstract: Techniques disclosed herein manage and resolve incidents in hybridity manager applications, without the back-and-forth manual steps of the traditional software support lifecycle. In one embodiment, a virtual network operations center (NOC) with a centralized view of distributed, cross-cloud hybridity manager installations is responsible for tracking incident reports relating to hybridity managers and associated bugs, and the virtual NOC automatically publishes notifications of upgrade builds that fix the tracked bugs to the appropriate hybridity managers. When the same bug is encountered again with another hybridity manager instance, the virtual NOC may also publish an upgrade notification to the other hybridity manager instance, without requiring a support ticket to be filed, etc.

Abstract: Techniques are provided for reducing the amount of data that to be transferred in a hybrid cloud system in order to spawn a VM at a private cloud computing system from a template library stored in a public cloud computing system. Instead of storing full virtual machine templates, template libraries at the public cloud computing system are “differential” libraries. Differential templates in these differential libraries only include data that is different as compared with either a base template or another differential template. Assuming a private cloud system already stores a base image, the private cloud system may spawn a VM based on a particular template simply by downloading the appropriate differential templates. This technique reduces the total amount of data that needs to be downloaded from the public cloud system in order to spawn a particular VM.

Abstract: System and method for managing public internet protocol (IP) addresses for a group of virtual data centers utilize a virtual overlay network to route communications between the virtual data centers and a public network through a virtual edge router of one of the virtual data centers using a public IP address assigned to that virtual edge router.

Abstract: A system and method for backing up virtual machines are disclosed. To better use the backup resources, an optimal set of virtual machines needing backup during a time window is generated. The optimal set depends on a total time for backing up each virtual machine needing backup and a cost metric that indicates a cost of not backing up the virtual machine during the time window. The optimal set also meets various system constraints that reflect the backup resource limitations. Performing backups according to the optimal set limits the number of missed backups and the number of service level agreement violations, thereby improving the backup performance without costly additions to its infrastructure.

Abstract: A system and method for backing up workloads for multiple tenants of a cloud computing system are disclosed. A method of backing up workloads for multiple tenants of a computing system, includes determining that a first tenant has elected to maintain a copy of backups in an off-site location and a second tenant has elected to not maintain a copy of backups in an off-site location, directing first backup data of the first tenant to a backup storage device within the computing system and to a backup storage device at the off-site location, and directing second backup data of the second tenant to the backup storage device within the computing system, and not to the backup storage device at the off-site location.

Abstract: Backups of workloads in a multi-tenant cloud computing environment are efficiently queued and scheduled. A method of backing up workloads for multiple tenants of a cloud computing system, includes the steps of determining a pool of workloads to be backed up during a time window, the workloads including workloads for a first tenant and workloads for a second tenant, placing a backup task for backing up each of the workloads in the pool in a scheduling queue and prioritizing the backup tasks according to backup parameters specified by the tenants, sizes of workload data to be backed up, and hardware constraints of a backup storage device executing the backups, and instructing the backup storage device to execute the backup tasks according to an order of the backup tasks in the scheduling queue.

Abstract: A system and method for backing up workloads for multiple tenants of a cloud computing system are disclosed. A method of backing up workloads for multiple tenants of a computing system includes triggering an archival process according to an archival policy set by a tenant, and executing the archival process by reading backup data of the tenant stored in a backup storage device of the computer system and transmitting the backup data to an archival store designated in the archival policy, and then deleting or invalidating the backup data stored in the backup storage device.

Abstract: Techniques are provided for reducing the amount of data that to be transferred in a hybridcloud system in order to spawn a VM at a private cloud computing system from a template library stored in a public cloud computing system. Instead of storing full virtual machine templates, template libraries at the public cloud computing system are “differential” libraries. Differential templates in these differential libraries only include data that is different as compared with either a base template or another differential template. Assuming a private cloud system already stores a base image, the private cloud system may spawn a VM based on a particular template simply by downloading the appropriate differential templates. This technique reduces the total amount of data that needs to be downloaded from the public cloud system in order to spawn a particular VM.