H04L47/762

Allocating additional bandwidth to resources in a datacenter through deployment of dedicated gateways

Some embodiments provide policy-driven methods for deploying edge forwarding elements in a public or private SDDC for tenants or applications. For instance, the method of some embodiments allows administrators to create different traffic groups for different applications and/or tenants, deploys edge forwarding elements for the different traffic groups, and configures forwarding elements in the SDDC to direct data message flows of the applications and/or tenants through the edge forwarding elements deployed for them. The policy-driven method of some embodiments also dynamically deploys edge forwarding elements in the SDDC for applications and/or tenants after detecting the need for the edge forwarding elements based on monitored traffic flow conditions.

Automated local scaling of compute instances

At a first compute instance run on a virtualization host, a local instance scaling manager is launched. The scaling manager determines, based on metrics collected at the host, that a triggering condition for redistributing one or more types of resources of the first compute instance has been met. The scaling manager causes virtualization management components to allocate a subset of the first compute instance's resources to a second compute instance at the host.

Automated local scaling of compute instances

At a first compute instance run on a virtualization host, a local instance scaling manager is launched. The scaling manager determines, based on metrics collected at the host, that a triggering condition for redistributing one or more types of resources of the first compute instance has been met. The scaling manager causes virtualization management components to allocate a subset of the first compute instance's resources to a second compute instance at the host.

CLUSTER CAPACITY MANAGEMENT FOR HYPER CONVERGED INFRASTRUCTURE UPDATES

Disclosed are various implementations of cluster capacity management for infrastructure updates. In some examples, cluster hosts for a cluster can be scheduled for an update. A component of a datacenter level resource scheduler can analyze cluster specific resource usage data to identify a cluster scaling decision for the cluster. The datacenter level resource scheduler transmits an indication that the resource scheduler is successfully invoked. Cluster hosts can then be updated.

Multi-tier resource, subsystem, and load orchestration

Electronic communications received via a network from a plurality of electronic devices may include signals of device interactions or data changes that correspond to process performances by process-performing resources, signals of conditions of loads, or signals of processes associated with the process-performing resources and the loads. Data composites may be formed from the electronic communications, with data portions collected and mapped to resource profile records and load profile records that may be updated with the collected data portions. For each load, at least one of the one or more resource profile records and/or the one or more load profile records may be used to map the process-performing resources to the load. Content nodes may be linked in a network of content nodes, including respective linked content, resource specifications or load specifications. Access to the network of content nodes may be allowed via a control interface.

Multi-tier resource, subsystem, and load orchestration

Electronic communications received via a network from a plurality of electronic devices may include signals of device interactions or data changes that correspond to process performances by process-performing resources, signals of conditions of loads, or signals of processes associated with the process-performing resources and the loads. Data composites may be formed from the electronic communications, with data portions collected and mapped to resource profile records and load profile records that may be updated with the collected data portions. For each load, at least one of the one or more resource profile records and/or the one or more load profile records may be used to map the process-performing resources to the load. Content nodes may be linked in a network of content nodes, including respective linked content, resource specifications or load specifications. Access to the network of content nodes may be allowed via a control interface.

System for automated cross-network monitoring of computing hardware and software resources

A system is provided for automated cross-network monitoring of computing hardware and software status. In particular, the system may track the status of various computing resources using process automation-based operations to simulate calls made by users to the various resources that the users are authorized to access. Based on said operations, the system may assess whether the authorized pathways to the resources and/or their respective components are properly functioning by capturing information regarding the resource, its associated components, and the current status of the resource. The results of these operations may be aggregated to provide an overview of which resources and/or systems are functioning and which are not. In this way, the system may provide a detailed view of the statuses of the individual resources and components within an entity's complex computing network.

System for automated cross-network monitoring of computing hardware and software resources

A system is provided for automated cross-network monitoring of computing hardware and software status. In particular, the system may track the status of various computing resources using process automation-based operations to simulate calls made by users to the various resources that the users are authorized to access. Based on said operations, the system may assess whether the authorized pathways to the resources and/or their respective components are properly functioning by capturing information regarding the resource, its associated components, and the current status of the resource. The results of these operations may be aggregated to provide an overview of which resources and/or systems are functioning and which are not. In this way, the system may provide a detailed view of the statuses of the individual resources and components within an entity's complex computing network.

Cluster capacity management for hyper converged infrastructure updates

Disclosed are various implementations of cluster capacity management for infrastructure updates. In some examples, cluster hosts for a cluster can be scheduled for an update. A component of a datacenter level resource scheduler can analyze cluster specific resource usage data to identify a cluster scaling decision for the cluster. The datacenter level resource scheduler transmits an indication that the resource scheduler is successfully invoked. Cluster hosts can then be updated.

Cluster capacity management for hyper converged infrastructure updates

Disclosed are various implementations of cluster capacity management for infrastructure updates. In some examples, cluster hosts for a cluster can be scheduled for an update. A component of a datacenter level resource scheduler can analyze cluster specific resource usage data to identify a cluster scaling decision for the cluster. The datacenter level resource scheduler transmits an indication that the resource scheduler is successfully invoked. Cluster hosts can then be updated.