Abstract:
Examples perform monitoring of multiple-step, concurrently executed workflows across distributed nodes. Requests from an intermediate node are classified by a load balancer as monitoring or non-monitoring. Non-monitoring requests are handled by any node; however, monitoring requests are distributed to all nodes via a plurality of queues but handled only by nodes executing the subject workflow. The load balancer receives reports from any node executing the subject workflow, and passes the first report to the intermediate node.
Abstract:
Exemplary methods, apparatuses, and systems include receiving a command to perform a failover workflow for a plurality of logical storage devices from a protected site to a recovery site. A first logical storage device within the plurality of logical storage devices is determined to be a stretched storage device. In response to the failover command, a site preference for the first logical storage device is switched from the protected site to the recovery site. The failover includes a live migration of a virtual machine that resides on the first logical storage device. The live migration is performed without interruption to one or more services provided by the virtual machine. The site preference for the first logical storage device is switched prior to performing the live migration of the virtual machine.
Abstract:
A cloud availability manager configured to execute a recovery workflow that fails over one or more virtual machines (VMs) to and from a cloud computing system. In doing so, the cloud availability manager typically performs multiple operations for each VMs. The operations involve making several application programming interface (API) calls to component APIs of management components within the cloud computing system. To avoid bringing down the entire cloud infrastructure, the cloud availability manager throttles the API calls to other components while executing a recovery workflow. The throttling spans multiple instances (nodes) of the cloud availability manager and involves cooperation from the other management components to ensure the throttling is fair across all tenants of the cloud computing system.
Abstract:
A recovery manager discovers replication properties of datastores stored in a storage array, and assigns custom tags to the datastores indicating the discovered replication properties. A user may create storage profiles with rules using any combination of these custom tags describe replication properties. The recovery manager protects a storage profile using a policy-based protection mechanism. Whenever a new replicated datastore is provisioned, the datastore is dynamically tagged with the replication properties of their underlying storage, and will belong to one or more storage profiles. The recovery manager monitors storage profiles for new datastores and protects the newly provisioned datastore dynamically, including any or all of the VMs stored in the datastore.
Abstract:
To prevent a user from initiating potentially dangerous virtual machine migrations, a storage migration engine is configured to be aware of replication properties for a source datastore and a destination datastore. The replication properties are obtained from a storage array configured to provide array-based replication. A recovery manager discovers the replication properties of the datastores stored in the storage array, and assigns custom tags to the datastores indicating the discovered replication properties. When storage migration of a virtual machine is requested, the storage migration engine performs or prevents the storage migration based on the assigned custom tags.
Abstract:
Exemplary methods, apparatuses, and systems include a recovery manager receiving selection of a storage profile to be protected. The storage profile is an abstraction of a set of one or more logical storage devices that are treated as a single entity based upon common storage capabilities. In response to the selection of the storage profile to be protected, a set of virtual datacenter entities associated with the storage profile is added to a disaster recovery plan to automate a failover of the set of virtual datacenter entities from a protection site to a recovery site. The set of one or more virtual datacenter entities includes one or more virtual machines, one or more logical storage devices, or a combination of virtual machines and logical storage devices. The set of virtual datacenter entities is expandable and interchangeable with other virtual datacenter entities.
Abstract:
Exemplary methods, apparatuses, and systems include a recovery manager receiving selection of a storage profile to be protected. The storage profile is an abstraction of a set of one or more logical storage devices that are treated as a single entity based upon common storage capabilities. In response to the selection of the storage profile to be protected, a set of virtual datacenter entities associated with the storage profile is added to a disaster recovery plan to automate a failover of the set of virtual datacenter entities from a protection site to a recovery site. The set of one or more virtual datacenter entities includes one or more virtual machines, one or more logical storage devices, or a combination of virtual machines and logical storage devices. The set of virtual datacenter entities is expandable and interchangeable with other virtual datacenter entities.
Abstract:
Mapping computer resources to consumers in a computer system is described. In an example, a method of mapping computer resources to consumers in a computer system includes: receiving tags assigned to the computer resources at a resource manager executing in the computer system, where the resource manager: identifies a first tag assigned to a first computer resource; determines whether a first consumer is associated with the first tag; enables the first consumer to access the first computer resource if the first consumer is associated with the first tag; and prevents the first consumer from accessing the first computer resource if the first consumer is not associated with the first tag.
Abstract:
Examples perform monitoring of multiple-step, concurrently executed workflows across distributed nodes. Requests from an intermediate node are classified by a load balancer as monitoring or non-monitoring. Non-monitoring requests are handled by any node; however, monitoring requests are distributed to all nodes via a plurality of queues but handled only by nodes executing the subject workflow. The load balancer receives reports from any node executing the subject workflow, and passes the first report to the intermediate node.
Abstract:
Examples perform concurrent execution of distributed workflows sharing common operations by a plurality of nodes, such as execution of recovery plans for disaster recovery of virtual machines operating on and off premises. Concurrent execution of identical operations that were part of a previously executed workflow are prevented, by evaluating the source of the workflow and whether the workflow has previously been initiated by that source. The disclosure is scalable to allow for new nodes to be included.