Abstract: Systems/techniques that facilitate multi-admin verification (MAV) for improved security of data stores are provided. In various embodiments, auto-execution of electronic requests may be facilitated. For example, an electronic approval of an electronic request may be received from an approver credential. A determination can be made that the electronic approval is a final electronic approval that causes a threshold number of valid electronic approvals for placing the electronic request in an approved state to be met. The electronic request is marked as being in the approved state in response to determining that the electronic approval is the final electronic approval. The electronic request is executed automatically after the electronic request has entered the approved state when the electronic request has been designated for auto-execution.

Abstract: Systems/techniques that facilitate multi-admin verification (MAV) for improved security of data stores are provided. In various embodiments, a system can access a request to perform an operation on an object stored in a data store. In various aspects, the system can identify an MAV rule that specifies: approver credentials authorized to approve the request; a threshold number of approvals needed to place the request into an approved state; a request expiration timespan denoting for how long the request can be approved; executor credentials authorized to execute the request once/when in the approved state; an approved state expiration timespan denoting for how long the request can be executed once/when in the approved state; and/or a maximum number of times the request can be executed once/when in the approved state. In various instances, the system can approve/execute the request according to the MAV rule, thereby safeguarding/protecting the object from the operation.

Abstract: One or more techniques and/or systems are provided for generating a macroscopic cluster view of storage devices, as opposed to merely an isolated view from an individual node. For example, nodes within a node cluster may be queried for storage device reports comprising storage device information regarding storage devices with which the nodes are respectively connected (e.g., I/O performance statistics, path connections, storage device attributes, status, error history, etc.). The storage device reports may be aggregated together to define one or more storage device data structures (e.g., a storage device data structure comprising one or more tables that may be populated with storage device information). In this way, the cluster view may be generated based upon querying one or more storage device data structures (e.g., an error cluster view, a storage device cluster view, a node summary cluster view, etc.).

Abstract: One or more techniques and/or systems are provided for generating a macroscopic cluster view of storage devices, as opposed to merely an isolated view from an individual node. For example, nodes within a node cluster may be queried for storage device reports comprising storage device information regarding storage devices with which the nodes are respectively connected (e.g., I/O performance statistics, path connections, storage device attributes, status, error history, etc.). The storage device reports may be aggregated together to define one or more storage device data structures (e.g., a storage device data structure comprising one or more tables that may be populated with storage device information). In this way, the cluster view may be generated based upon querying one or more storage device data structures (e.g., an error cluster view, a storage device cluster view, a node summary cluster view, etc.).

Abstract: A variety of complex multiphase tasks may execute within a cluster network environment. It may be advantageous to track and analyze the processing of such multiphase tasks. Accordingly, one or more techniques and/or systems are disclosed for tracking the processing of a multiphase task within a cluster network environment. In particular, runtime support for recording task processing annotations may be embedded into a multiphase task using an analysis model. The analysis model may specify task processing annotations that are to be recorded during one or more phases of processing the multiphase task. During execution, task processing annotations may be recorded and associated with corresponding phases of the multiphase task. Task processing annotations may be aggregated into aggregated statistical task data. The aggregated statistical task data may be used to generate views of statistical data, which may provide insight into the cluster network environment (e.g., problematic nodes, bottlenecks, etc.).

Abstract: One or more techniques and/or systems are provided for generating a macroscopic cluster view of storage devices, as opposed to merely an isolated view from an individual node. For example, nodes within a node cluster may be queried for storage device reports comprising storage device information regarding storage devices with which the nodes are respectively connected (e.g., I/O performance statistics, path connections, storage device attributes, status, error history, etc.). The storage device reports may be aggregated together to define one or more storage device data structures (e.g., a storage device data structure comprising one or more tables that may be populated with storage device information). In this way, the cluster view may be generated based upon querying one or more storage device data structures (e.g., an error cluster view, a storage device cluster view, a node summary cluster view, etc.).

Abstract: A variety of complex multiphase tasks may execute within a cluster network environment. It may be advantageous to track and analyze the processing of such multiphase tasks. Accordingly, one or more techniques and/or systems are disclosed for tracking the processing of a multiphase task within a cluster network environment. In particular, runtime support for recording task processing annotations may be embedded into a multiphase task using an analysis model. The analysis model may specify task processing annotations that are to be recorded during one or more phases of processing the multiphase task. During execution, task processing annotations may be recorded and associated with corresponding phases of the multiphase task. Task processing annotations may be aggregated into aggregated statistical task data. The aggregated statistical task data may be used to generate views of statistical data, which may provide insight into the cluster network environment (e.g., problematic nodes, bottlenecks, etc.).