Discussed herein are techniques that utilize hierarchical locality information of host machines included in a cluster network for the execution of general workloads. Hierarchical locality information for each host machine of a plurality of host machines is stored. The hierarchical locality information for a host machine identifying, for each locality of a plurality of localities, location information for the locality. Responsive to receiving a request requesting execution of a workload, the hierarchical locality information for the plurality of host machines is obtained and provided (e.g., to a customer) in response to the request.

A method of identifying errors or manipulations of data or software, includes receiving a first hash value stored in a first block of the memory, receiving a second hash value from a reference memory, and comparing the hash values. If different, error correction information and the content of the first block is received. The content of the first block is reconstructed by in accordance with the error correction information, generating a hash value and comparing the hash value of the modified content with the received first hash value, until the modified content and the received hash values are identical. The content of the first block received from the reference memory and the content of the reconstructed first block stored in the memory of the device are compared for identifying the differences in the content.

Generating a private key recovery seed based on random words extracted from an input memory of a user and using the recovery seed to recover the private key. An input that is related to a specific memory of a user is received. The specific memory was previously entered and used to generate random words that are related to each other by being included in the specific memory. The random words are extracted from the received input. The random words are associated with a first private key recovery mechanism for recovering a private key. The random words are input into the first private key recovery mechanism to generate a recovery seed. The recovery seed is input into a second private key recovery mechanism. The second private key recovery mechanism generates a recovered private key upon performing a recovery operation on the private key recovery seed.

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system identifies buckets that are to be searched. The data intake and query system performs a hash on bucket identifiers of the identified buckets to identify search nodes to search the buckets.

Technologies for allocating resources of managed nodes to workloads to balance multiple resource allocation objectives include an orchestrator server to receive resource allocation objective data indicative of multiple resource allocation objectives to be satisfied. The orchestrator server is additionally to determine an initial assignment of a set of workloads among the managed nodes and receive telemetry data from the managed nodes. The orchestrator server is further to determine, as a function of the telemetry data and the resource allocation objective data, an adjustment to the assignment of the workloads to increase an achievement of at least one of the resource allocation objectives without decreasing an achievement of another of the resource allocation objectives, and apply the adjustments to the assignments of the workloads among the managed nodes as the workloads are performed. Other embodiments are also described and claimed.

Disclosed herein are techniques for visualizing and configuring controller function sequences. Techniques include identifying at least one executable code segment associated with a controller; analyzing the at least one executable code segment to determine at least one function and at least one functional relationship associated with the at least one code segment; constructing, a software functionality line-of-code behavior and relation model visually depicting the determined at least one function and at least one functional relationship; displaying the software functionality line-of-code behavior and relation model at a user interface; receiving a first input at the interface; in response to the received first input, animating the line-of-code behavior and relation model to visually depict execution of the at least one executable code segment on the controller; receiving a second input at the interface; and in response to the received second input, animating an update to the line-of-code behavior and relation model.

Methods, information handling systems and computer readable media are disclosed for generation of consistent structured data hash values across platforms and structured data formats. In one embodiment, a method includes identifying, at an information handling system, a set of data segments within a set of structured data and expressing the set of structured data in a standard format. This embodiment of the method further includes, for each of the data segments within the set of data segments, applying a hash algorithm to produce a data segment hash value and obtaining a standardized identifier for the data segment. The method continues with assembling an aggregate hash code comprising the standardized identifier and the data segment hash value for each of the data segments, and confirming an association of the aggregate hash code with the set of structured data.

The present teaching relates to method, system, medium, and implementations for storage management. A hash table is constructed, having an index file having one or more slots, each of which includes one or more buckets. Each bucket stores one or more types of records, including a direct record, an indirect record, and a forwarding record. A direct record stores data directly in a bucket of a slot of the index file. When a storage request is received related to some relevant data, the request is handled based on the constructed hash table.

Systems and methods presented herein provide examples for distributing resources in a UEM system. In one example, the UEM system can receive a request to check out a user device enrolled in the UEM system. The request can include a profile identifier (“ID”) of a user profile making the request and attributes of the user device. The UEM system can create a hash of group IDs associated with the profile ID. The UEM system can create a device context that includes the device attributes and the hash. The UEM system can then determine if the device context matches to a resource context. Resource contexts can identify a set of UEM resources associated with a device context. Where a match is found, the UEM system can provide the corresponding resources to the user device.

Access control lookups may be implemented that support user-configurable and host-configurable processing stages. A request may be received and evaluated to determine whether bypass of user-configured access request processing stages should be bypassed. A lookup may be determined for user-configured access controlled decisions, and the access control decisions can be applied, if not bypassed. A lookup may be determined for a host-configured access control decisions and the access control decisions applied.