Abstract:
A computer implemented method includes: accessing from a configuration management database, by a virtualization manager, configuration data for a first computing node of a computing system; generating, by the virtualization manager, a set of attribute/value pairs for the first computing node using the configuration data; and managing, by the virtualization manager, a first container on the first computing node using the set of attribute/value pairs for the first computing node.
Abstract:
The present disclosure is to determine a probable root cause of a performance issue. For example, a method can include processing, using a processor, a set of calls for a Hypertext Transfer Protocol (HTTP) transaction wherein individual calls of the set of calls have a set of parameters; and identifying, using the processor, that the HTTP transaction has a performance issue that falls below a predetermined level of a performance metric. Further steps can include separating, using the processor, the set of calls into a first group with the performance issue and a second group without the performance issue; discovering, using the processor, a common subset of parameters among the first group; and determining that the common subset of parameters is a probable root cause of the performance issue if the common subset of parameters is not found in the second group.
Abstract:
In one example in accordance with the present disclosure, a method may include receiving a digit sequence including a subset of N digits encoded with semantic information and determining a set of possible combinations for the N digits in the subset. The method may also include establishing a mapping between each possible combination in the set of possible combinations and a corresponding integer sequence belonging to a set of integer sequences. Each integer sequence in the set of integer sequences is of the length of N-1. The method may also include identifying a selected integer sequence corresponding to the subset and replacing n-1 digits from the subset with the selected integer sequence. The method may also include replacing a digit of the subset with a digit value calculated to produce a valid checksum for the entire first digit sequence, wherein the first digit is not included in the n-1 digits.
Abstract:
Examples include monitoring performance of an application. Some examples include tracing a set of transactions associated with an application, generating a transaction interface that includes an area to receive a selection of a transaction of the set of transactions, and receiving a selected transaction. Based on the selected transaction, a transaction monitor rule may be built to monitor the selected transaction. Based on the transaction monitor rule, a performance interface may be generated that includes an area having transaction performance information of the selected transaction.
Abstract:
Example implementations relate to comparable UI object identifications. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also automatically identify, based on the correlated data points, a set of comparable UI objects.
Abstract:
Examples disclosed herein relate to data objects associated with private set intersection (PSI). Some examples disclosed herein may enable identifying a set of server elements and a set of data objects. Each data object of the set of data objects may be associated with at least one server element of the set of server elements. Some examples further enable sending the set of server elements and the set of data objects to a client computing device that has a set of client elements. A private set intersection (PSI) between the set of server elements and the set of client elements may be inaccessible by the client computing device, and a subset of the set of data objects that are associated with the PSI may be accessible by the client computing device.
Abstract:
In some examples, a system includes a scan execution engine and a scan adaptation engine. The scan execution engine may execute a scan of a web application hosted on a web host. During scan execution, the scan adaptation engine may adapt a subsequent scan portion for later execution based on a scan metric received from a monitoring agent that monitors the web application, the web host, or both.
Abstract:
In some examples, first segment of computer language text in a first rule in IT workflow data and a second segment of computer language text in a second rule in the IT workflow data may be identified. In some examples, a similarity score may be determined between the first and the second rules based on a comparison of the first segment with the second segment.
Abstract:
An example method comprises performing for each class from a plurality of classes: constructing binary training set for the class, the binary training set including labeled cases for that class from the main training set other labeled cases from the main training set; training classifier for the class on the binary training set; computing a local calibration threshold using scores of the labeled cases in the binary training set; and adjusting all scores of the label cases in the binary training set with the local calibration threshold to meet a global decision threshold. The method also comprises determining, with the processor, a global hierarchical calibration threshold by using the adjusted scores for all classes to optimize a performance measurement of all trained classifiers. The method further comprises classifying, with the processor, a new case by using a previously trained classifier, a local calibration threshold, and the global hierarchical calibration threshold.
Abstract:
Examples disclosed herein relate to encryption of community-based security information. Some examples may enable authorizing a user of a community to access an encrypted data item (e.g., at least an encrypted portion of community-based security information of that community) using a decryption key. The community may be generated on a security information sharing platform based on a set of community attributes. The decryption key may comprise a private key corresponding to each user attribute of a set of user attributes that are associated with the authorized user where the set of user attributes satisfy the set of community attributes.