Disclosed here is a system to automatically predict and resolve issues within a telecommunication network. Initially, the system builds a service registry to store dependence information within the network, which can include software components and hardware components. Various components of the network create logs of their operations. Machine learning models examine the logs and detect any issues. Upon detecting an issue or abnormal event, the system can automatically resolve the issue by determining the most similar issue occurring previously and determining a solution that resolved the previous most similar issue. In addition, the system can propagate the fix to dependent systems and/or notify the dependent systems of the issue.

Systems, methods, and apparatuses for autonomous functional testing of a processor are described. In one example, a processor includes a plurality of processor cores that are each coupled to a respective power management agent circuit; a cache shared by the plurality of processor cores; and a control register, that when set, causes: a save of a state of a first processor core of the plurality of processor cores to storage, a transfer of control of the first processor core to a power management agent circuit of the first processor core, isolation of the first processor core from the other of the plurality of processor cores by the power management agent circuit, performance of one or more functional tests from the cache on the first processor core caused by the power management agent circuit to generate a test result, removal of the isolation of the first processor core from the other of the plurality of processor cores by the power management agent circuit, and a transfer of the control by the power management agent circuit back to the first processor core.

Techniques for automatically selecting device tests for testing devices configured for operation in wireless communication networks, based upon maintenance releases (MRs) received from original equipment manufacturers. When an MR with changes for a device is received, the MR may be analyzed in order to determine what the changes pertain to with respect to the device. The changes may be clustered with respect to requirements for the changes and a knowledge base may be consulted by a recommendation engine in order to determine candidate tests for testing the MR. The candidate tests may be based upon previous tests, failed tests and, relevant tests. Based at least in part on the identified previous tests, failed tests and relevant tests, one or more tests may be selected for testing devices with respect to the newly received MR.

Disclosed here is a system to automatically predict and resolve issues within a telecommunication network. Initially, the system builds a service registry to store dependence information within the network, which can include software components and hardware components. Various components of the network create logs of their operations. Machine learning models examine the logs and detect any issues. Upon detecting an issue or abnormal event, the system can automatically resolve the issue by determining the most similar issue occurring previously and determining a solution that resolved the previous most similar issue. In addition, the system can propagate the fix to dependent systems and/or notify the dependent systems of the issue.

A method of an automatic support service that includes receiving a request for additional assistance for an error from a user interface, retrieving error information from a logging system for the error, generating an error information collection interface, in response to the request, populating the error information collection interface with the error information from the logging system, sending the error information collection interface to be displayed to the user by the user interface, and receiving additional error information from the user via the error information collection interface.

Embodiments relate to capturing referenced information in a report to resolve a computer problem. A report for a problem is determined to contain at least one referenced document, the report being generated based on at least one log. Relevant content is determined in the at least one referenced document based at least in part on hint information associated with the at least one referenced document and a term in the report. An enhanced report is generated for the problem of the computer equipment by inserting the relevant content into the report. A problem experienced by computer equipment is resolved by causing execution of at least one operation identified in the enhanced report.

The present embodiments relate to data center outage detection and alert generation. An outage detection service as described herein can process near real-time data from various sources in a datacenter and process the data using a model to determine one or more projected sources of a detected outage. The model as described herein can include one or more machine learning models incorporating a series of rules to process near-real time data and offline data and determine one or more projected sources of an outage. An alert message can be generated to provide the projected sources of the outage and other data relevant to the outage.

Embodiments relate to capturing referenced information in a report to resolve a computer problem. A report for a problem is determined to contain at least one referenced document, the report being generated based on at least one log. Relevant content is determined in the at least one referenced document based at least in part on hint information associated with the at least one referenced document and a term in the report. An enhanced report is generated for the problem of the computer equipment by inserting the relevant content into the report. A problem experienced by computer equipment is resolved by causing execution of at least one operation identified in the enhanced report.

A method for managing error messages includes obtaining, by a message resolution manager, a plurality of error messages, performing an error message consecutive deduplication on the plurality of error messages to obtain a plurality of deduplicated error messages, generating a plurality of message sequences using the plurality deduplicated error messages, applying a message sequence frequency algorithm to the plurality of message sequences to obtain a high severity message sequence list, and initiating an error message resolution on at least one message sequence specified in the high severity message sequence list.

An improved method for telecommunication analysis and monitoring employing a logic analyzer device. The logic analyzer device provides a plurality of concurrent graphic depictions of different electronic signals under differing electronic protocols for signal error determination on a communications channel. Error source determination is enabled through the provided concurrent depiction of digital and analog signal characteristics in the differing protocols, including digital data packets, signal voltages and timing. Through this concurrent depiction the user can visually discern potential causation for electronic communication errors caused by non-continuous signal anomalies affecting one or more of the protocols.