A data storage device includes a non-volatile memory device including a memory block having a number of memory dies, and a controller coupled to the memory device. A memory access command is received and a memory access operation based on the received command is performed. A number of bytes transferred during the memory access operation is determined, and the determined number of bytes is analyzed to determine whether the number of transferred bytes is equal to a predetermined number. A transfer status fail bit is set if the number of transferred bytes is not equal to the predetermined number.

Exemplary methods, apparatuses, and systems include receiving a plurality of read operations. The read operations are divided into a current set of a sequence of read operations and one or more other sets. The size of the current set is a first number of read operations. An aggressor read operation is selected from the current set. A first data integrity scan is performed on a victim of the aggressor and a first indicator of data integrity is determined based on the first data integrity scan. A scaling factor is determined using the indicator of data integrity and a number of program erase cycles for the portion of memory. The set size of read operations is adjusted to a second number of read operations using the scaling factor for a subsequent set.

Described is an improved approach to implement fast detection of node death. Instead of just relying on multiple heart beats to fail in order to determine whether a node is dead, the present approach performs an on demand validation using RDMA to determine whether the node is reachable, where the approach of using RDMA is significantly faster than the heartbeat approach.

The independent claims of this patent signify a concise description of embodiments. An automatic process for determining and/or predicting the original root-cause(s) of a violation is proposed using two major enhancements on top of the current VC-Static solution. First, an information repository is created by mining various Static checker components' analysis information, and second, an analysis framework is created which systematically prunes the above-mentioned information repository to find the actual root cause(s) of the violation. This Abstract is not intended to limit the scope of the claims.

Embodiments provide enhanced performance diagnosis in a network computing environment. In response to an occurrence of a performance issue for a node while under operating conditions, common logs for applications on the node are analyzed. The applications are respectively registered in advance for diagnosis services. The applications each register rules in advance for the diagnosis services. At a time of the performance issue, debug programs are automatically issued to generate debug level logs respectively for the applications. Debug level logs are analyzed according to the rules to determine a root cause of the performance issue. A potential solution to the root cause of the performance issue is determined using the rules, without having to recreate the operating conditions occurring during the performance issue. The potential solution to rectify the root cause of the performance issue is executed without having to recreate the operating conditions occurring during the performance issue.

This disclosure describes automatically collecting, analyzing, and remediating operational issues with respect to systems executing within a network. For example, a service provider network may include a monitoring service may generate notifications related to operational issues upon detection of operational issues within a system executing within the service provider network. The monitoring service may provide one or more notifications related to an aggregation service that may aggregate the one or more notifications into a standardized format. Contextual information related to the operational issues may be automatically gathered by an analytics service, which may analyze the contextual information to determine a potential cause of the operational issues. Based on the potential cause, a remediation service may automatically remediate the operational issues.

Program analysis is provided. An intermediate representation of a program is generated. A set of structured inputs is provided to the program. The set of structured inputs are derived from the intermediate representation. The program is executed using the set of structured inputs. A set of action steps is performed in response to observing a violation of a policy during execution of the program using the structured inputs.

Aspects of the invention include detecting an error alert from a target computer system. In response to detecting the error alert, performance data is then retrieved from the target computer system. A gated recurrent unit (GRU) neural network is used to generate a prediction of a root cause of the error alert based on the performance data. The weights of a reset gate of the GRU neural network are adjusted based on received feedback of the prediction.

Systems and methods are disclosed for detecting shingled overwrite errors. When a read error is encountered when reading from shingled recording tracks, a processor may determine whether the read error is an error caused by shingled overwriting. The processor may determine whether the read error is caused by shingled overwriting by determining read signal quality of one or more sectors preceding the read error, such as based on a bit error count or bit error ratio (BER), and comparing the read signal quality to a threshold value. The processor may determine that the read error is caused by shingled overwriting when the read signal quality value is lower than the threshold.

Techniques for determining insight are described. An exemplary method includes receiving a request to provide insight into potential abnormal behavior; receiving one or more of anomaly information and event information associated with the potential abnormal behavior; evaluating the received one or more of the anomaly information and event information associated with the abnormal behavior to determine there is insight as to what is causing the potential abnormal behavior and to add to an insight at least two of an indication of a metric involved in the abnormal behavior, a severity for the insight indication, an indication of a relevant event involved in the abnormal behavior, and a recommendation on how to cure the potential abnormal behavior; and providing an insight indication for the generated insight.