557 results about "Logfile" patented technology

A multi-node, multi-container cluster system that generates, aggregates, and manages log files from services and components to be used for audit logs and to debug and perform other serviceability tasks provided by a vendor of the cluster system. Logs are collected from all components of the system and aggregated into a consistent format for user analysis and debugging. Embodiments provide a comprehensive way to parse and index vast numbers of log files that can then be packaged and displayed to a user in a way that facilitates analysis and debugging and / or efficient input to appropriate debugging programs.

A method for operating a first computer system is provided. The method includes: building a database comprising entries, each entry indicating a failure in one or more second computer systems and an action pattern to remedy the failure, the action pattern indicating log files to be accessed to remedy the failure. In response to detecting a failure in the first computer system, one or more entries of the database that match the detected failure may be identified. The one or more action patterns associated with the identified one or more entries may be used for extracting debugging data representing the detected failure. At least part of the debugging data may be sent to an external system. In response to the sending, instructions to remedy the detected failure may be received from the external system.

The invention relates to the technical field of data processing, and provides a BMC fault recording method and device, computer equipment and a storage medium, and the method comprises the steps: responding to a kernel fault of a target operating system of a target BMC, and printing fault log information; obtaining a pre-configured memory technology device partition; transmitting the fault log information to an annular fault cache region to form cache log data; storing the cached log data in a memory technical equipment partition, and generating a fault log file; and in response to a user reading instruction, reading and outputting the fault log file of the memory technical equipment partition. According to the technical scheme provided by one or more embodiments of the invention, the fault log can be effectively recorded, maintenance personnel can timely and accurately know the fault position and the fault reason, and BMC fault diagnosis and repair can be efficiently completed.

The invention belongs to the technical field of log monitoring, and particularly relates to a real-time log monitoring alarm method, system and equipment based on event driving, and the method comprises the steps: dynamically obtaining a log file path needing to be monitored, monitoring a log file on a server, and sending incremental log data to a specified Topic of Kafka in real time; through an event-driven architecture, using a Kafka consumer group to consume log data in Kafka in real time, and using a kset data type of Redis to temporarily store the log data; performing real-time processing on the log data in the Redis; comparing the statistical result with a preset threshold value, and if the statistical result reaches the preset threshold value, sending alarm information according to a configured notification mode and a notifier; and storing the monitoring result in a relational database, and displaying the monitoring big disk through a visual page. And an event-driven architecture is adopted, so that the data processing flow is more efficient, and the overall performance and expandability of the system are improved.

The invention relates to the technical field of network security, and discloses a security vulnerability AI positioning method and system based on log files. The method comprises the following steps: firstly, analyzing user feedback describing open source component security vulnerabilities to extract fault key entity information, screening related log entries based on the fault key entity information, and constructing a vulnerability propagation graph; identifying a vulnerability triggering initial point set by using a graph traversal algorithm and a graph neural network, calling a component vulnerability case library to deduce a vulnerability utilization propagation chain and calculating a matching degree with a known open source component vulnerability utilization chain feature, and obtaining a maximum probability vulnerability utilization propagation chain and an associated vulnerability triggering initial point set; and generating a root cause positioning report, and updating the knowledge base or model training data according to a user verification result. According to the method, the initial vulnerability point and the complete vulnerability propagation chain of the security vulnerability of the open source component can be accurately and efficiently positioned, and the positioning accuracy and timeliness are improved.

The techniques disclosed herein provide a system for condensing large log files to enable interoperability with transformer-based large language models in automated failure analysis. In various contexts such as enterprise cloud services, log files can be large oftentimes containing millions of lexical units that can incur significant processing time and resource consumption. As such, the disclosed techniques provide a system for producing a directional knowledge graph representing a condensed form of a log file for automated failure analysis. Firstly, the log file is preprocessed to filter information that is irrelevant to the failure that previously occurred. The filtered lexical units are then used to generate a directional knowledge graph comprising a plurality of vertices which correspond to individual lexical units, and which are connected by edges representing the semantic connection between the lexical units. In this way, the directional knowledge graph significantly reduces processing times and improves resource consumption.

In the DevOps process, testing teams use automated testcases to test a product in a regression testing running daily, which generate thousands of log files per run, in various distributed environment with different formats. Solutions to errors depend on SMEs and the impact of solution leads to rework of defect / errors and high degree of heterogeneity. This leads to huge bottleneck in automation of DevOps process leading to loss of productivity and agility. Present disclosure addresses the challenges by providing systems and methods that auto capture the log files of different formats efficiently in a scalable, extendible, and plug-able way. The system then mines and parses the log files based on given identifiers to standardize and de-duplicate to create unique error records with detail description including cause, position, module, timestamp, etc. The system predicts the solutions leveraging the database containing solutions and errors by using a modified Smooth Inverse Frequency technique.

The invention relates to the technical field of artificial intelligence and data engineering, in particular to an intelligent data development treatment system and method based on a large model, the system is composed of a data access layer, a large model treatment engine, an intelligent feature factory, a compliance control layer and an application interface layer, and all the modules cooperate to achieve intelligent transformation of the whole data development process; the method has the beneficial effects that the potential mode of the multi-source heterogeneous data can be automatically identified, for example, transaction records, user behavior data and system monitoring information are distinguished from mixed log files, and manual rule pre-definition is not needed. And dynamically adjusting the protection intensity according to the data use scene.

A distributed operation and maintenance data management method based on a multi-modal log aggregation framework relates to the field of electrical digital data processing, and comprises the following steps: calculating a node load state index; determining node acquisition parameters including an acquisition period and an acquisition trigger condition; when the log file change amount of the target node is larger than the collection triggering condition, event collection is executed, and event collection data flow is obtained; when the log file change amount is smaller than or equal to the collection triggering condition, polling collection is executed according to the collection period, and a periodic collection data stream is obtained; generating a data compensation instruction and executing incremental acquisition to obtain a compensation data stream; merging to generate complete log data, and carrying out type distinguishing to generate a multi-modal data packet; and allocating the data to corresponding storage engines to obtain multi-modal log aggregation data. By implementing the method, the integrity of log data acquisition in a large-scale distributed system can be improved.

The invention relates to the technical field of data storage, and discloses a solid state disk compatibility testing method which comprises the following steps: after a solid state disk is started, automatically collecting basic performance information of the solid state disk based on a Python script and generating a standardized log file; running performance operation of the solid state disk in a preset time period, and simultaneously executing multi-user or multi-task concurrent test operation based on the automated script; a script is used for calling a system startup command or a shutdown command, the next startup process is automatically triggered after shutdown, a startup and shutdown cycle test mechanism is formed, and the startup time, the initialization duration and the abnormal interruption record of the solid state disk are synchronously collected in each startup and shutdown process; when the system runs, the Python script is used for safely removing and reinserting the solid state disk. The problem that an existing test method is narrow in platform coverage range is solved.

The invention provides a DFT process monitoring method and device, electronic equipment and a storage medium, and belongs to the technical field of DFTs. The DFT process monitoring method comprises the steps that in response to monitoring that execution of a current test task is finished, a process state and a current log file generated in the process of executing the current test task are obtained; determining a target predefined analysis rule corresponding to the type of the EDA tool adopted for executing the current test task through a mapping relation between the type of the EDA tool and the predefined analysis rule; analyzing the current log file through a target predefined analysis rule to obtain semantic keywords; and determining a final execution state of the current test task based on the process state and the semantic keyword. According to the scheme, massive unstructured log files generated by different EDA tools can be analyzed, and the final execution state of each test task can be determined.

The invention discloses a data recovery method, device and equipment, a medium and a program product, and relates to the technical field of computers. The data recovery method comprises the following steps: analyzing a pre-write log WAL file in a database to obtain a log frame in the WAL file; the log frame comprises modification information, a page number, transaction metadata and page mapping information for a database page; according to the transaction metadata in the log frame, performing boundary identification on the modification information of the database page to obtain at least one item of transaction information; and according to the transaction information, the page number, the page mapping information and a data structure of the database, performing data recovery in the database to obtain a recovered database. According to the technical scheme provided by the embodiment of the invention, the problem of data loss easily occurring during data recovery can be solved by utilizing the characteristic that the WAL file is independently stored and is not easy to lose.

The invention discloses a target system information processing method of a server and electronic equipment, and relates to the technical field of computers, and the method comprises the steps that in the starting process of the server, a target management controller starts timing for a certain duration after receiving a timer starting command sent by a basic input / output system, and the basic input / output system writes the log file into a target memory shared by the basic input / output system and the target management controller, so that the target management controller does not receive a timer closing command until timing is finished, reads the log file from the target memory, stores the log file and displays alarm information on a target page. The technical problems that an existing target system information processing mode cannot automatically record logs and the recorded logs are usually incomplete, so that the repairing efficiency and effect are poor are solved, and the technical effect that the complete logs are automatically recorded to shorten the subsequent repairing time is achieved.

The invention relates to the technical field of computer software and system performance optimization, in particular to a high-performance software operation log storage method and device. The high-performance software operation log storage method comprises the following steps: monitoring an available memory of a system and a resource state of a concurrent thread number in real time; dynamically initializing parameters of a lockless ring buffer based on the resource state; concurrently writing log information generated by a service thread into the lockless annular buffer area through atomic operation; before or after the log information is written into the lock-free annular buffer area, multi-dimensional filtering based on keywords, date ranges and log levels is conducted on the log information through an intelligent log filtering engine; and through a self-adaptive file management subsystem, writing the log data output by the lock-free annular buffer into a log file, and dynamically managing rotation and archiving of the log file according to a system storage space state.

The invention relates to a kernel hot patch symbol table generation method and device, equipment, a storage medium and a program product. The method comprises the following steps: in a kernel hot patch compiling stage, collecting a compiling log through a pipeline, storing the compiling log as a log file, outputting a hot patch module, and extracting and storing a modified kernel module name at the same time; reading a segment for storing patch function information in the hot patch module, acquiring the byte length of the segment by means of a binary file analysis tool, checking whether the byte length is an integral multiple of 72 or not, if not, terminating the process, if so, scanning the data of the segment line by line, extracting kernel symbol position information and a function address according to a remainder rule of modulo 9 by a line number, and storing the kernel symbol position information and the function address in the hot patch module; querying a function name matched with the function address, comparing the function name with a to-be-patched function name in a log, screening a matching item, and forming a scanning result; and writing a result into a file, and generating a kernel hot patch symbol table. By adopting the method, whether the current hot patch is suitable for loading or not can be conveniently detected in advance during operation and maintenance deployment, and the corresponding preposed environment is prepared.

The invention discloses an exception handling method and electronic equipment, and particularly relates to the technical field of electronics, and by analyzing a collected target log file, the reason for error information in the target log file can be determined, so that the surface reason for exception of target storage equipment in the running process can be obtained. Afterwards, through a mode of jointly analyzing a log analysis file, register information and a program source code, detailed analysis can be carried out in a program source code level, and a code position when an abnormal problem occurs can be quickly and accurately positioned, so that the accuracy of abnormal positioning is improved. Moreover, through a mode of performing result feedback on the abnormity positioning result, the user can be ensured to quickly know the reason of abnormity of the target storage equipment, the closed-loop time of abnormity of the target storage equipment is reduced to the greatest extent, and the feedback efficiency of the problem positioning result is improved.

Ultrasound image devices, systems and methods are provided. A system is configured to determine and track manipulation of an ultrasound probe during an ultrasound exam. Tracked probe manipulations may be synced with recorded user inputs received by the system during the exam. Probe manipulations paired with user inputs are stored as comprehensive log files documenting the exam, which are then converted into narrative text summaries for user review. A neural network is implemented to determine probe positions and orientations utilized during the exam based on landmarks identified in acquired image frames. User inputs received by the system are filtered such that only inputs indicative of exam performance are paired with the determined manipulations of the probe. External sensors are not necessary to track probe motion, but may be implemented to augment or replace certain system features.

Provided are security encryption algorithm identification method and system, including: an electronic device having a software app, a downloadable storage unit for storing a dynamic-link library (DLL), and a scanning module for scanning the DLL to obtain DLL filename information; a cryptography DLL list, with the scanning module comparing the DLL filename information according to the cryptography DLL list to generate security encryption algorithm library (SEAL) filename information and being linked to a SEAL corresponding to the SEAL filename information to retrieve SEAL version information from a metadata of the SEAL; a specified SEAL storage unit having a plugin-equipped SEAL downloadable by the scanning module from the specified SEAL storage unit according to the SEAL filename information and version information and dedicated to replacing the SEAL; and a specified storage unit disposed in the electronic device to store log files created when the software app calls the plugin-equipped SEAL.

Methods, systems, and devices for data management are described. A data management system (DMS) may provide backup and recovery services for customer computing systems or databases. The DMS may implement an active / passive partition scheme to enable reception of log files in a push manner and avoid frequent building and teardown of the stack to back up the database. The DMS may implement two storage partitions which alternate between an active and passive state. Received log files may be stored temporarily in a first storage partition in the active state. Once the first storage partition is transitioned to the passive state, the DMS may capture a snapshot of the storage partition and may store the snapshot. When the first storage partition is transitioned to the passive state, the second storage partition may be transitioned to the active state so that the DMS may continue to receive log files.

The invention provides a log retrieval method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: receiving a log query request, wherein the log query request comprises a query time period and an identifier of a first service; obtaining identifiers of second services which can be provided in the server, identifiers of a plurality of first log files corresponding to each second service, time information of each first log file, and start time and line numbers corresponding to a plurality of groups of log data in each first log file; on the basis of the query time period, the identifier of the first service, the identifier of each second service and the multiple pieces of time information, determining the identifier of a second log file in the identifiers of the multiple first log files; determining a target line number corresponding to the query time period based on the start time and the line number corresponding to the multiple groups of log data in the second log file; and on the basis of the target line number, log data corresponding to the log query request is obtained in the second log file, so that the log retrieval efficiency is improved.

A log system prompts a foundation model to identify regular expressions that delineate single line logs in log files and incorporates user feedback for the regular expressions in a feedback loop as part of a hybrid parsing approach. The log system splits the log files into single line logs according to the regular expressions and augments the single line logs with classifications and values of metadata fields. The augmented single line logs are then clustered into hierarchical clusters with corresponding cluster patterns and the log system stores the augmented single line logs in a database indexed by the classifications and values of metadata fields and associated with corresponding clusters / cluster patterns. A presentation module accesses the database when responding to user queries for filtered single line logs and log correlations / root cause analysis.

The invention belongs to the technical field of computer technology server data processing, and discloses a method and a system for generating observable data through lightweight collection of WEB container logs. According to the method, a mode of expanding a filter of a WEB container is adopted, a user-defined filter is added to generate data in a set format, and the data is output to a log file; the method comprises the following steps: extracting data in a log, processing the data, and then calling a log storage module to store the data in a storage; creating an index according to the label, and maintaining a mapping relationship between the index and the original log content; and converting the log data into an observable view by utilizing the maintained index and data file storage structure. According to the method, lightweight design serves as the core, logs serve as carriers of original data, the resource cost of the data from generation, collection to display is reduced, the observability requirement is met, and the provided data can meet aggregation display of common various dimension index data.

A computing system for cross-platform support and log summarization includes a language model, APIs, processors, and memories to generate queries and troubleshooting steps from log files and IR system results. A method involves obtaining log files, generating IR system queries, and creating troubleshooting steps using a language model. A non-transitory computer readable medium contains instructions for obtaining log files, generating queries, and creating troubleshooting steps based on log files and IR results.

The invention discloses a log query method and device and a storage medium, and relates to the technical field of electronic digital data processing.The method comprises the steps that a query request is received, and the query request is converted into at least one target index key and / or at least one target index key range; in a log structure merge tree (LSM-Tree) index structure, querying a target index entry matched with the target index key and / or the range of the target index key; and obtaining log data corresponding to the query request from a log file according to metadata of a target index value in the target index entry. The log query efficiency is improved.

Systems, computer program products, and methods are described herein for configuring data using advanced computational models for data analysis and automated processing. The present disclosure is configured to train a large language model (LLM), wherein training the LLM comprises using system-specific data comprising feed data, process run logs, historical events, code base, existing permissions, and data classification rules. The present disclosure is configured to determine prone data, wherein the prone data comprises a log file comprising sensitive information, and wherein the prone data is determined via a prone module. The present disclosure is configured to configure the prone data using a generative artificial intelligence (GenAI) module, wherein the GenAI module configures the prone data by masking the sensitive information using a masking procedure. The present disclosure is configured to determine the masking procedure via a decentralized autonomous organization (DAO).

The invention relates to a method and a device for collecting log round-robin files of a linux system. The method comprises the following steps: configuring a file path of a log rotation file to be collected in a linux system; when a log collection program is started, obtaining a target log file and / or a target directory based on the file path; generating and storing file state information of the target log file; adding event monitoring to a target directory corresponding to each file path and a parent directory of the target directory; and when the log file meets a log rotation condition, performing log rotation file collection through the event monitoring and the file state information. According to the method and the device for collecting the log rotation file of the linux system, a create mode and a copyruncate mode which are commonly used by a log tool can be supported at the same time, the log file after rotation is accurately recognized, and repeated collection or missing collection caused by a configuration problem is avoided.

The invention discloses a unified management method, device and equipment for multiple JBOSS instances, and the method comprises the steps: when an instance starting request is received, analyzing configuration information associated with a target JBOSS instance, creating an independent management thread, starting a JBOSS process in the management thread, and creating an anonymous pipeline; the method comprises the following steps of: periodically monitoring a running state of a JBOSS process and capturing log data through an anonymous pipeline on the basis of starting a guard cycle in a management thread; creating a temporary log file corresponding to the log data, and matching with the log data in the temporary log file based on an alarm rule in a preset rule base to obtain a matching result; and generating structured alarm information from the log event indicating successful matching in the matching result according to a preset alarm template, storing the structured alarm information in a log alarm list, and providing the running state of the corresponding target JBOSS instance and the log alarm list through an HTTP service interface. The centralized management and real-time monitoring of a plurality of JBOSS instances can be realized, and the operation and maintenance efficiency and the system availability are improved.

A method for managing log files for recording operations on data stored in a database is provided, wherein a set of log files having an allocated first portion of storage is updated, the allocated first portion of storage is monitored, and a second portion of storage is allocated in dependence on a determination that an available portion of storage is below a predetermined size. A method for generating a snapshot is provided, wherein data entries are included in the snapshot in dependence on a determined relative order of log records in a set of log files. A method of replicating a binary large object is provided, wherein the binary large object is sent to a second database in response to identifying a log record comprising data indicating the binary large object. A method for deleting one or more binary large objects is provided, wherein the data indicating one or more binary large objects that have been logically deleted are stored in a snapshot and the one or more binary large objects are deleted using the data indicating the one or more binary large objects after a previous snapshot is deleted.

The invention discloses a storage device fault prediction method, equipment, a medium and a product, and relates to the technical field of storage, log files collected by a plurality of management controllers of the equipment are obtained, namely, multi-source log files are obtained, and more information sources related to storage device faults are covered; performing alignment processing on the event sequence of the multi-source log file to obtain an alignment event set, and extracting a storage unit feature of the target storage device and a first association feature of the storage unit feature from the alignment event set, and calling a plurality of fault prediction models with different input data to perform fault prediction on the target storage device based on the storage unit characteristics and the first association characteristics, thereby solving the problem of relatively low detection rate of potential errors caused by only paying attention to storage unit errors in related technologies, and improving the detection probability of abnormal information of the storage device. And determining the fault prediction result of the target memory device according to the output result of the fault prediction model, thereby improving the accuracy of the fault prediction result of the memory device.

The present disclosure relates to a database-based data synchronization method, device, medium, equipment and product, and in particular to the technical field of data transmission, which writes the current data synchronization point into the log file of the database through the target statement of the data definition language type carrying the current data synchronization point, and finds the target data synchronization point in the log file of the database when data breakpoint transmission, and then performs data synchronization based on the target data synchronization point, which can play the role of data fence, avoid the invalidation of the data synchronization point in the scene of master-slave database switching, so that the consistency and integrity of the data can be guaranteed in the data synchronization process in the scene of master-slave database switching. Moreover, the data synchronization point can also be supported by various versions of MySQL database through the target statement of the data definition language.