346 results about "Logfile" patented technology

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 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 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.

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.

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.

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.

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 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.

This disclosure provides a data processing method and apparatus. The method, during the migration of a metadata table from a source cluster to a target cluster, detects a write operation on the metadata table, performs a checkpoint operation on the metadata table to back up the existing metadata information under the checkpoint operation, migrates the existing metadata information to the target cluster, and then replays the existing metadata information based on the corresponding log files after the write operation to obtain the target metadata information after the write operation. Finally, after the metadata table migration is complete, the corresponding data file is migrated to the target cluster. This technical solution avoids data location confusion during data migration and does not affect normal read / write operations for users.

The application discloses a time series data processing method and system, a storage medium and an electronic device. The method comprises the following steps: in response to a client request, obtaining time series data to be processed from a time series database, wherein the time series data is generated by a data source according to a time period and stored in the time series database; storing a sharding result corresponding to the time series data in a message queue, wherein the sharding result is used to enable the message queue to store a corresponding log file; and writing the sharding result read from the message queue into a memory. The application solves the technical problem of low data storage efficiency.

The invention provides a communication driver and interface construction automation solution providing method, device and system for machinery equipment. The system may comprise a memory for storing instructions and a processor. Instructions, when executed by a processor, provide a universal driver, the system can communicate with PLCs of a plurality of manufacturers, receive address mapping data in the form of Excel files and automatically analyze the data through a memory analyzer, generate PLC I / O mapping according to the analyzed data, automatically generate corresponding source codes, compile generated source codes, and send the generated source codes to the processor. And automatically linking the compiled program with the PLC I / O, and automatically generating and storing a log generated in the system operation process. The system automatically analyzes stored log files to assess system performance and errors, visualizes equipment states and test consistency line by line according to analysis results, and controls and provides the results to a user terminal.

The invention discloses a log compression and decompression method and device, equipment and a medium in the technical field of computers. According to the method and the device, the log file not only comprises the content of the current log, but also comprises the position information when the content of the current log subsequently and repeatedly appears, and the position information can be used for querying the log original text of the corresponding compressed field in the log file. Namely, the log file itself serves as a compression index table, so that the method does not need to maintain and store the index table, does not need to use a complex coding compression algorithm, is used for real-time log compression, reduces records of repeated log contents, and retains an original log text.

The application discloses a kind of based on key value memory network's complex electromechanical system design knowledge active recommendation method.First, the scene feature semantic information extraction of software platform log file in the design process of complex electromechanical system is carried out, and scene ontology is established based on scene feature semantic information, and system scene knowledge base is formed by scene ontology and original knowledge base;Then, the scene maximum frequent sequence is used to describe the scene sequence feature similarity between designers;Again, the knowledge item interaction sequence of all designers is learned, and the knowledge item sequence preference vector corresponding to all designers is obtained;Further, input to key value memory network, and the initial design knowledge active recommendation sequence is obtained;Finally, after knowledge item selection, the final design knowledge active recommendation sequence of each designer is obtained.The application obtains design knowledge active recommendation sequence more in line with the needs of designers, and then improves the efficiency of complex electromechanical system design.

This invention relates to the field of data processing and discloses a database log archiving method, apparatus, device, and medium, comprising: identifying a target redo log file to be archived from the database; creating a preliminary redo log file with the same attributes as the target redo log file and empty content within the same logical disk as the target redo log file; moving the target redo log file to a preset archiving directory located within the same logical disk via MV operations; changing the filename and storage path of the preliminary redo log file to the original filename and storage path of the target redo log file via MV operations; and mounting the revised preliminary redo log file to the database. This invention solves the problems of high I / O consumption and low archiving efficiency in existing database log archiving technologies.

The invention relates to a data synchronization method, system and device for a hybrid load service and electronic equipment. The method comprises the following steps: analyzing a log file generated by a source end data storage system to obtain all transaction data, and filtering the transaction data according to a preset white list rule to obtain target transaction data related to a target service; performing multi-dimensional analysis on the target transaction data, and generating at least one transaction judgment feature representing transaction behavior characteristics according to an analysis result; determining a target data synchronization optimization strategy matched with the transaction judgment feature, and obtaining corresponding transaction data in the target transaction data according to the target data synchronization optimization strategy; and buffering and sorting the obtained transaction data, and synchronizing the transaction data to a target data storage system through playback processing. The technical problems that analysis of operators is time-consuming, misjudgment is easy to occur, and a synchronization channel is blocked due to high-load mixed services are solved.

A logfile recommender service incorporates trained machine learning models to predict recommended logfile types for support tickets. The machine learning models are trained using data from past support tickets such as titles, problem descriptions, and communication records. After receiving a request to generate a logfile recommendation for a given support ticket, the logfile recommender service first calls an attachment prediction machine learning model (e.g., a binary classification model) to predict whether logfiles are relevant to the support ticket. If so, the logfile recommender service calls an attachment recommendation machine learning model (e.g., a multi-label classification model) to generate a list of recommended logfile types for the support ticket, which is output by the logfile recommender service as the logfile recommendation. Logfiles of the recommended types can then be attached to the support ticket to facilitate and expedite resolution of the support ticket.

The application provides a lightweight log generation method, system and electronic equipment, and relates to the technical field of computer software.The method comprises the following steps: creating a running log management task and an operation log management task with lower priority than an application task, and establishing a message queue; when a log event is generated by the application task, a formatted log message containing a timestamp, a log level, a module identifier and content is generated and sent to the message queue; the log management task asynchronously acquires the log message, and distributes the log message to a running log folder or an operation log folder according to the log level and type; and the size of the log file is monitored, and when the capacity threshold is reached, a cover writing mechanism is enabled to recycle the file storage area.The application realizes asynchronous decoupling of log recording and the application task, supports hierarchical classified storage and cyclic coverage, significantly improves the maintainability and debugging efficiency of the embedded system while ensuring real-time performance, and meets the lightweight log demand in a resource-limited environment.

The invention relates to a log processing method based on dynamic triggering and index driving, and relates to the technical field of computer software, and the method comprises the following steps: coding log entries through a dictionary coding rule, generating coded log entries, and writing the coded log entries into a plaintext log file; monitoring a file state of the plaintext log file, and when the file state meets a preset dynamic triggering condition, compressing the plaintext log file to generate a compressed log file; generating an index file associated with the compressed log file, wherein the index file comprises metadata; and in response to a user query request, positioning and compressing a target data block in the log file based on the metadata, decompressing and reversely decoding the target data block, and filtering decoded log contents according to the query mode to output a log query result. By means of the scheme, development complexity is reduced, efficient real-time compression is achieved, full scanning is avoided, consumed time in the index positioning stage is reduced from the minute level to the millisecond level, and query efficiency is improved.

The invention discloses a method, device and equipment for automatically generating an EMIR test case and a medium, and the method comprises the steps: obtaining process information required by a layout according to a preset parameter configuration file; performing geometric abstraction on each component of the layout according to the parameter configuration file to obtain a geometric shape of each component of the layout; obtaining coordinates of each component of the layout according to the geometrical shape, the parameter configuration file and the process information of each component of the layout; generating a script for drawing the layout according to the coordinates of the components of the layout and executing the script to obtain a recorded layout file; and obtaining a log file of the drawing layout according to the layout file so as to generate an EMIR test case. Through geometric abstraction of the components of the layout of the EMIR test case and automation of the EMIR test case, the construction efficiency of the test case can be greatly improved, the labor cost is saved, and the competitiveness of domestic EDA tools in the current situation is enhanced.

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 system inputs at least one security log file from a first data domain into a first machine learning (ML) model. The system compute, using an output from the first ML model, a weighted sentiment value for one or more of the multiple cybersecurity events. The system detects, using a second ML model, an anomaly in a first cybersecurity event of the multiple cybersecurity events. The system correlates, using a third ML model, the anomaly in the first cybersecurity event to a different anomaly in a second cybersecurity event associated with a second data domain. The system determines, using a fourth machine learning model, a cybersecurity action to minimize a cyberattack. The system determines, using the fourth model, a predicted impact to the telecommunication network associated. The system generates a prioritization ranking of every cybersecurity action and executes each cybersecurity action based on the prioritization ranking.

An embodiment includes a method of process analysis that includes obtaining a preliminary log file. The preliminary log file is generated during implementation of a first process. The method includes identifying a first token associated with the first process in the preliminary log file. The method includes calculating an expected number of the first token in the preliminary log file. The method includes identifying a number of times the first token is present in the preliminary log file. The method includes determining a progress indicator of the first process based on a comparison between the expected number of the first token in the preliminary log file and the number of times the first token is present in the preliminary log file.

The embodiment of the invention provides a log processing method and device and electronic equipment, and relates to the technical field of big data. According to the method, a predefined log format is generated in response to an execution request of a current test case, multiple pieces of server information associated with the current test case are obtained, after a test is triggered, a unique service identifier returned by a tested system is obtained, a matching rule is constructed according to the unique service identifier and the predefined log format, and the server information is matched according to the matching rule. According to the method, the log records associated with the current test case are screened out from the log files of the multiple servers, the problems that logs are scattered and manual positioning is difficult in a distributed environment are solved, and the accuracy of log association and the collection efficiency are improved.

The invention provides an EasyLogger-based log management and SFTP automatic synchronization method, which comprises the following steps that: when equipment runs, an application program outputs logs through an integrated EasyLogger component, and adds color identifiers for output logs of different levels based on a preset rule to obtain colored logs; storing the coloring log in a local file in a rolling manner based on a preset strategy, and generating a unique hash value for the coloring log stored in the local file; a preset triggering condition is continuously monitored, and when the triggering condition is met, the SFTP transmission client is started to realize the uploading of the coloring log; after the coloring log is uploaded, the remote server returns receiving confirmation, and the integrity of the uploaded file is verified based on the Hash value of the coloring log; after the integrity verification of the uploaded file is passed, the corresponding log file successfully uploaded on the device is automatically deleted, and the local storage space is released, the device flow and the storage space are saved to the maximum extent, the method and the device are suitable for an Internet of Things scene sensitive to cost and resources, and the pain point of the resource-limited embedded device in log management is solved.

The application discloses a hybrid memory-based NUMA-aware key-value storage system and an operating method, and belongs to the field of key-value storage. The system comprises a plurality of NUMA nodes; in the PM of each NUMA node, key-value pair data is written in the form of log items into a log file; a first storage area in the DRAM of each NUMA node constitutes a volatile index layer and is used for storing the address information of the log item where the key and the latest value are located; a second storage area in the DRAM of each NUMA node constitutes a RAF cache and is used for caching key-value pair data; the higher the access frequency and the higher the delay of the NUMA node initiating an access request to access the PM of the NUMA node where the key-value pair data is located, the greater the corresponding cache benefit; when the RAF cache is replaced, the entry with the smallest cache benefit is selected for replacement. The application can optimize the PM access performance across NUMA nodes and provide efficient key-value storage services.

This invention provides a parallel replay method and system, relating to the field of Internet technology, comprising: acquiring all gateway log files and synchronizing them to a replay system database; parsing the gateway log files according to a specified date using multiple threads to obtain original transaction information and registering it to the replay system database; segmenting all transactions corresponding to the gateway log files by time and replaying them in chronological order; acquiring the original transaction data and sending request messages to the new core system through the replay system to obtain new response messages and response results; configuring a transaction parameter table, assembling comparison expressions based on the transaction parameter table, and comparing the response messages returned by the old and new core systems; configuring and maintaining statistical SQL, executing the statistical SQL in both the old and new core systems, and comparing the statistical results. This invention enables the system to accommodate two core business models through technical means and also allows for the verification of the new core system's functionality through parallel replay, reducing the workload of manual testing.

One or more techniques and / or systems are provided for dynamically provisioning logical storage pools of storage devices for applications. For example, a logical storage pool, of one or more storage devices, may be constructed based upon a service level agreement for an application (e.g., an acceptable latency, an expected throughput, etc.). Real-time performance statistics of the logical storage pool may be collected and evaluated against the service level agreement to determine whether a storage device does not satisfy the service level agreement. For example, a latency of a storage device within the logical storage pool may increase overtime as log files and / or other data of the application increase. Accordingly, a new logical storage pool may be automatically and dynamically defined and provisioned for the application to replace the logical storage pool. The new logical storage pool may comprise storage devices expected to satisfy the storage level agreement.