Component life cycle automatic monitoring method and device, equipment and storage medium
By encapsulating basic component base classes for components, establishing an automated interception layer, generating session identifiers, and recording state transition processes, the problem of coupling between component lifecycle monitoring logic and business logic is solved, achieving efficient and automated monitoring and end-to-end tracing, and improving development efficiency and data consistency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING BAILONG MAYUN TECH CO LTD
- Filing Date
- 2025-12-15
- Publication Date
- 2026-04-28
AI Technical Summary
In existing technologies, the component lifecycle monitoring logic is highly coupled with business logic, resulting in low development efficiency, high maintenance costs, poor consistency of monitoring data, lack of end-to-end tracing capabilities, difficulty in automatically recording state transition paths, and low efficiency in operation and maintenance troubleshooting.
By encapsulating basic component base classes for components, an automated interception layer for component-level lifecycle is established, session identifiers are generated, state transition processes and timestamps are recorded in real time, lifecycle data is collected and classified, stored in a local queue, and the data is batch aggregated and sent to the server.
It enables automated monitoring of component lifecycles, reduces human error, improves development efficiency, ensures data consistency, supports end-to-end tracing, and facilitates the diagnosis of cross-component issues.
Smart Images
Figure CN121935100A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of automatic data reporting technology, and in particular to a method, apparatus, device and storage medium for automated monitoring of component lifecycle. Background Technology
[0002] In driver-side applications of real-time O2O (Online To Offline) platforms such as ride-hailing and freight, the stability and smoothness of components are crucial. Any anomalies, such as loading failures, rendering lag, or unresponsive interactions, may lead to lost orders and a decline in driver experience. Therefore, implementing fine-grained monitoring of component lifecycles has become the core of improving application quality. The related technologies still have significant shortcomings: First, the monitoring logic is highly coupled with the business logic, requiring developers to manually insert reporting code into various lifecycle methods of the components, resulting in bloated and highly intrusive code. This leads to low development efficiency, high maintenance costs, and problems easily caused by omissions or changes. Second, due to reliance on manual implementation, the consistency of event tracking is poor, and the naming of events, reporting timing, and parameter structure are not standardized, making data cleaning and analysis difficult. Third, the monitoring dimensions are limited to single-point events, lacking continuous tracking of the complete lifecycle chain of components. It is difficult to automatically record the state transition path and time consumption, and the ability to locate problems such as slow rendering or mid-process lag is insufficient. Fourth, when online anomalies occur, operations and maintenance personnel need to manually piece together logs from massive discrete events in the backend to reconstruct the scene, resulting in low troubleshooting efficiency and difficulty in ensuring accuracy.
[0003] Therefore, in view of the shortcomings of existing technical solutions, the present invention provides a method for automated monitoring of component lifecycle. Summary of the Invention
[0004] Therefore, it is necessary to provide a method, apparatus, device, and storage medium for automated monitoring of component lifecycles to address the aforementioned technical problems.
[0005] On the one hand, a method for automated monitoring of component lifecycle is provided. The method includes: encapsulating a base component class for at least one component and establishing an automated interception layer for component-level lifecycle; in response to receiving a business session, generating a session identifier and writing the session identifier into the context of at least one component associated with the business session; through the automated interception layer for component-level lifecycle, recording the state transition process and timestamp of at least one component in real time based on the session identifier in the context; collecting component lifecycle data, classifying and associating the component lifecycle data according to the session identifier, and storing it in a local queue; performing batch aggregation on the component lifecycle data in the local queue, and sending the batch aggregation results to the server.
[0006] Optionally, before encapsulating a base component class for at least one component and establishing an automated interception layer for the component-level lifecycle, the method further includes: constructing a cross-platform universal lifecycle semantic model; automatically identifying the technology stack based on the runtime environment and dynamically loading the interception adapter corresponding to the current platform; and determining the architecture of the automated interception layer for the component-level lifecycle corresponding to the current platform based on the cross-platform universal lifecycle semantic model and the interception adapter.
[0007] Optionally, a base component class can be encapsulated for at least one component to establish an automated interception layer for the component-level lifecycle, including: configuring the aspect-oriented programming framework and determining custom annotations; determining pointcuts based on the custom annotations and writing aspect classes for aspect-oriented programming based on the pointcuts; and adding custom annotations in response to components that cannot be encapsulated in the base component class.
[0008] Optionally, through the automated interception layer of the component-level lifecycle, based on the session identifier in the context, the state transition process and timestamp of at least one component are recorded in real time, including: obtaining snapshots of at least one component before and after the state change through the automated interception layer of the component-level lifecycle; and associating the snapshots with the corresponding state transition process.
[0009] Optionally, component lifecycle data is collected, classified and associated according to session identifiers, and stored in a local queue. This includes: processing the component lifecycle data, where the processing methods include compression and / or encryption; and storing the component lifecycle data in a first cache or a second cache according to the importance of the processed component lifecycle data.
[0010] Optionally, batch aggregation of component lifecycle data in the local queue and sending the batch aggregation results to the server include: sending data to the server in response to detecting that the number of component lifecycle data entries in the local queue has reached a target threshold; and / or, in response to detecting whether component lifecycle data exists in the local queue at fixed time intervals, and if so, sending the component lifecycle data to the server; and / or, in response to detecting that a specific event has occurred, sending component lifecycle data to the server, wherein the specific event is used to describe an event in which the application environment has changed.
[0011] Optionally, batch aggregation of component lifecycle data in the local queue and sending the batch aggregation results to the server also includes: the server constructing a lifecycle graph based on the session identifier corresponding to the component lifecycle data; and the server performing anomaly detection and early warning for at least one component based on the lifecycle graph.
[0012] On the other hand, an automated component lifecycle monitoring device is provided, comprising: a first processing module for encapsulating a base component class for at least one component and establishing an automated interception layer for component-level lifecycle; a second processing module for generating a session identifier in response to receiving a business session and writing the session identifier into the context of at least one component associated with the business session; a third processing module for recording the state transition process and timestamp of at least one component in real time based on the session identifier in the context through the automated interception layer for component-level lifecycle; a fourth processing module for collecting component lifecycle data, classifying and associating the component lifecycle data according to the session identifier, and storing it in a local queue; and a fifth processing module for batch aggregating the component lifecycle data in the local queue and sending the batch aggregation results to the server.
[0013] On another front, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it performs the following steps: encapsulates a base component class for at least one component and establishes an automated interception layer for component-level lifecycle; in response to receiving a business session, generates a session identifier and writes the session identifier into the context of at least one component associated with the business session; through the automated interception layer for component-level lifecycle, records the state transition process and timestamp of at least one component in real time based on the session identifier in the context; collects component lifecycle data, classifies and associates the component lifecycle data according to the session identifier, and stores it in a local queue; performs batch aggregation on the component lifecycle data in the local queue, and sends the batch aggregation results to the server.
[0014] On another front, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it performs the following steps: encapsulating a base component class for at least one component and establishing an automated interception layer for component-level lifecycles; in response to receiving a business session, generating a session identifier and writing the session identifier into the context of at least one component associated with the business session; through the automated interception layer for component-level lifecycles, recording the state transition process and timestamp of at least one component in real time based on the session identifier in the context; collecting component lifecycle data, classifying and associating the component lifecycle data according to the session identifier, and storing it in a local queue; performing batch aggregation on the component lifecycle data in the local queue, and sending the batch aggregation results to the server.
[0015] The aforementioned automated monitoring method, apparatus, device, and storage medium for component lifecycles includes the following steps: encapsulating a base component class for at least one component and establishing an automated interception layer for component-level lifecycles; generating a session identifier in response to a received business session and writing the session identifier into the context of at least one component associated with the business session; recording the state transition process and timestamp of at least one component in real time based on the session identifier in the context through the automated interception layer for component-level lifecycles; collecting component lifecycle data, classifying and associating the component lifecycle data according to the session identifier, and storing it in a local queue; batch aggregating the component lifecycle data in the local queue and sending the batch aggregation results to the server; thus, through automation and seamless data tracking, human error can be reduced, development efficiency and quality can be improved, full-link tracing can be supported while ensuring data consistency, and cross-component issues can be easily diagnosed. Attached Figure Description
[0016] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 This is a flowchart illustrating an automated monitoring method for the component lifecycle in one embodiment; Figure 2 This is a system diagram illustrating an automated component lifecycle monitoring method in one embodiment; Figure 3 This is a structural block diagram of a component lifecycle automated monitoring device in one embodiment; Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0019] It should be understood that, in the description of this application, unless the context explicitly requires it, the words "including," "comprising," and similar terms throughout the specification should be interpreted as including rather than exclusive or exhaustive; that is, meaning "including but not limited to."
[0020] It should also be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this application, unless otherwise stated, "a plurality of" means two or more.
[0021] It should be noted that the terms "S1," "S2," etc., are used only for descriptive purposes and do not specifically refer to the order or sequence, nor are they intended to limit this application. They are merely for the convenience of describing the method of this application and should not be construed as indicating the sequential order of the steps. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.
[0022] In one embodiment, such as Figure 1 As shown, a method for automated monitoring of component lifecycle is provided, including the following steps: S101: Encapsulate a base component class for at least one component and establish an automated interception layer for the component-level lifecycle.
[0023] Here, the executing entity can be the client.
[0024] Here, the base class of basic components can include core functionalities such as component lifecycle management, event system, and state management, such as lifecycle callback methods like onCreate, onStart, onResume, onVisible, onHide, and onDestroy.
[0025] The components can include order receiving components, navigation components, and settlement components.
[0026] Specifically, the base class of the basic component can be an abstract, generic BaseComponent (such as BaseFragment, BaseViewController).
[0027] Specifically, by encapsulating a unified component base class, the lifecycle methods of all business components are uniformly intercepted and enhanced at the framework level, thereby achieving complete decoupling between monitoring logic and business logic.
[0028] S102: In response to receiving a business session, generate a session identifier and write the session identifier into the context of at least one component associated with the business session.
[0029] Here, a business session refers to a set of contextual information, state data, and transaction boundaries that the system maintains to track, coordinate, and manage interactions between users and the system within a complete business operation cycle.
[0030] Here, context refers to the collection of environmental information and state data required for program execution.
[0031] The context of a component includes the environment containing the session identifier that the component can access when it is executed.
[0032] Specifically, a business session can be from when a driver receives an order to when the order is settled.
[0033] Here, a complete business session (such as an order from push to completion) generates a globally unique session identifier, which is used to connect all the scattered lifecycle events in the session.
[0034] The session identifier can be trace_id, which is a global identifier.
[0035] Specifically, a Global Context Manager can be defined. When a business session (such as "order received") begins, the Global Context Manager generates a globally unique trace_id and injects it into all packets related to that session and the context of subsequently launched components.
[0036] S103: Through the automated interception layer of component-level lifecycle, based on the session identifier in the context, record the state transition process and timestamp of at least one component in real time.
[0037] State transitions can include creation, destruction, and updating, such as transitioning from create to visible.
[0038] Specifically, the lifecycle state changes of a component can include INIT (initialization), CREATED (creation complete), ATTACHED (mounted), VISIBLE (displayed), INTERACTED (interacted), DETACHED (unmounted), and DESTROYED (destroyed).
[0039] Specifically, each state transition generates a structured data record containing the component ID, state, precise timestamp (Unix milliseconds), and trace_id.
[0040] Specifically, obtain the current business session identifier, identify the component whose current state has changed, record the current timestamp and state information, save this record, and associate it with the session identifier.
[0041] S104: Collect component lifecycle data, classify and associate the component lifecycle data according to the session identifier, and store it in a local queue.
[0042] In one embodiment, dynamic queue management can be implemented, including support for priority queues, capacity limits, and expiration policies.
[0043] In one embodiment, a cache data backup mechanism or a local cache and cloud synchronization mechanism can be added.
[0044] S105: Perform batch aggregation of component lifecycle data in the local queue and send the batch aggregation results to the server.
[0045] This can be done asynchronously.
[0046] It should be noted that this application can reduce human error, improve development efficiency and quality, and support end-to-end tracing while ensuring data consistency, making it easier to diagnose cross-component issues through automation and seamless event tracking.
[0047] In some specific implementations, before encapsulating a base component class for at least one component and establishing an automated interception layer for component-level lifecycles, the method further includes: Build a cross-platform, universal lifecycle semantic model; Automatically identify the technology stack based on the operating environment and dynamically load the interception adapter corresponding to the current platform; Based on the cross-platform universal lifecycle semantic model and intercept adapter, determine the architecture of the automated interception layer for the component-level lifecycle corresponding to the current platform.
[0048] Here, the lifecycle semantic model can include the type of lifecycle event (such as mounting, updating, unmounting, etc.), the data structure of the event (such as event ID, timestamp, component identifier, etc.), and the semantics of event delivery.
[0049] Among them, the lifecycle semantic model is used to map different lifecycle terms from various platforms to a unified concept.
[0050] The technology stack can include React, Vue, Android, and mini-programs.
[0051] Specifically, it determines whether the current application is a React application, a Vue application, or a mini-program by detecting global variables (such as React and Vue) or environment characteristics (such as the wx object in the mini-program environment).
[0052] Here, the interceptor adapter intercepts the lifecycle of components in the corresponding technology stack (for example, using higher-order components or hooks in React, using mixins or plugins in Vue, and overriding the Page or Component constructor in WeChat Mini Programs).
[0053] This improves the portability of the solution, supports multi-platform deployment, and eliminates the need to rewrite the monitoring logic.
[0054] In some specific implementations, a base component class is encapsulated for at least one component, and an automated interception layer for the component-level lifecycle is established, including: Configure the aspect-oriented programming framework and define custom annotations; Determine the pointcut based on the custom annotation, and write the aspect class for aspect-oriented programming based on the pointcut; Add custom annotations for components that cannot be encapsulated in the base component class.
[0055] Here, Aspect-Oriented Programming (AOP, AspectJ for Android) is a programming paradigm that aims to separate cross-cutting concerns from the main business logic in order to improve the modularity of the code.
[0056] Here, the pointcut is used to define the connection point that will be notified to match, and the aspect is a modular implementation of the lateral concern.
[0057] Here, components that cannot encapsulate the base component class can be components that cannot inherit from the base class, such as Activity, Fragment, or third-party components.
[0058] The custom annotation can be @MonitorLifecycle.
[0059] Specifically, for legacy code or third-party components that cannot be uniformly managed through inheritance, the AOP framework was introduced. By defining pointcuts, all method executions marked with specific annotations (such as @MonitorLifecycle) are intercepted, thereby achieving non-intrusive monitoring.
[0060] In this way, custom annotations provide flexibility, extend support for legacy systems or third-party components, cover scenarios where inheritance relationships cannot be modified, and greatly improve the scope of application.
[0061] In some specific implementations, an automated interception layer at the component level lifecycle is used to record the state transition process and timestamp of at least one component in real time based on the session identifier in the context, including: By using the automated interception layer of the component-level lifecycle, obtain snapshots of at least one component before and after a state change; Associate snapshots with their corresponding state transition processes.
[0062] In this way, state change points can be intercepted by utilizing framework lifecycle callbacks (such as Android's Activity and Fragment lifecycles), state management middleware (such as Redux, MobX, Vuex, etc.), AOP (Aspect-Oriented Programming) to intercept method execution, or by using proxy patterns (such as Java dynamic proxies, ES6 Proxy) to wrap the target object.
[0063] Specifically, a data structure for state snapshots is defined to capture key state information of components. A snapshot of the current state is captured before a state change (such as when leaving the current state), and a snapshot of the new state is captured after a state change (such as when entering a new state). The snapshots before and after the change are recorded together with the state change event and reported.
[0064] In one embodiment, performance issues can be avoided by limiting recursion depth and filtering fields.
[0065] This provides richer debugging information, making it easier to analyze the reasons for state changes.
[0066] In some specific implementations, component lifecycle data is collected, categorized and associated according to session identifiers, and stored in a local queue, including: Process component lifecycle data, including compression and / or encryption. Depending on the importance of the processed component lifecycle data, the component lifecycle data will be stored in either the first or second cache.
[0067] The first cache can be a memory cache, and the second cache can be a disk cache. The memory cache is used for fast read and write, and the disk cache is used for persistent storage.
[0068] Specifically, on the Web, data compression can be performed using CompressionStream (native) or pakko. On React Native, data compression can be performed using pakko or react-native-zip-archive. To achieve cross-platform consistency, data compression can be performed using lz-string.
[0069] Specifically, on the web, temporary keys (session-level) can be generated using window.crypto.subtle. On mobile devices, the master key can be stored using the system Keychain (iOS) / Keystore (Android). In other cases, short-term keys can be dynamically issued by the server.
[0070] In one embodiment, the cache can be cleaned up by time: deleting data older than a certain number of days; the cache can be cleaned up by quantity: when the cached data exceeds a certain quantity, deleting the oldest data; the cache can be cleaned up by storage space: when the cache occupied space exceeds a threshold, deleting data according to LRU (Least Recently Used).
[0071] In this way, storage resources are optimized, high-priority data is uploaded first, and critical information is not lost.
[0072] In some specific implementations, batch aggregation of component lifecycle data in the local queue is performed, and the batch aggregation results are sent to the server, including: In response to detecting that the number of component lifecycle data entries in the local queue has reached a target threshold, data is sent to the server; and / or, In response to periodically checking the local queue for component lifecycle data, if the data exists, the component lifecycle data is sent to the server; and / or, In response to the detection of a specific event, component lifecycle data is sent to the server. The specific event describes an event that changes the application environment.
[0073] Each time, one or more automatic reporting methods can be used for reporting.
[0074] Specifically, a queue and a timer are initialized. When new monitoring data is generated, the data is added to the queue, and the queue length is checked to see if it has reached the quantitative reporting threshold. If it has, reporting is triggered (quantitative reporting). At the same time, the timer is triggered every 5 minutes to check if there is data in the queue. If there is, it is reported (timed reporting). In addition, system events (network status changes, application foreground / background switching) are monitored. When an event occurs (such as connecting to Wi-Fi or the application entering the background), reporting is triggered (event-driven reporting).
[0075] In one embodiment, to avoid triggering multiple reporting processes simultaneously, a lock can be added during reporting to ensure that only one reporting task is executed at a time.
[0076] After a successful report, the reported data is removed from the queue. If the report fails, the data is retained and the number of failures is recorded, and the report is attempted again next time (but multiple data may be merged).
[0077] In this way, the combination of multiple triggering mechanisms balances data real-time performance and system stability, reduces server load, avoids network congestion, and improves reliability.
[0078] In some specific implementations, batch aggregation of component lifecycle data in the local queue and sending the batch aggregation results to the server also includes: The server constructs a lifecycle graph based on the session identifiers corresponding to the component lifecycle data; The server performs anomaly detection and early warning for at least one component based on the lifecycle graph.
[0079] In the lifecycle graph, nodes represent component states, edges represent transitions between states, and time-consuming metrics can be attached to the edges.
[0080] Specifically, the server automatically calculates a large number of refined metrics based on graph data, such as component loading time (Create-to-Visible), interaction response latency, and page rendering completion time (FMP). These metrics can be aggregated and analyzed by dimensions such as App version, operating system, device model, and city.
[0081] Specifically, flexible threshold alarm rules can be configured (e.g., does the time from the creation of an order card to its visibility exceed 2 seconds?).
[0082] Specifically, machine learning algorithms can be integrated to learn from historical indicator data, automatically establish dynamic baselines, and intelligently detect abnormal fluctuations (such as slow increases in time) that do not exceed fixed thresholds but deviate from historical normal patterns, thus achieving earlier and smarter early warnings.
[0083] In this way, visualized lifecycle relationships and automated anomaly detection improve operational efficiency, enable proactive monitoring, and reduce downtime.
[0084] In one embodiment, Figure 2 This is a system schematic diagram in an embodiment of this application, such as... Figure 2 As shown, the system includes: a client and a server.
[0085] Specifically, the client executes the following steps: S1 Business components inherit from a unified base class or use AOP aspects; S2 The base class / aspect automatically hooks lifecycle methods; S3 The context manager assigns trace_id and records the status and timestamp; S4 Data is assembled and temporarily stored in a local queue; S5 After aggregation, structured lifecycle data is asynchronously reported via a wireless link.
[0086] S1 and S2: Seamless Tracking and Unified Lifecycle Interception Layer The design incorporates a unified component base class: the system defines an abstract, generic BaseComponent (such as BaseFragment, BaseViewController), from which all business components must inherit. This base class overrides all core lifecycle callback methods (such as onCreate, onStart, onResume, onVisible, onHide, onDestroy).
[0087] Aspect-Oriented Programming (AOP) is used as a supplementary solution: for legacy code or third-party components that cannot be uniformly managed through inheritance, the system introduces an AOP framework (such as AspectJ for Android). By defining pointcuts, all method executions marked with specific annotations (such as @MonitorLifecycle) are intercepted, thereby achieving non-intrusive monitoring.
[0088] Both of these methods work together to build a unified lifecycle interception layer beneath the business code, achieving complete and physical decoupling between monitoring logic and business logic.
[0089] This significantly reduces invasiveness and maintenance costs: business developers don't need to worry about monitoring code when writing components; all monitoring actions are handled automatically by the underlying framework. Monitoring capabilities automatically take effect when a component is added or modified, achieving "one-time setup, lifelong benefit," completely avoiding omissions and errors; and ensuring data consistency: because all components' monitoring logic is implemented using the same standard, it ensures a high degree of uniformity in event names, reporting timing, and additional parameters, providing extremely high consistency and reliability for backend data processing and analysis.
[0090] S3: Global Context Management and Tracing Link Construction Among them, session-level trace_id injection: The system defines a global context manager (GlobalContextManager). When a core business session (such as "order received") begins, the manager generates a globally unique trace_id and injects it into all data packets related to that session and the context of subsequently started components.
[0091] Among these features, automated trace tracking: When the lifecycle interception layer records each event, it automatically retrieves the trace_id from the current context and uses it as the core field of the event data. In this way, all lifecycle events scattered across different components and time points in a complete business session (e.g., from when a driver receives an order to when the order is settled) can be linked together through this trace_id.
[0092] Thus, true end-to-end full-link tracing is achieved: the technological innovation lies in the perfect application of the concept of backend distributed link tracing (such as OpenTracing) to component-level monitoring within the monolithic client application. This allows us to reconstruct the complete path of an order within the driver's app, rather than observing isolated, discrete points; greatly improving the efficiency of problem localization: when online feedback indicates "order lag," operations personnel only need to enter the order number to directly query the associated trace_id, and pull out the complete lifecycle sequence and performance data of all components in this session with one click, quickly determining which link has a problem, achieving accurate and rapid problem localization.
[0093] S4 and S5: Structured Data Assembly and Intelligent Reporting Specifically, a standardized state machine and data model are defined: the system defines a precisely defined finite state machine for the component lifecycle (e.g., INIT->CREATED->ATTACHED->VISIBLE->INTERACTED->DETACHED->DESTROYED). Each state transition generates a structured data record containing the component ID, state, precise timestamp (Unix milliseconds), and trace_id.
[0094] The system employs local caching and aggregated reporting: The generated monitoring data is not sent immediately. A local persistent queue is used for caching, and an intelligent reporting strategy is followed: a) quantitative reporting (when the queue reaches a certain length); b) timed reporting (e.g., every 5 minutes); c) event-driven reporting (in a Wi-Fi environment, when the application switches to the background). Data is compressed and batch-aggregated before reporting.
[0095] Thus, network overhead and power consumption are reduced: batch aggregation and conditional reporting strategies greatly reduce the number of HTTP requests, saving users' mobile data and device power, reflecting a deep optimization of user experience; data reliability is enhanced: the local caching mechanism ensures that data will not be lost even in unstable or offline environments, and will continue to be reported after the network is restored, ensuring the high reliability and integrity of monitoring data.
[0096] Specifically, the server executes the following steps: S6 receives and parses the data; S7 associates events by trace_id and builds a lifecycle graph; S8 analyzes the data using a rule engine / machine learning model; S9 determines if there is an anomaly; S10 if so, triggers an alarm and pushes a diagnostic report; S11 if not, aggregates metrics and provides a visual dashboard.
[0097] S6 and S7: Server-side data association and lifecycle graph construction Among them, real-time data pipeline processing: the server receives massive amounts of reported data through a high-performance real-time data pipeline (such as based on Kafka+Flink / SparkStreaming).
[0098] Among them, the streaming merging based on trace_id: the stream processing engine uses trace_id as the key to merge and sort all events within a session window, and restores the state transition process of each component according to the timeline.
[0099] Among these features, the automatic generation of the lifecycle graph involves the system automatically converting the merged event sequence into a directed graph data structure—the lifecycle graph. In this graph, nodes represent component states, edges represent transitions between states, and time-consuming metrics (such as the time taken from CREATED to VISIBLE) can be attached to the edges.
[0100] In this way, data is transformed into intuitive insights: dry log files are transformed into visual graphs rich in time series and topological relationships, making program behavior clear at a glance and providing a strong structured data foundation for subsequent analysis.
[0101] S8, S9, S10 and S11: Intelligent Analysis and Early Warning Among these features, the system calculates a large number of refined metrics based on graph data, such as component loading time (Create-to-Visible), interaction response latency, and page rendering completion time (FMP). These metrics can be aggregated and analyzed by dimensions such as App version, operating system, device model, and city.
[0102] Among them, rule-based real-time alarms: a powerful built-in rule engine allows operations and maintenance personnel to configure flexible threshold alarm rules (e.g., "If the loading time of 'order card' P90 exceeds 2000ms within 5 minutes, then trigger a P1 level alarm").
[0103] Among its features, machine learning-based anomaly detection integrates machine learning algorithms to learn from historical indicator data and automatically establish dynamic baselines. It can intelligently detect abnormal fluctuations (such as slow increases in latency) that deviate from historical normal patterns but do not exceed fixed thresholds, enabling earlier and smarter warnings.
[0104] Thus, the system shifts from "passive response" to "proactive discovery": Traditional monitoring requires users to report problems before checking logs, while this system can discover potential issues before users do and proactively notify the development team through the alerting system, nipping problems in the bud and greatly improving the service SLA (Service Level Agreement); Data-driven precision optimization: It provides the gold standard for measuring optimization effectiveness. Product and technology teams can accurately evaluate the performance of each release based on multi-dimensional data reports on the dashboard, determine the priority of performance bottlenecks (e.g., optimizing for low-end models and specific cities), making performance optimization work targeted and maximizing return on investment (ROI).
[0105] It should be understood that, although Figure 1 and Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 and Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.
[0106] In one embodiment, such as Figure 3 As shown, an automated component lifecycle monitoring device is provided. The device includes: a first processing module 301, used to encapsulate a basic component base class for at least one component and establish an automated interception layer for component-level lifecycle; a second processing module 302, used to generate a session identifier in response to receiving a business session and write the session identifier into the context of at least one component associated with the business session; a third processing module 303, used to record the state transition process and timestamp of at least one component in real time based on the session identifier in the context through the automated interception layer for component-level lifecycle; a fourth processing module 304, used to collect component lifecycle data, classify and associate the component lifecycle data according to the session identifier, and store it in a local queue; and a fifth processing module 305, used to perform batch aggregation of the component lifecycle data in the local queue and send the batch aggregation results to the server.
[0107] As a preferred implementation, in this embodiment of the application, the device further includes: an adaptive module, which is specifically used to: construct a cross-platform universal lifecycle semantic model; automatically identify the technology stack according to the operating environment and dynamically load the interception adapter corresponding to the current platform; and determine the architecture of the automated interception layer of the component-level lifecycle corresponding to the current platform according to the cross-platform universal lifecycle semantic model and the interception adapter.
[0108] As a preferred implementation, in this embodiment of the application, the first processing module 301 is specifically used for: configuring an aspect-oriented programming framework and determining custom annotations; determining pointcuts based on the custom annotations and writing aspect classes for aspect-oriented programming based on the pointcuts; and adding custom annotations in response to components that cannot encapsulate the base class of basic components.
[0109] As a preferred implementation, in this embodiment of the application, the third processing module 303 is specifically used to: obtain at least one snapshot of a component's state before and after a change through an automated interception layer of the component-level lifecycle; and associate the snapshot with the corresponding state transition process.
[0110] In a preferred embodiment of this application, the fourth processing module 304 is specifically used to: process component lifecycle data, wherein the processing method includes compression and / or encryption; and store the component lifecycle data in a first cache or a second cache according to the importance of the processed component lifecycle data.
[0111] In a preferred embodiment of this application, the fifth processing module 305 is specifically configured to: send data to the server in response to detecting that the number of component lifecycle data entries in the local queue has reached the maximum threshold; and / or, in response to detecting whether component lifecycle data exists in the local queue at fixed time intervals, and if so, send the component lifecycle data to the server; and / or, in response to detecting that a specific event has occurred, send component lifecycle data to the server, wherein the specific event is used to describe an event in which the application environment has changed.
[0112] As a preferred implementation, in this embodiment of the application, the fifth processing module 305 is further configured to: construct a lifecycle graph based on the session identifier corresponding to the component lifecycle data; and perform anomaly detection and early warning on at least one component based on the lifecycle graph.
[0113] Specific limitations regarding the automated component lifecycle monitoring device can be found in the limitations of the automated component lifecycle monitoring method described above, and will not be repeated here. Each module in the aforementioned automated component lifecycle monitoring device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.
[0114] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements an automated component lifecycle monitoring method. The display screen can be an LCD screen or an e-ink display screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.
[0115] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0116] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above-described embodiments of the component lifecycle automated monitoring method when it is run.
[0117] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.
[0118] Embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above-described embodiments of the component lifecycle automated monitoring method.
[0119] Embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in any of the above-described embodiments of the component lifecycle automated monitoring method.
[0120] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0121] The above provides a detailed description of the component lifecycle automated monitoring method, apparatus, table parsing system, and computer device provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only intended to help understand the method and core ideas of this application. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this application.
Claims
1. A method for automated monitoring of a component lifecycle, characterized in that, The method includes: Encapsulate a base component class for at least one component and establish an automated interception layer for the component-level lifecycle; In response to receiving a service session, a session identifier is generated and written into the context of at least one component associated with the service session; Through the automated interception layer of the component-level lifecycle, the state transition process and timestamp of at least one component are recorded in real time based on the session identifier in the context; Collect component lifecycle data, classify and associate the component lifecycle data according to the session identifier, and store it in a local queue; The component lifecycle data in the local queue is aggregated in batches, and the batch aggregation results are sent to the server.
2. The component lifecycle automated monitoring method according to claim 1, characterized in that, Before encapsulating a base component class for at least one component and establishing an automated interception layer for component-level lifecycles, the method further includes: Build a cross-platform, universal lifecycle semantic model; Automatically identify the technology stack based on the operating environment and dynamically load the interception adapter corresponding to the current platform; Based on the cross-platform universal lifecycle semantic model and the interception adapter, determine the architecture of the automated interception layer for the component-level lifecycle corresponding to the current platform.
3. The component lifecycle automated monitoring method according to claim 1, characterized in that, The process involves encapsulating a base component class for at least one component and establishing an automated interception layer for the component-level lifecycle, including: Configure the aspect-oriented programming framework and define custom annotations; The pointcut is determined based on the custom annotation, and the aspect class for aspect-oriented programming is written based on the pointcut. For components that cannot encapsulate the base component class, add the custom annotation.
4. The component lifecycle automated monitoring method according to claim 1, characterized in that, The automated interception layer through the component-level lifecycle, based on the session identifier in the context, records the state transition process and timestamp of at least one component in real time, including: The automated interception layer of the component-level lifecycle is used to obtain snapshots of at least one component before and after a state change. Associate the snapshot with the corresponding state transition process.
5. The component lifecycle automated monitoring method according to claim 1, characterized in that, The process of collecting component lifecycle data, classifying and associating the component lifecycle data according to the session identifier, and storing it in a local queue includes: The component lifecycle data is processed, including compression and / or encryption. Depending on the importance of the processed component lifecycle data, the component lifecycle data is stored in a first cache or a second cache.
6. The component lifecycle automated monitoring method according to claim 1, characterized in that, The step of batch aggregating component lifecycle data in the local queue and sending the batch aggregation results to the server includes: In response to detecting that the number of component lifecycle data entries in the local queue has reached a target threshold, the data is sent to the server; and / or, In response to periodically checking whether component lifecycle data exists in the local queue, if it does, the component lifecycle data is sent to the server; and / or, In response to the detection of a specific event, the component lifecycle data is sent to the server, whereby the specific event describes an event that changes the application environment.
7. The component lifecycle automated monitoring method according to claim 1, characterized in that, The step of batch aggregating the component lifecycle data in the local queue and sending the batch aggregation results to the server also includes: The server constructs a lifecycle graph based on the session identifier corresponding to the component lifecycle data. The server performs anomaly detection and early warning for at least one component based on the lifecycle graph.
8. An automated monitoring device for the lifecycle of a component, characterized in that, The device includes: The first processing module is used to encapsulate a base component class for at least one component and establish an automated interception layer for the component-level lifecycle. The second processing module is configured to generate a session identifier in response to receiving a service session, and write the session identifier into the context of at least one component associated with the service session; The third processing module is used to record the state transition process and timestamp of at least one component in real time based on the session identifier in the context through the automated interception layer of the component-level lifecycle; The fourth processing module is used to collect component lifecycle data, classify and associate the component lifecycle data according to the session identifier, and store it in a local queue; The fifth processing module is used to perform batch aggregation of component lifecycle data in the local queue and send the batch aggregation results to the server.
9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.