Software development application updating processing method and system based on cloud computing

Abstract

The invention provides a software development application updating processing method and system based on cloud computing, and the method comprises the steps: analyzing a dependency relationship between software application components, and generating a software deployment topological graph; preheating the target computing resource on the cloud platform to generate a dynamic resource pool, and executing an application version replacement operation in the dynamic resource pool; when the triggered service is abnormal, switching the abnormal service traffic to a backup resource node, updating the abnormal software application component at the node, and generating an updated software application component; re-accessing the updated software application component into the dynamic resource pool so as to complete software development application updating processing; according to the method, accurate matching of the updating task and the computing resource is realized, the consistency of version replacement is guaranteed, and the problems of low deployment efficiency and insufficient stability caused by confusion of dependence of software updating in a traditional cloud environment are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of software development and application update processing, and in particular to a software development and application update processing method and system based on cloud computing. Background Art

[0002] With the widespread adoption of cloud computing and microservices architectures, enterprises are placing higher demands on software application updates in the context of continuous delivery and rapid iteration. Therefore, ensuring system stability while efficiently coordinating the update sequence of various components, rationally scheduling resources, and achieving rapid recovery in the event of anomalies have become core technical challenges facing current software operations and maintenance.

[0003] To address these needs, existing solutions are based on static resource allocation and dependency-aware automated updates. By pre-building a call relationship graph between microservices, the required computing resources for each component are estimated based on historical data before the update task begins. Fixed resource groups are then allocated on the cloud platform to support the update process. Furthermore, the dependencies in the graph are used to determine the order in which component updates are performed, ensuring that the version upgrade of downstream components is triggered only after the upstream component has been updated. This reduces the risk of service interruptions due to missing dependencies. However, existing solutions have inherent flaws. These include resource estimation relying on historical experience, which can lead to idle resources or resource contention during some update processes. The system can only pause the update process for an abnormal component and relies on manual intervention for troubleshooting and recovery. The system lacks an automated fault-tolerance mechanism, which reduces the robustness and automation level of the update process. Summary of the Invention

[0004] The present invention provides a cloud computing-based software development application update processing method and system to solve the problems in the existing technology such as resource estimation relying on historical experience settings, resulting in resource idleness or resource competition in some update processes; the system can only pause the update process of an abnormal component and rely on manual intervention for fault detection and recovery, lacking an automated fault-tolerant mechanism, which reduces the robustness and automation level of the update process.

[0005] In a first aspect, the present invention provides a method for processing software development and application updates based on cloud computing, comprising:

[0006] Analyze the dependency topology between software application components and generate a software deployment topology map containing component dependency paths;

[0007] Preheating target computing resources on the cloud platform based on the resource demand characteristics of the software application components to generate a dynamic resource pool that matches the preset software update task;

[0008] Based on the component dependency path, starting a software application component update process in the dynamic resource pool, wherein the software application component update process performs an application version replacement operation according to the component dependency path;

[0009] When a service exception is triggered by the application version replacement operation, the service traffic of the abnormal software application component that has the exception is switched to the backup resource node;

[0010] Updating the abnormal software application component at the backup resource node to generate an updated software application component;

[0011] The updated software application components are re-connected to the dynamic resource pool until the versions of the various software application components recorded in the software deployment topology map are replaced, thereby completing the software development and application update process.

[0012] Optionally, the dependency topology relationships between software application components are analyzed to generate a software deployment topology map containing component dependency paths, including:

[0013] Acquiring interface call feature information between software application components, wherein the interface call feature information includes a call direction flag and a call frequency parameter;

[0014] Constructing an initial dependency graph according to the call direction mark, wherein the nodes of the initial dependency graph represent software application components, and the edges of the initial dependency graph represent component connection paths;

[0015] Extracting the running state characteristic parameters of the software application components, and assigning weights to the component connection paths based on the association between the call frequency parameters and the running state characteristic parameters to generate a weighted dependency graph;

[0016] Traversing the incoming edge weight value of each node in the weighted dependency graph, and determining the update priority order of the software application components according to the descending order of the incoming edge weight values;

[0017] Mapping the update priority order with the component connection path to generate a component dependency path;

[0018] A software deployment topology map is generated according to the component dependency path and the topological structure of the weighted dependency graph.

[0019] Optionally, based on the resource demand characteristics of the software application component, target computing resources are preheated on the cloud platform to generate a dynamic resource pool that matches the preset software update task, including:

[0020] Acquiring historical operation data of the software application component, wherein the historical operation data includes resource demand parameters;

[0021] Determining the resource allocation priority of each software application component based on the matching degree between the resource demand parameters and the current cloud platform resource status;

[0022] Generate a resource allocation strategy based on the resource allocation priority and the component dependency path in the software deployment topology map;

[0023] Creating a virtual resource container corresponding to the resource allocation strategy in the cloud platform, and loading the runtime environment with the virtual resource container according to preset preheating parameters to generate a set of virtual resource containers in a ready state;

[0024] monitoring the resource loading progress of the virtual resource container set in the standby state in real time, and activating the virtual resource container set in the standby state to generate a dynamic resource pool when it is monitored that the pre-dependent component of the first software application component to be updated in the component dependency path has completed the update and the virtual resource container corresponding to the component dependency path has reached a resource-ready state;

[0025] According to the execution state of the update process of the software application component, the resource configuration ratio of the virtual resource container in the dynamic resource pool is adjusted to generate a dynamic resource pool that matches the preset software update task.

[0026] Optionally, based on the component dependency path, starting a software application component update process in the dynamic resource pool, wherein the software application component update process performs an application version replacement operation according to the component dependency path, including:

[0027] Parsing the component dependency path to generate a set of direct predecessor components of each software application component;

[0028] generating a linear update sequence according to the update completion status of the set of direct predecessor components;

[0029] Allocating resource instances for the linear update sequence in the dynamic resource pool to generate a set of allocated resource instances that matches the resource allocation strategy in the software deployment topology map;

[0030] Performing an atomic version replacement operation on the set of allocated resource instances in the order of the linear update sequence;

[0031] monitoring the execution status of the atomic version replacement operation in real time, and pausing the update process of all subsequent software application components in the linear update sequence that depend on the current software application component when monitoring that the version replacement operation of the current software application component triggers a blocking signal;

[0032] recalculating the linear update sequence according to the blocking signal and the component dependency path to generate an update execution instruction set;

[0033] The update execution instruction set is loaded into the unactivated resource instance in the dynamic resource pool to generate an update process branch path parallel to the linear update sequence until all the software application components complete the version replacement to complete the software application component update process.

[0034] Optionally, when a service exception is triggered by the application version replacement operation, switching the service traffic of the abnormal software application component where the exception occurs to a backup resource node includes:

[0035] monitoring the execution status of the application version replacement operation in real time, and marking the software application component as an abnormal software application component when it is detected that the service response delay of the software application component exceeds a preset threshold or the error rate exceeds a critical value;

[0036] Determining a backup resource node corresponding to the abnormal software application component based on the component dependency path and the preheated resource instances in the dynamic resource pool;

[0037] Sending a preset traffic switching instruction to a traffic distribution unit associated with the abnormal software application component to generate traffic redirection configuration information;

[0038] Isolating, according to the traffic redirection configuration information, a communication link between the abnormal software application component and a currently running resource instance in the dynamic resource pool, and generating a component isolation state identifier;

[0039] Based on the component isolation status identifier and the traffic redirection configuration information, triggering the backup resource node to load the target version of the software application component and generate a backup component instance running on the backup resource node;

[0040] Connect the backup component instance to the dynamic resource pool, and synchronously update the component dependency path in the software deployment topology map according to the traffic redirection configuration information until all service traffic is switched to the backup component instance, so as to complete the switching of the service traffic of the abnormal software application component that has an abnormality to the backup resource node.

[0041] Optionally, updating the abnormal software application component at the backup resource node to generate an updated software application component includes:

[0042] Obtaining a target version update package corresponding to the abnormal software application component;

[0043] Creating an operating environment on the backup resource node according to the resource allocation policy in the dynamic resource pool and generating an environment verification result;

[0044] Based on the environment verification result, the target version update package is loaded into the storage area of ​​the backup resource node, and a version update ready mark is generated;

[0045] According to the version update ready mark, executing the operation of terminating the old version process and starting the new version process replacement at the backup resource node, and generating a replacement operation completion status;

[0046] monitoring the operation indicators in the completion state of the replacement operation in real time, and generating an update completion confirmation signal when it is monitored that the resource occupancy rate and interface response delay of the operation indicators meet the preset conditions;

[0047] According to the update completion confirmation signal, the software application component running in the backup resource node is marked as an updated software application component.

[0048] Optionally, the updated software application components are re-connected to the dynamic resource pool until the versions of the software application components recorded in the software deployment topology map are replaced, thereby completing the software development application update process, including:

[0049] Obtaining the running status parameters of the updated software application component to generate a component access ready signal;

[0050] Sending a component access instruction to a corresponding resource instance in the dynamic resource pool according to the component access ready signal and the component dependency path to generate resource instance binding information;

[0051] Based on the resource instance binding information, switching the service traffic of the updated software application component from the backup resource node to the target resource instance in the dynamic resource pool, and generating a traffic switching completion mark;

[0052] monitoring the resource occupancy rate fluctuation range and the interface call success rate of the target resource instance in real time, and generating a version replacement confirmation signal when it is detected that the resource occupancy rate fluctuation range is within a preset tolerance interval and the interface call success rate meets the standard;

[0053] updating the version status identifier of the software application component according to the version replacement confirmation signal, and generating a component status update record;

[0054] Traverse the version status identifiers of the software application components. When there are software application components with unfinished version replacements, trigger the software application component update process according to the component status update record and component dependency path and iterate until all the version status identifiers are marked as completed, thereby completing the software development application update processing.

[0055] In a second aspect, the present invention provides a cloud computing-based software development and application update processing system, comprising:

[0056] An analysis module is used to analyze the dependency topology relationships between software application components and generate a software deployment topology map containing component dependency paths;

[0057] A preheating module, configured to preheat target computing resources on the cloud platform according to the resource demand characteristics of the software application component, and generate a dynamic resource pool that matches the preset software update task;

[0058] a startup module, configured to start a software application component update process in the dynamic resource pool based on the component dependency path, wherein the software application component update process performs an application version replacement operation according to the component dependency path;

[0059] a switching module, configured to switch the service traffic of the abnormal software application component that has experienced the abnormality to a backup resource node when a service abnormality is triggered by the application version replacement operation;

[0060] An updating module, configured to update the abnormal software application component at the backup resource node to generate an updated software application component;

[0061] The access module is used to re-access the updated software application components to the dynamic resource pool until the versions of the various software application components recorded in the software deployment topology map are replaced, thereby completing the software development application update process.

[0062] In a third aspect, the present invention provides a computing device comprising a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute a cloud computing-based software development application update processing method as described in any one of the first aspects.

[0063] In a fourth aspect, the present invention provides a computer storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement a cloud computing-based software development application update processing method as described in any one of the first aspects.

[0064] The present invention generates a deployment topology map by analyzing the dependency topology relationship between software components and builds a dynamic resource pool by preheating cloud platform resources, thereby achieving a precise match between update tasks and computing resources. By starting the update process in an orderly manner according to the dependency path and automatically switching to the backup node for fault tolerance in the event of an anomaly, the consistency of version replacement is guaranteed and the risk of service interruption is significantly reduced. Ultimately, through the dynamic migration of abnormal components and the replacement of full topology component versions, an efficient rolling update effect is achieved, solving the problems of low deployment efficiency and insufficient stability caused by dependency confusion in software updates in traditional cloud environments.

[0065] Furthermore, through dynamic analysis of interface call characteristics and operational status parameters, quantitative indicators such as call direction and frequency are converted into weighted values ​​for dependency paths, enabling the topology map to accurately reflect the actual coupling strength between components. Determining update priorities based on descending input edge weights not only avoids concurrent update conflicts for strongly dependent components, but also reduces service jitter during the update process through topological optimization of the weighted dependency graph. The component dependency paths and priority order generated by this method provide data support for dynamic resource pool allocation and process startup, ultimately improving the controllability and success rate of complex software system updates.

[0066] These and other aspects of the present invention will become more apparent from the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0068] Figure 1 A flowchart of a cloud computing-based software development application update processing method provided by an embodiment of the present invention;

[0069] Figure 2 A schematic diagram of the structure of a cloud computing-based software development and application update processing system provided by an embodiment of the present invention;

[0070] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0071] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0072] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., and do not represent the order of precedence, nor do they limit "first" and "second" to be different types.

[0073] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0074] Figure 1 The present invention provides a flowchart of a method for updating software development applications based on cloud computing, such as Figure 1 As shown, the method includes:

[0075] First, the characteristics and real-time running status are called to upgrade the topology map from a static structure to a dynamic model that reflects the actual coupling strength, solving the dependency misjudgment problem; secondly, based on the path weights and resource demand characteristics of the topology map, computing resources are pre-allocated and preheated on the cloud platform to form a dynamic resource pool that strongly matches the update task; then, the priority is sorted by the dependency path weights to trigger the rolling update, and when a single component anomaly is detected, its traffic is automatically switched to the preheated backup node to complete the isolated update, avoiding the full rollback operation of the traditional solution; finally, high-reliability, low-latency incremental updates are achieved under the microservice architecture, breaking through the bottlenecks of low resource utilization and high fault tolerance costs in the existing technology. Based on this, the present invention provides a software development application update processing method based on cloud computing, such as Figure 1 ,include:

[0076] Step 101: Analyze the dependency topology relationship between software application components and generate a software deployment topology map including component dependency paths.

[0077] In this step, the dependency topology relationship refers to the call dependency structure between software application components; the component dependency path refers to the call chain from the starting component to the target component in the dependency topology relationship, which is extracted by the topological sorting algorithm; the software deployment topology graph refers to the component deployment relationship described in the form of a graph structure.

[0078] In an embodiment of the present invention, the dependency topology relationship is first analyzed by calling the interface log and runtime monitoring data of the microservice component; secondly, an initial dependency graph is constructed based on a graph theory algorithm; then, dynamic weights are assigned to the edges to generate a weighted dependency graph that reflects the actual dependency strength; finally, the key dependency paths are extracted through a topological sorting algorithm to form a software deployment topology map.

[0079] Step 102: Preheat the target computing resources on the cloud platform according to the resource demand characteristics of the software application component to generate a dynamic resource pool that matches the preset software update task.

[0080] In this step, resource demand characteristics refer to the computing resource specifications required for the operation of software application components; preheating operations refer to pre-allocating computing resources on the cloud platform and loading the operating environment; dynamic resource pool refers to the collection of computing resources that are elastically allocated according to the requirements of update tasks.

[0081] In an embodiment of the present invention, the resource demand characteristics of each software application component in the software deployment topology map are first analyzed; secondly, a virtual machine or container instance is pre-applied according to the demand characteristics and the target version of the operating environment image is loaded; then, memory is pre-allocated and network bandwidth is reserved for the computing node; finally, the pre-warmed resources are logically grouped according to component dependencies to generate the dynamic resource pool.

[0082] Step 103: Based on the component dependency path, start a software application component update process in the dynamic resource pool, wherein the software application component update process performs an application version replacement operation according to the component dependency path.

[0083] In this step, the software application component update process refers to the version replacement process executed in the dependency path sequence; the application version replacement operation refers to the process of upgrading the software application component from the old version to the new version.

[0084] In an embodiment of the present invention, the software application component update priority is first determined, and the software application component update process is started in sequence in the dynamic resource pool; then the new instance is connected to the service registration center to complete the application version replacement operation; finally, after verifying the health status of the new version component, the traffic is gradually switched to the new instance.

[0085] Step 104: When a service exception is triggered by the application version replacement operation, the service traffic of the abnormal software application component that has the exception is switched to the backup resource node.

[0086] In this step, abnormal software application components refer to components that fail during the version replacement process; service traffic refers to the data flow of user requests or calls between components; backup resource nodes refer to pre-reserved computing nodes used to take over traffic and perform isolated repairs in the event of an anomaly.

[0087] In an embodiment of the present invention, the service anomalies of each software application component are first monitored during the application version replacement operation. When an abnormal software application component is detected, its service traffic is immediately switched to a pre-deployed backup resource node; then, after the traffic switching is completed, an alarm is automatically triggered and the abnormal context is recorded; finally, it is ensured that the caller of the abnormal component is automatically redirected to the backup node to maintain service continuity.

[0088] Step 105: updating the abnormal software application component at the backup resource node to generate an updated software application component.

[0089] In this step, the update operation refers to the specific action of repairing or rolling back the version of the abnormal software application component, including image replacement and configuration update; the updated software application component refers to the component instance that has completed the version repair or upgrade and is re-connected to the service grid after passing the health check.

[0090] In an embodiment of the present invention, first, an updated image of the abnormal software application component is loaded on the backup resource node and the operating environment is reinitialized; secondly, an incremental update strategy is adopted to replace the faulty module of the abnormal component; then, the functional integrity of the updated software application component is verified through an automated testing framework to ensure its dependency compatibility with other components; finally, the repaired component is marked as available.

[0091] Step 106: Re-adding the updated software application components to the dynamic resource pool until all software application components recorded in the software deployment topology map have completed version replacement, thereby completing the software development application update process.

[0092] In this step, the reconnection operation refers to the process of re-registering the repaired component to the service discovery system and gradually restoring its traffic; the version replacement operation refers to the final state process in which all components in the software deployment topology map complete the version upgrade in sequence.

[0093] In an embodiment of the present invention, the updated software application component is first re-registered with the service discovery system so that it can be re-connected to the dynamic resource pool; secondly, the traffic of the backup resource node is gradually migrated back to the repaired component while continuously monitoring the stability; then the version replacement operation is repeated until all software application components in the software deployment topology map are updated; finally, the temporarily occupied backup resource nodes are released, and an update completion report is generated, recording the version change log of each component.

[0094] For example, first, the interface call logs between components are collected, the dependency topology relationship is analyzed, and a weighted software deployment topology map is generated based on the call frequency and response time; secondly, according to the resource demand characteristics in the map, matching virtual machine instances are applied for on the cloud platform, memory preloading and network bandwidth reservation are completed, and a dynamic resource pool is formed; then, the update process is started according to the component dependency path in the topology map, the old version instances are isolated and the new version is deployed in turn, and the service status is monitored at the same time. When an abnormality is detected in an order service component, its traffic is immediately switched to the backup resource node and the incremental update of the component is completed on the backup node; finally, the repaired order service is reconnected to the dynamic resource pool, and the version replacement of the remaining components continues until all components are upgraded, the temporary backup resources are released, and an update report is output.

[0095] The embodiment of the present invention ensures that the update sequence matches the actual coupling strength by dynamically analyzing the component dependency topology and generating a weighted deployment graph. It also adopts an abnormal component isolation and backup node rapid repair mechanism to avoid the full rollback problem of traditional solutions. It achieves highly reliable and low-latency incremental rolling updates under the microservice architecture, and improves the automation level of cloud environment software updates.

[0096] To address the issue of complex microservice component dependencies making it difficult to determine the update order, this step provides a method for generating a software deployment topology map based on interface call characteristics and operating status parameters. The present invention provides a specific embodiment, step 101, analyzing the dependency topology relationships between software application components and generating a software deployment topology map containing component dependency paths, specifically comprising the following steps:

[0097] Step 111: Acquire interface call feature information between software application components, wherein the interface call feature information includes a call direction tag and a call frequency parameter.

[0098] In this step, the interface call characteristic information refers to the dynamic characteristic data of the interface calls between software application components; the call frequency parameter refers to the statistical value of the number of interface calls per unit time.

[0099] In an embodiment of the present invention, first, interface call feature information between software application components is obtained through microservice components and a distributed tracing system; secondly, the collected raw data is cleaned and normalized; finally, the processed interface call feature information is stored in an analysis database.

[0100] Step 112: construct an initial dependency graph according to the call direction mark, wherein the nodes of the initial dependency graph represent software application components, and the edges of the initial dependency graph represent component connection paths.

[0101] In this step, the construction operation refers to the process of generating the initial dependency graph through a graph theory algorithm based on the call direction mark and component relationship data, including node creation and edge connection; the initial dependency graph refers to a directed graph model with software application components as nodes and call relationships as edges.

[0102] In an embodiment of the present invention, the interface call feature information is first parsed to clarify the calling relationship between each software application component; secondly, an initial dependency graph is constructed based on a directed graph model in graph theory and verified; finally, the initial dependency graph is converted into a storage format of an adjacency list or an adjacency matrix.

[0103] Step 113: extracting the running state characteristic parameters of the software application component, and assigning weights to the component connection paths based on the association between the call frequency parameters and the running state characteristic parameters to generate a weighted dependency graph.

[0104] In this step, the weight assignment operation refers to the calculation process of assigning weight values ​​to the edges in the dependency graph based on the association analysis of the call frequency parameters and the operating status characteristic parameters; the weighted dependency graph refers to a weighted directed graph generated by the weight assignment operation on the basis of the initial dependency graph.

[0105] In an embodiment of the present invention, first, the operating status characteristic parameters of the software application components are extracted from the performance monitoring system; secondly, the call frequency parameters are correlated with the operating status characteristic parameters, and a weighted algorithm is used to calculate the comprehensive weight value of each component connection path; then, the edges in the initial dependency graph are weighted according to the weight values ​​to generate a weighted dependency graph reflecting the actual dependency strength; finally, the weighted dependency graph is standardized to eliminate the influence of dimensional differences on the weights.

[0106] Step 114: traverse the incoming edge weight value of each node in the weighted dependency graph, and determine the update priority order of the software application components according to the descending order of the incoming edge weight values.

[0107] In this step, the input edge weight value refers to the sum of the weights of all edges pointing to a node in the weighted dependency graph, which is used to measure the dependency importance of the node in the system.

[0108] In an embodiment of the present invention, first, the incoming edge weight value of each node in the weighted dependency graph is traversed, and the total incoming edge weight of each node is counted; secondly, the update priority order of the software application components is determined to ensure that components with high dependency intensity are updated first; then, the update order is dynamically adjusted through the priority queue to adapt to changes in runtime dependencies; finally, an update priority list is generated.

[0109] Step 115: Map the update priority order with the component connection path to generate a component dependency path.

[0110] In this step, the mapping operation refers to the process of associating and matching the update priority order with the component connection path to ensure that the path selection is consistent with the priority.

[0111] In an embodiment of the present invention, the update priority order is first matched with the component connection path in the weighted dependency graph to identify the key dependency links; secondly, the high-priority component connection path is extracted as the component dependency path; then, the component dependency path is subjected to conflict detection and loop elimination to ensure the feasibility and efficiency of the path; finally, the optimized component dependency path is stored in the path library.

[0112] Step 116: Generate a software deployment topology map based on the component dependency path and the topological structure of the weighted dependency graph.

[0113] In this step, the topology structure refers to the connection relationship and layout characteristics of nodes and edges in the weighted dependency graph, which is used to describe the overall architecture and dependency context of the system.

[0114] In an embodiment of the present invention, the topological structure of the component dependency path and the weighted dependency graph is first integrated to identify core components and edge components; secondly, a graph layout algorithm is used to visualize the topological structure and generate an intuitive software deployment topology map; then, the rationality and fault tolerance of the deployment topology are verified through a graph analysis tool; finally, the software deployment topology map is published to the configuration management system.

[0115] The embodiments of the present invention solve the problem of insufficient accuracy of traditional static dependency analysis by dynamically collecting and analyzing interface call feature information; the software deployment topology map provides a scientific basis for the collaborative update of the microservice architecture in the cloud environment, thereby improving update efficiency and system stability.

[0116] To improve cloud platform resource utilization, this step provides a dynamic resource pool preheating and adjustment method based on historical operating data and real-time resource status. The present invention provides a specific embodiment, step 102, preheating target computing resources on the cloud platform based on the resource demand characteristics of the software application component to generate a dynamic resource pool that matches the preset software update task, specifically including the following steps:

[0117] Step 201: Acquire historical operation data of the software application component, wherein the historical operation data includes resource demand parameters.

[0118] In this step, resource requirement parameters refer to the computing resource specifications required for the normal operation of software application components, including the number of CPU cores, memory capacity, storage space, and network bandwidth.

[0119] In an embodiment of the present invention, the historical operation data of software application components is first collected through the cloud platform monitoring system; secondly, the historical data is cleaned and denoised to remove outliers and invalid records; then, a time series analysis method is used to count the peak and average resource usage of each component in different time periods to establish a resource demand model; finally, the processed historical operation data is stored in a resource feature database.

[0120] Step 202: Determine the resource allocation priority of each software application component based on the matching degree between the resource demand parameters and the current cloud platform resource status.

[0121] In this step, the current cloud platform resource status refers to the available resources of the cloud platform at a specific point in time; the resource allocation priority refers to the resource acquisition priority determined for each software application component based on the degree of match between resource requirements and platform status, which is used to guide resource scheduling decisions.

[0122] In an embodiment of the present invention, the current cloud platform resource status is first obtained from the cloud platform resource management interface; secondly, a multi-dimensional matching calculation is performed between the resource demand parameters and the current resource status, and a weighted algorithm is used to evaluate the degree to which the resource requirements of each component are satisfied; then, the software application components are sorted according to the matching scores to determine the resource allocation priority; finally, a resource requirement list with priority is generated.

[0123] Step 203: Generate a resource allocation strategy based on the resource allocation priority and the component dependency path in the software deployment topology map.

[0124] In this step, the resource allocation strategy refers to the resource allocation plan formulated after comprehensively considering the component priorities and dependencies, including specific component resource mapping rules and scheduling timing arrangements.

[0125] In an embodiment of the present invention, the component dependency paths in the software deployment topology map are first parsed to identify the core components on the critical path; secondly, a resource pre-allocation simulation is performed in combination with the resource allocation priority list; then, the dependency path constraints and resource competition relationships are considered to optimize the allocation plan; finally, a resource allocation strategy is generated to ensure that high-priority components and critical path components obtain resources first.

[0126] Step 204: creating a virtual resource container corresponding to the resource allocation strategy in the cloud platform, and loading the virtual resource container into the runtime environment according to preset preheating parameters to generate a set of virtual resource containers in a ready state.

[0127] In this step, the virtual resource container refers to the isolated runtime environment instance created on the cloud platform; the loading operation refers to the entire process of deploying the runtime environment in the virtual resource container, including system image initialization, dependent software installation, and configuration parameter setting; the virtual resource container set refers to a group of virtual resource containers created according to the resource allocation strategy, which are in a ready state waiting to be activated and used.

[0128] In an embodiment of the present invention, a creation request is first sent to the cloud platform resource scheduler; secondly, the specification parameters of the virtual resource container are configured according to the policy requirements; then the runtime environment is loaded; finally, a health check is performed on the set of virtual resource containers in the prepared state to ensure that each container meets the availability standard.

[0129] Step 205: Monitor the resource loading progress of the virtual resource container set in the preparation state in real time. When it is monitored that the pre-dependent component of the first software application component to be updated in the component dependency path has completed the update and the virtual resource container corresponding to the component dependency path has reached the resource-ready state, activate the virtual resource container set in the preparation state to generate a dynamic resource pool.

[0130] In this step, resource loading progress refers to the completion status of various resource configuration tasks during the initialization of the virtual resource container; activation operation refers to the process of transferring the virtual resource container in the preparation state to the running state so that it can officially undertake business loads.

[0131] In an embodiment of the present invention, a monitoring agent is first deployed to collect resource loading progress data of a set of virtual resource containers in real time; secondly, a resource readiness status judgment rule is established; then, update events on the component dependency path are monitored, and a check is triggered when the update of the preceding dependent component is completed; finally, when the dependency conditions and resource conditions are met, an activation operation is executed to transfer the prepared container to the running state, forming a dynamic resource pool.

[0132] Step 206: According to the execution status of the update process of the software application component, the resource configuration ratio of the virtual resource containers in the dynamic resource pool is adjusted to generate a dynamic resource pool that matches the preset software update task.

[0133] In this step, the execution status of the update process refers to the real-time status information of the component during the update process; the resource allocation ratio refers to the allocation ratio of various resources in the dynamic resource pool.

[0134] In an embodiment of the present invention, the execution status information of the software application component update process is first obtained; secondly, the deviation between the current resource usage and the expected demand is analyzed to identify resource bottlenecks; then, an elastic scaling algorithm is used to dynamically adjust the resource allocation ratio of the virtual resource container; finally, the composition structure of the dynamic resource pool is optimized based on the adjustment results to ensure that it always matches the requirements of the software update task.

[0135] The embodiment of the present invention optimizes resource utilization efficiency through priority and path-dependent resource allocation strategies; the dynamic adjustment function ensures that the resource pool always keeps pace with actual demand, solves the problems of resource competition and performance fluctuations during software updates in a cloud environment, and improves the stability and efficiency of the update process.

[0136] To resolve dependency conflicts and blocking issues during distributed system component updates, this step provides an atomic version replacement method based on a combination of linear sequences and parallel branches. The present invention provides a specific embodiment, in which step 103, based on the component dependency path, a software application component update process is initiated in the dynamic resource pool. The software application component update process performs application version replacement operations according to the component dependency path, specifically including the following steps:

[0137] Step 301: Parse the component dependency path and generate a set of direct predecessor components of each software application component.

[0138] In this step, the parsing operation refers to the process of performing structured analysis on the component dependency path, including dependency extraction, topological sorting, and data structure conversion; the direct predecessor component set refers to the set consisting of all upstream components that directly call the current component in the component dependency path.

[0139] In an embodiment of the present invention, first, the component dependency path is parsed by a topological graph traversal algorithm to identify the upstream dependency of each software application component; secondly, a depth-first search method is used to collect all directly called predecessor components of each component to form a set of direct predecessor components; then, the components in the set are deduplicated and topologically sorted; finally, the parsing results are stored in a dependency database.

[0140] Step 302: Generate a linear update sequence according to the update completion status of the set of direct predecessor components.

[0141] In this step, the update completion status refers to the execution result identifier of the software application component version replacement operation; the linear update sequence refers to the version replacement execution order list determined according to the component dependency and predecessor status, ensuring that each component will not be processed until all its predecessor components are updated.

[0142] In an embodiment of the present invention, first, the update completion status mark of each component in the direct predecessor component set is obtained from the version management system; secondly, the predecessor components that have completed the update are screened and a dependency constraint relationship matrix is ​​established; then, combined with the dependency constraint conditions, a linear update sequence that meets all predecessor conditions is generated; finally, the sequence is conflict detected and optimized to ensure the rationality and efficiency of the update order.

[0143] Step 303: Allocate resource instances for the linear update sequence in the dynamic resource pool, and generate a set of allocated resource instances that matches the resource allocation strategy in the software deployment topology map.

[0144] In this step, the resource instance allocation operation refers to the process of binding the computing resources in the dynamic resource pool with specific software application components, including resource specification matching, instance allocation, and binding relationship registration; the allocated resource instance set refers to the resource instance combination that completes component binding according to the resource allocation strategy.

[0145] In an embodiment of the present invention, the resource requirement specifications of each software application component in the linear update sequence are first parsed; secondly, the available resource list of the dynamic resource pool is queried to match resource instances that meet the specification requirements; then, the resource instance allocation operation is executed according to the resource allocation strategy to establish a binding relationship between the component and the resource instance; finally, the health status of the allocated resource instance set is verified.

[0146] Step 304: Perform an atomic version replacement operation on the set of allocated resource instances in the order of the linear update sequence.

[0147] In this step, the atomic version replacement operation refers to an indivisible complete update transaction, which either completely and successfully completes the new version deployment or completely rolls back to keep the old version running, ensuring the consistency of the system state.

[0148] In an embodiment of the present invention, first, target components are selected one by one starting from the head of the sequence in the order of a linear update sequence; secondly, the resource instance corresponding to the component is located in the set of allocated resource instances, and an environment isolation operation is performed; then, an atomic transaction mechanism is used to complete the version replacement operation; finally, the version replacement result is verified to ensure that the operation is completely successful or completely rolled back to maintain system consistency.

[0149] Step 305: Monitor the execution status of the atomic version replacement operation in real time. When it is detected that the version replacement operation of the current software application component triggers a blocking signal, suspend the update process of all subsequent software application components in the linear update sequence that depend on the current software application component.

[0150] In this step, the blocking signal refers to the abnormal event identifier detected during the version replacement process that hinders the normal execution of the operation; the update process of the subsequent software application components refers to the version replacement processing flow of all components that follow the current component in the linear update sequence and depend on the current component.

[0151] In an embodiment of the present invention, first, a distributed monitoring probe is deployed to collect the execution status data of the atomic version replacement operation; secondly, a blocking signal detection rule is established to trigger a signal when an abnormal situation occurs; then, the dependency impact range of the current software application component is analyzed to determine the list of subsequent software application components that need to be paused; finally, a pause instruction is sent to the update coordinator to freeze the update process of the relevant components.

[0152] Step 306: recalculate the linear update sequence according to the blocking signal and the component dependency path to generate an update execution instruction set.

[0153] In this step, the recalculation operation refers to the dependency reconstruction processing of the remaining update tasks after the blocking signal appears, including dependency subgraph extraction, new sequence generation and resource reallocation; the update execution instruction set refers to the set of operation commands generated after recalculation.

[0154] In an embodiment of the present invention, the cause and impact scope of the blocking signal are first analyzed to extract key parameters; secondly, the component dependency path data is reloaded and the component nodes that have been successfully updated are marked; then, the remaining components are recalculated to generate a new dependency subgraph; finally, an update execution instruction set is constructed based on the subgraph structure to clarify the execution order and resource requirements of subsequent updates.

[0155] Step 307: Load the update execution instruction set to the unactivated resource instance in the dynamic resource pool, generate an update process branch path parallel to the linear update sequence, until all the software application components complete the version replacement, so as to complete the software application component update process.

[0156] In this step, unenabled resource instances refer to available computing resources that have been created in the dynamic resource pool but have not yet been allocated to any component; update process branch paths refer to parallel update execution routes created to solve blocking problems, working in conjunction with the main update sequence.

[0157] In an embodiment of the present invention, first, idle resource instances in the dynamic resource pool are screened to verify their specification compliance; secondly, the update execution instruction set is decomposed into task units that can be executed in parallel, and a task-resource mapping relationship is established; then, the update process branch path is started on the backup resource instance and the version replacement operation is executed in parallel until all software application components complete the version replacement.

[0158] The embodiment of the present invention generates an optimized update sequence by accurately parsing component dependencies, ensuring that the update order complies with system architecture constraints; dynamic resource allocation and branch path mechanism solve the dependency management problem in complex distributed system updates and realize a highly efficient automated update process.

[0159] To reduce the risk of service interruption during the version update process, this step provides a method for rapidly switching abnormal components based on real-time monitoring and traffic redirection. The present invention provides a specific embodiment, step 104, when the service abnormality triggered by the application version replacement operation occurs, switching the service traffic of the abnormal software application component to a backup resource node, specifically including the following steps:

[0160] Step 401: monitor the execution status of the application version replacement operation in real time, and when it is monitored that the service response delay of the software application component exceeds a preset threshold or the error rate exceeds a critical value, mark the software application component as an abnormal software application component.

[0161] In this step, service response latency refers to the time interval from when the client sends a request to when it receives a response.

[0162] In an embodiment of the present invention, first, the performance indicator data of the software application components are collected in real time through a distributed monitoring system; secondly, the collected data is compared and analyzed with the preset threshold value. When the delay exceeds 300ms or the error rate exceeds 5%, the abnormal judgment mechanism is triggered; then the abnormal component is marked, and the time when the abnormality occurred and the specific manifestation characteristics are recorded; finally, the abnormal information is pushed to the alarm center.

[0163] Step 402: Determine the backup resource node corresponding to the abnormal software application component based on the component dependency path and the preheated resource instances in the dynamic resource pool.

[0164] In this step, the preheated resource instance refers to a computing resource unit that has completed environment initialization and loaded the necessary runtime.

[0165] In an embodiment of the present invention, the component dependency path database is first queried to obtain the upstream and downstream dependency relationships of the abnormal software application components; secondly, the list of preheated resource instances in the dynamic resource pool is scanned to screen candidate nodes that meet the specification requirements; then, the optimal backup resource node is selected based on the proximity principle and resource load conditions; finally, a backup plan is generated and submitted to the resource scheduling system.

[0166] Step 403: Send a preset traffic switching instruction to the traffic distribution unit associated with the abnormal software application component to generate traffic redirection configuration information.

[0167] In this step, the traffic distribution unit refers to the network component responsible for request routing and load balancing; the traffic redirection configuration information refers to the policy set that controls the request flow path.

[0168] In an embodiment of the present invention, the traffic distribution unit information associated with the abnormal software application component is first obtained from the service registration center; then a traffic switching instruction is constructed and a configuration update request is sent to the traffic distribution unit; finally, the traffic redirection configuration information returned by the verification traffic distribution unit is received.

[0169] Step 404: Isolate the communication link between the abnormal software application component and the currently running resource instance in the dynamic resource pool according to the traffic redirection configuration information, and generate a component isolation status identifier.

[0170] In this step, the communication link refers to the network connection channel established between business components.

[0171] In an embodiment of the present invention, the traffic redirection configuration information is first parsed to extract a list of communication links that need to be isolated; secondly, the interface of the network control plane is called to set firewall rules and routing policies; then, the isolation effect of the communication link is verified to ensure that the abnormal component no longer receives new requests; finally, a component isolation status identifier is generated and updated to the configuration management system.

[0172] Step 405: Based on the component isolation status identifier and the traffic redirection configuration information, trigger the backup resource node to load the target version of the software application component, and generate a backup component instance running on the backup resource node.

[0173] In this step, the loading operation refers to the entire process of deploying and starting software components on computing resources, including steps such as environment preparation, binary deployment, and service registration; the backup component instance refers to the alternative service instance created on the backup resource node to take over the business traffic of the abnormal component.

[0174] In an embodiment of the present invention, the storage location of the target version of the software package is first obtained; secondly, the environment initialization operation is performed on the backup resource node; then, the target version image is loaded to start the service process and complete the creation of the backup component instance; finally, a health check is performed on the new instance to confirm that it meets the service standards.

[0175] Step 406: Connect the backup component instance to the dynamic resource pool, and synchronously update the component dependency path in the software deployment topology map according to the traffic redirection configuration information until all service traffic is switched to the backup component instance, so as to complete the switching of the service traffic of the abnormal software application component that has an abnormality to the backup resource node.

[0176] In this step, the synchronous update operation refers to the process of maintaining the consistency of configuration information of each component in the distributed system.

[0177] In an embodiment of the present invention, the backup component instance is first registered with the service discovery system to complete the access to the dynamic resource pool; secondly, the load balancing policy is updated according to the traffic redirection configuration information, and the traffic is gradually switched; then, the component dependency path information in the software deployment topology map is synchronously modified; finally, the progress of traffic switching is monitored, and when all traffic migration is completed, the residual resources of the abnormal component are cleaned up.

[0178] The embodiments of the present invention achieve rapid discovery and precise positioning of abnormal components through real-time monitoring and intelligent analysis; a preheated backup resource mechanism ensures the timeliness of fault switching; fine-grained flow control technology minimizes the impact of service interruptions; and automated isolation and recovery processes significantly improve system availability, building a highly reliable cloud-native application update guarantee system and solving the failure problems in traditional solutions.

[0179] To improve the success rate of abnormal component updates, this step provides a backup node version update method that includes environmental verification and operational indicator monitoring. The present invention provides a specific embodiment, step 105, in which the abnormal software application component is updated at the backup resource node to generate an updated software application component, specifically including the following steps:

[0180] Step 501: Obtain the target version update package corresponding to the abnormal software application component.

[0181] In this step, the target version update package refers to an archive package containing all deployment files of a specific version of the software component, including executable files, configuration templates, and dependency declarations, which is generated through the version control system.

[0182] In an embodiment of the present invention, the target version information of the abnormal software application component is first queried from the version management system; secondly, the corresponding target version update package is downloaded from the product warehouse according to the version identifier; then the update package is integrity checked to verify the digital signature and hash value; finally, the verified update package is temporarily stored in the local cache in preparation for subsequent deployment.

[0183] Step 502: Create a running environment on the backup resource node according to the resource allocation policy in the dynamic resource pool, and generate an environment verification result.

[0184] In this step, the creation operation refers to the entire process of initializing the runtime environment on the computing node; the environment verification result refers to the output report of the functional verification of the newly created environment.

[0185] In an embodiment of the present invention, the resource allocation strategy is first parsed to obtain the specification requirements of the backup resource node; secondly, an isolated runtime environment is created on the backup resource node, basic dependency components are installed, and environment variables and permission settings are verified; finally, an environmental health check is performed to generate an environment verification result.

[0186] Step 503: Based on the environment verification result, the target version update package is loaded into the storage area of ​​the backup resource node, and a version update ready mark is generated.

[0187] In this step, the loading operation refers to the complete process of deploying the software package to the target environment, including file transfer, decompression, and permission configuration, to ensure that the deployment results are consistent with expectations.

[0188] In an embodiment of the present invention, first, the mount point and available space of the storage area are determined based on the environment verification results; secondly, the target version update package is unzipped to the specified directory of the backup resource node, retaining the original file permissions; then, runtime configuration parameters are injected to adapt to the current environment characteristics; finally, after all files are in place, a version update ready marker file is created to record the deployment timestamp and version fingerprint.

[0189] Step 504: According to the version update ready mark, terminate the old version process and start the new version process replacement operation at the backup resource node, and generate a replacement operation completion status.

[0190] In this step, the replacement operation is completed and the status record version switching process detailed results report.

[0191] In an embodiment of the present invention, the resource usage of the old version process is first queried; secondly, a termination signal is sent and the old version process is left to wait for completion of the current request processing; then the new version process is started from the path indicated by the version update ready mark, the process startup log is monitored, and a replacement operation completion status report is generated.

[0192] Step 505: monitor the operation indicators in the replacement operation completion state in real time, and generate an update completion confirmation signal when it is monitored that the resource occupancy rate and interface response delay of the operation indicators meet the preset conditions.

[0193] In this step, resource utilization refers to the proportion of computing resources consumed by the service instance during operation; interface response latency refers to the processing time from the service's external API receiving a request to returning a response.

[0194] In an embodiment of the present invention, a performance collection agent is first deployed to monitor the resource occupancy and interface response delay of the new version process; secondly, a sliding time window is established to calculate the moving average of key indicators; then the calculation results are compared with preset conditions, including CPU occupancy not exceeding 70% and P99 delay being less than 200ms; finally, when all indicators meet the standards for more than 5 minutes, an update completion confirmation signal is triggered.

[0195] Step 506: According to the update completion confirmation signal, mark the software application component running in the backup resource node as an updated software application component.

[0196] In this step, the marking operation refers to the metadata update action in the management system, which is used to identify the component status change.

[0197] In an embodiment of the present invention, the version information and performance data in the update completion confirmation signal are first parsed; secondly, the component status in the backup resource node is updated to healthy in the service registration center; then, the component is marked as an updated software application component in the configuration management system, and the update time is recorded; finally, the alarm rules of the monitoring system are synchronously updated to adapt to the new version characteristics.

[0198] The embodiment of the present invention ensures the accuracy of version deployment through standardized update package management and environment verification processes; automated status marking and synchronous updates improve operation and maintenance efficiency, builds a safe and reliable cloud-native application update system, and solves problems such as version inconsistency and difficulty in rollback in traditional update methods.

[0199] To ensure smooth access to updated components and overall system consistency, this step provides a method for confirming the completion of version replacement based on status monitoring and iterative execution. The present invention provides a specific embodiment, step 106, reconnecting the updated software application components to the dynamic resource pool until all software application components recorded in the software deployment topology map have completed version replacement, thereby completing the software development and application update process. Specifically, the method includes the following steps:

[0200] Step 601: Acquire the running status parameters of the updated software application component to generate a component access ready signal.

[0201] In this step, the operating status parameter refers to a set of indicators that reflect the real-time operating performance of the software component; the component access readiness signal refers to a digital notification confirming that the component has met the accessibility standards.

[0202] In an embodiment of the present invention, the operating status parameters of the updated software application components are first collected and normalized to calculate a comprehensive health score; the score is then compared with a preset threshold, and a component access readiness signal is generated when all key indicators continue to meet the standards for more than a stable period; finally, the signal is pushed to the resource scheduling center to trigger the subsequent access process.

[0203] Step 602: Send a component access instruction to a corresponding resource instance in the dynamic resource pool according to the component access ready signal and the component dependency path to generate resource instance binding information.

[0204] In this step, the component access instruction refers to the operation command for controlling the component to join the resource pool; the resource instance binding information refers to the metadata that records the association relationship between the component and the specific resource instance.

[0205] In an embodiment of the present invention, the component access ready signal is first parsed to determine the position of the component in the dynamic resource pool, and a component access instruction is sent to the resource management service; then the binding confirmation of the resource instance is received, the resource instance binding information is generated and the service registry is updated.

[0206] Step 603: Based on the resource instance binding information, the service traffic of the updated software application component is switched from the backup resource node to the target resource instance in the dynamic resource pool, and a traffic switching completion mark is generated.

[0207] In this step, the target resource instance refers to the computing resource unit specifically allocated to a specific component in the dynamic resource pool; the traffic switching completion mark refers to the status mark that the service traffic migration process has ended.

[0208] In an embodiment of the present invention, the forwarding rules of the load balancer are first configured according to the resource instance binding information; secondly, the traffic is gradually migrated from the backup resource node to the target resource instance; then, the request processing status of each traffic shard is verified to generate a traffic switching completion mark and trigger the monitoring policy update.

[0209] Step 604: monitor the resource occupancy fluctuation range and interface call success rate of the target resource instance in real time, and generate a version replacement confirmation signal when it is monitored that the resource occupancy fluctuation range is within a preset tolerance interval and the interface call success rate meets the standard.

[0210] In this step, the resource occupancy fluctuation range refers to the variation in computing resource usage within the observation window, reflecting load stability; the interface call success rate refers to the proportion of requests that the service interface correctly processes.

[0211] In an embodiment of the present invention, first, the CPU and memory usage data of the target resource instance are collected, and the fluctuation range within a 5-minute sliding window is calculated; secondly, the success rate index of the interface call is collected, and the distribution of HTTP status codes is counted; then, the fluctuation range is compared with the preset tolerance interval to verify whether the success rate reaches 99.9%; finally, when all monitoring indicators continue to stably meet the standards, a version replacement confirmation signal is generated.

[0212] Step 605: Update the version status identifier of the software application component according to the version replacement confirmation signal, and generate a component status update record.

[0213] In this step, the update operation refers to the management action of changing and maintaining the component version status; the component status update record refers to the audit log that describes the version change process in detail.

[0214] In an embodiment of the present invention, the verification results and performance data in the version replacement confirmation signal are first parsed; secondly, the version status identifier of the software application component is updated in the version management system, and the new version number, deployment time and performance baseline are recorded; then, a component status update record is generated and stored in the audit log; finally, the update event is notified to the relevant dependent components, triggering their configuration hot update.

[0215] Step 606: Traverse the version status identifiers of the software application components. When there are software application components with unfinished version replacement, trigger the software application component update process according to the component status update record and component dependency path and iterate until all the version status identifiers are marked as completed, thereby completing the software development application update processing.

[0216] In this step, the version status identifier refers to the metadata tag that marks the current version and deployment status of the component. It uses a standardized encoding format to support fast query and batch processing.

[0217] In an embodiment of the present invention, first, a list of components that have not been replaced is screened; second, dependency changes of completed components are analyzed based on component status update records; then, the next batch of components to be updated and their priorities are determined according to the component dependency path; finally, the update process is iteratively executed until the version status identifiers of all components in the version management system are marked as completed, and a global update completion report is generated.

[0218] The embodiment of the present invention ensures the reliability of component access through multi-dimensional operating status evaluation; the iterative execution mechanism ensures overall consistency in complex dependency scenarios, builds an efficient cloud-native application update system, and solves the coordination problem in large-scale distributed system upgrades.

[0219] Figure 2 The present invention provides a schematic diagram of a software development and application update processing system based on cloud computing, as shown in FIG. Figure 2 As shown, the system includes:

[0220] Analysis module 21, used to analyze the dependency topology relationship between software application components and generate a software deployment topology map containing component dependency paths;

[0221] A preheating module 22 is used to preheat target computing resources on the cloud platform according to the resource demand characteristics of the software application component, and generate a dynamic resource pool that matches the preset software update task;

[0222] A starting module 23 is configured to start a software application component update process in the dynamic resource pool based on the component dependency path, wherein the software application component update process performs an application version replacement operation according to the component dependency path;

[0223] A switching module 24 is configured to switch the service traffic of the abnormal software application component to a backup resource node when a service abnormality is triggered by the application version replacement operation;

[0224] An updating module 25 is configured to update the abnormal software application component at the backup resource node to generate an updated software application component;

[0225] The access module 26 is used to re-access the updated software application components to the dynamic resource pool until the versions of the various software application components recorded in the software deployment topology map are replaced, thereby completing the software development application update process.

[0226] Figure 2 The software development application update processing system based on cloud computing can execute Figure 1 The implementation principles and technical effects of the cloud computing-based software development and application update processing method described in the illustrated embodiment are not further elaborated. The specific manner in which each module and unit performs operations in the cloud computing-based software development and application update processing system in the above embodiment has been described in detail in the relevant embodiments of the method and will not be elaborated on here.

[0227] In one possible design, Figure 2 The software development application update processing system based on cloud computing of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0228] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0229] The processing component 32 is used to: analyze the dependency topology relationship between software application components and generate a software deployment topology map containing component dependency paths; preheat the target computing resources on the cloud platform according to the resource demand characteristics of the software application components to generate a dynamic resource pool that matches the preset software update task; based on the component dependency path, start the software application component update process in the dynamic resource pool, wherein the software application component update process performs the application version replacement operation according to the component dependency path; when the service exception triggered by the application version replacement operation occurs, the service traffic of the abnormal software application component that has the exception is switched to the backup resource node; update the abnormal software application component at the backup resource node to generate an updated software application component; re-connect the updated software application component to the dynamic resource pool until the versions of the various software application components recorded in the software deployment topology map are replaced to complete the software development application update processing.

[0230] The processing component 32 may include one or more processors to execute computer instructions to perform all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0231] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0232] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0233] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0234] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0235] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0236] The embodiment of the present invention further provides a computer storage medium storing a computer program, which can achieve the above-mentioned Figure 1 The embodiment shown is a method for processing software development and application updates based on cloud computing.

[0237] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0238] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0239] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0240] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A software development application update processing method based on cloud computing, characterized in that: include: Analyze the dependency topology between software application components and generate a software deployment topology map containing component dependency paths; Preheating target computing resources on the cloud platform based on the resource demand characteristics of the software application components to generate a dynamic resource pool that matches the preset software update task; Based on the component dependency path, starting a software application component update process in the dynamic resource pool, wherein the software application component update process performs an application version replacement operation according to the component dependency path; When a service exception is triggered by the application version replacement operation, the service traffic of the abnormal software application component that has the exception is switched to the backup resource node; Updating the abnormal software application component at the backup resource node to generate an updated software application component; The updated software application components are re-connected to the dynamic resource pool until the versions of the various software application components recorded in the software deployment topology map are replaced, thereby completing the software development and application update process.

2. The method according to claim 1, characterized in that Analyze the dependency topology between software application components and generate a software deployment topology map containing component dependency paths, including: Acquiring interface call feature information between software application components, wherein the interface call feature information includes a call direction flag and a call frequency parameter; Constructing an initial dependency graph according to the call direction mark, wherein the nodes of the initial dependency graph represent software application components, and the edges of the initial dependency graph represent component connection paths; Extracting the running state characteristic parameters of the software application components, and assigning weights to the component connection paths based on the association between the call frequency parameters and the running state characteristic parameters to generate a weighted dependency graph; Traversing the incoming edge weight value of each node in the weighted dependency graph, and determining the update priority order of the software application components according to the descending order of the incoming edge weight values; Mapping the update priority order with the component connection path to generate a component dependency path; A software deployment topology map is generated according to the component dependency path and the topological structure of the weighted dependency graph.

3. The method according to claim 1, characterized in that Preheating target computing resources on the cloud platform based on the resource demand characteristics of the software application components to generate a dynamic resource pool that matches the preset software update task, including: Acquiring historical operation data of the software application component, wherein the historical operation data includes resource demand parameters; Determining the resource allocation priority of each software application component based on the matching degree between the resource demand parameters and the current cloud platform resource status; Generate a resource allocation strategy based on the resource allocation priority and the component dependency path in the software deployment topology map; Creating a virtual resource container corresponding to the resource allocation strategy in the cloud platform, and loading the runtime environment with the virtual resource container according to preset preheating parameters to generate a set of virtual resource containers in a ready state; monitoring the resource loading progress of the virtual resource container set in the standby state in real time, and activating the virtual resource container set in the standby state to generate a dynamic resource pool when it is monitored that the pre-dependent component of the first software application component to be updated in the component dependency path has completed the update and the virtual resource container corresponding to the component dependency path has reached a resource-ready state; According to the execution state of the update process of the software application component, the resource configuration ratio of the virtual resource container in the dynamic resource pool is adjusted to generate a dynamic resource pool that matches the preset software update task.

4. The method according to claim 1, wherein Based on the component dependency path, starting a software application component update process in the dynamic resource pool, wherein the software application component update process performs an application version replacement operation according to the component dependency path, including: Parsing the component dependency path to generate a set of direct predecessor components of each software application component; generating a linear update sequence according to the update completion status of the set of direct predecessor components; Allocating resource instances for the linear update sequence in the dynamic resource pool to generate a set of allocated resource instances that matches the resource allocation strategy in the software deployment topology map; Performing an atomic version replacement operation on the set of allocated resource instances in the order of the linear update sequence; monitoring the execution status of the atomic version replacement operation in real time, and pausing the update process of all subsequent software application components in the linear update sequence that depend on the current software application component when monitoring that the version replacement operation of the current software application component triggers a blocking signal; recalculating the linear update sequence according to the blocking signal and the component dependency path to generate an update execution instruction set; The update execution instruction set is loaded into the unactivated resource instance in the dynamic resource pool to generate an update process branch path parallel to the linear update sequence until all the software application components complete the version replacement to complete the software application component update process.

5. The method according to claim 1, wherein When a service exception is triggered by the application version replacement operation, the service traffic of the abnormal software application component that has the exception is switched to the backup resource node, including: monitoring the execution status of the application version replacement operation in real time, and marking the software application component as an abnormal software application component when it is detected that the service response delay of the software application component exceeds a preset threshold or the error rate exceeds a critical value; Determining a backup resource node corresponding to the abnormal software application component based on the component dependency path and the preheated resource instances in the dynamic resource pool; Sending a preset traffic switching instruction to a traffic distribution unit associated with the abnormal software application component to generate traffic redirection configuration information; Isolating, according to the traffic redirection configuration information, a communication link between the abnormal software application component and a currently running resource instance in the dynamic resource pool, and generating a component isolation state identifier; Based on the component isolation status identifier and the traffic redirection configuration information, triggering the backup resource node to load the target version of the software application component and generate a backup component instance running on the backup resource node; Connect the backup component instance to the dynamic resource pool, and synchronously update the component dependency path in the software deployment topology map according to the traffic redirection configuration information until all service traffic is switched to the backup component instance, so as to complete the switching of the service traffic of the abnormal software application component that has an abnormality to the backup resource node.

6. The method according to claim 1, wherein Updating the abnormal software application component at the backup resource node to generate an updated software application component includes: Obtaining a target version update package corresponding to the abnormal software application component; Creating an operating environment on the backup resource node according to the resource allocation policy in the dynamic resource pool and generating an environment verification result; Based on the environment verification result, the target version update package is loaded into the storage area of ​​the backup resource node, and a version update ready mark is generated; According to the version update ready mark, executing the operation of terminating the old version process and starting the new version process replacement at the backup resource node, and generating a replacement operation completion status; monitoring the operation indicators in the completion state of the replacement operation in real time, and generating an update completion confirmation signal when it is monitored that the resource occupancy rate and interface response delay of the operation indicators meet the preset conditions; According to the update completion confirmation signal, the software application component running in the backup resource node is marked as an updated software application component.

7. The method according to claim 1, characterized in that Re-adding the updated software application components to the dynamic resource pool until all software application components recorded in the software deployment topology map have completed version replacement, thereby completing the software development application update process, including: Obtaining the running status parameters of the updated software application component to generate a component access ready signal; Sending a component access instruction to a corresponding resource instance in the dynamic resource pool according to the component access ready signal and the component dependency path to generate resource instance binding information; Based on the resource instance binding information, switching the service traffic of the updated software application component from the backup resource node to the target resource instance in the dynamic resource pool, and generating a traffic switching completion mark; monitoring the resource occupancy rate fluctuation range and the interface call success rate of the target resource instance in real time, and generating a version replacement confirmation signal when it is detected that the resource occupancy rate fluctuation range is within a preset tolerance interval and the interface call success rate meets the standard; updating the version status identifier of the software application component according to the version replacement confirmation signal, and generating a component status update record; Traverse the version status identifiers of the software application components. When there are software application components with unfinished version replacements, trigger the software application component update process according to the component status update record and component dependency path and iterate until all the version status identifiers are marked as completed, thereby completing the software development application update processing.

8. A software development application update processing system based on cloud computing, characterized in that: include: An analysis module is used to analyze the dependency topology relationships between software application components and generate a software deployment topology map containing component dependency paths; A preheating module, configured to preheat target computing resources on the cloud platform according to the resource demand characteristics of the software application component, and generate a dynamic resource pool that matches the preset software update task; a startup module, configured to start a software application component update process in the dynamic resource pool based on the component dependency path, wherein the software application component update process performs an application version replacement operation according to the component dependency path; a switching module, configured to switch the service traffic of the abnormal software application component that has experienced the abnormality to a backup resource node when a service abnormality is triggered by the application version replacement operation; An updating module, configured to update the abnormal software application component at the backup resource node to generate an updated software application component; The access module is used to re-access the updated software application components to the dynamic resource pool until the versions of the various software application components recorded in the software deployment topology map are replaced, thereby completing the software development application update process.

9. A computing device, characterized in that It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a cloud computing-based software development application update processing method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the method for software development and application update processing based on cloud computing as claimed in any one of claims 1 to 7 is implemented.

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