Dynamic Server Build Rerouting via Step Dependency Analysis
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Solution Overview
Problem
The existing server build process is inefficient as it requires repeating all steps and stages when a failure occurs, leading to increased time and resource wastage, as the entire execution stage is repeated even if only a single step fails, without identifying the specific failed step or its dependencies.
Innovation Solution
The method involves dividing each execution stage into steps, tracking the order of each step, and performing a remedial sequence by pausing at the failed stage, analyzing dependencies, and repeating only the necessary prior steps or the failed step, with the option to retrieve and execute set action codes for failure repair, and generating new action codes based on historical patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire execution stage is repeated when a failure occurs, then the server build process ensures complete re-execution of all steps, but the time required for successful completion increases significantly
Solution Approach 1:
The patent segments the execution stage into discrete, identifiable steps that can be individually tracked and analyzed. When a failure occurs, the system identifies the specific failed step rather than treating the entire stage as a single unit, enabling selective re-execution of only the necessary steps.
Solution Approach 2:
The system changes the parameter of execution granularity from stage-level to step-level. By tracking and analyzing individual steps within an execution stage, the system can dynamically determine the minimum necessary scope for re-execution based on failure analysis, rather than always repeating the entire stage.
2Reliability
If all steps within an execution stage are repeated upon failure, then complete re-execution ensures no missed steps, but resource wastage increases
Solution Approach 1:
The execution stage is divided into discrete steps that can be independently analyzed for dependencies. This segmentation allows the system to identify which specific steps need re-execution based on the failed step and its dependencies, rather than re-executing all steps uniformly.
Solution Approach 2:
The system performs partial action by re-executing only the necessary steps required to resolve the failure, rather than performing excessive action by re-executing all steps in the stage. The remedial sequence is dynamically determined based on dependency analysis of the failed step.
3Device complexity
If the entire execution stage is repeated without identifying the specific failed step, then the process is simpler to implement, but the time and resources required increase unnecessarily
Solution Approach 1:
The system implements feedback by tracking the execution status of each step and analyzing the failure to identify the specific failed step and its dependencies. This feedback mechanism enables the system to dynamically determine the appropriate remedial sequence, balancing complexity with efficiency.
Solution Approach 2:
The system performs self-service by automatically analyzing the failure, identifying the failed step, determining dependencies, and generating the appropriate remedial sequence without requiring external intervention. This automation manages the complexity while achieving time efficiency.
4Productivity
If dependency analysis of prior steps is performed to determine remedial sequence, then fewer steps need to be repeated, but the complexity of the remediation process increases
Solution Approach 1:
The system uses feedback from tracking step execution order and analyzing step dependencies to dynamically generate the remedial sequence. This feedback-driven approach automates the complexity of dependency analysis, making it manageable while achieving improved productivity through selective re-execution.
Solution Approach 2:
The system performs self-service by automatically conducting dependency analysis and determining the minimal necessary remedial sequence without external intervention. This automation handles the computational complexity internally, allowing the system to optimize build completion efficiency without exposing the complexity to users.
Data Source
AI summary
An architecture for a server build is provided. The architecture may include a plurality of execution stages which may be divided into a plurality of steps. Each of the execution stages may be implemented on a server to complete a server build request. The architecture may further include an execution stage selector configured to identify, within a plurality of servers, a server that may have an availability to execute the request. The selector may be further configured to execute the request on the available server and record the order of each of the plurality of steps within each of the plurality of execution stages being executed on the server. In response to a failure, the selector may be configured to pause execution, determine a failed step within the execution stage, analyze the prior executed steps, and determine any prior executed steps that the failed step may depend from.