Task Execution API for Pipeline Orchestration
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Solution Overview
Problem
Conventional task execution systems lack a unified interface for task management and control, requiring manual setup and integration, and fail to adapt execution flows based on task execution results.
Innovation Solution
A task execution application programming interface (API) that communicates between a task image and a pipeline execution service, allowing seamless task execution across multiple pipelines by encapsulating executable code and an execution environment, and adapting to specific execution requirements of each pipeline service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional task execution systems use manual setup and integration for each component, then tasks can be executed in pipelines, but the system complexity and time required for deployment increase significantly
Solution Approach 1:
The patent implements a universal task execution interface that can execute multiple types of tasks (shell scripts, Python scripts, Java applications, etc.) through a single standardized API. This interface provides consistent methods for task registration, execution, and result retrieval across different pipeline execution services, eliminating the need for manual customization for each task type and reducing deployment complexity.
Solution Approach 2:
The task execution interface acts as an intermediary layer between diverse pipeline execution services and the task execution logic. It provides a standardized adapter pattern that mediates between different service APIs and the underlying task execution mechanisms, abstracting away service-specific complexities and enabling uniform task deployment across multiple platforms.
2Adaptability or versatility
If conventional systems lack a consistent interface for task management, then different pipeline services can operate independently, but integration effort and time increase
Solution Approach 1:
The task execution interface is designed as a universal adaptation layer that supports multiple pipeline execution services (Jenkins, Travis CI, CircleCI, etc.) through a single standardized API. It provides consistent methods for task registration, execution requests, and result retrieval that work across different services, eliminating the need for separate integration implementations for each service.
Solution Approach 2:
The interface uses configurable parameters and environment variables to adapt to different pipeline execution services without changing the core execution logic. By parameterizing service-specific configurations (API endpoints, authentication credentials, task paths), the system can quickly adapt to new services through configuration changes rather than code modifications, significantly reducing integration time.
3Reliability
If manual customization is required for each task execution, then specific pipeline requirements can be met, but the time and effort for setup increase
Solution Approach 1:
The task execution interface implements self-service capabilities where tasks automatically register themselves with the pipeline execution service upon initialization. The interface automatically discovers available tasks, configures execution parameters, and sets up execution environments without requiring manual intervention. This self-configuration approach maintains execution reliability through automated validation while eliminating time-consuming manual setup procedures.
4Productivity
If conventional systems lack feedback mechanisms on execution results, then simple tasks can run, but pipeline execution flow cannot be dynamically adjusted
Solution Approach 1:
The task execution interface implements comprehensive feedback mechanisms that capture execution results (success/failure status, output data, error messages, execution time) and return them to the pipeline execution service through standardized methods. This feedback enables dynamic pipeline execution flow adjustment, where subsequent tasks can be conditionally executed based on previous task results, improving overall pipeline efficiency and enabling complex workflow orchestration.
Data Source
AI summary
A task execution application programming interface may include a pipeline execution service interface configured to communicate between a task image and a pipeline execution service adapter. The pipeline execution service adapter may be configured to receive, from a pipeline execution service, a request to execute the task image in a pipeline. The request may include arguments. The task image may include executable code and an execution environment. The pipeline execution service interface may be further configured to obtain results by executing the executable code using the arguments in the execution environment. The pipeline execution service adapter may be further configured to provide, to the pipeline execution service, access to the results. The pipeline execution service may control execution of the pipeline using the results. The task execution application programming interface further includes the pipeline execution service adapter for communicating between the pipeline execution service interface and the pipeline execution service.