Stateful CI/CD Pipelines for Skipping Redundant Failed Tasks
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Solution Overview
Problem
Continuous integration and deployment (CI/CD) pipelines are resource-intensive and often result in repetitive task failures due to their stateless nature, leading to wasted computing resources and manual intervention, especially in scenarios like automotive or edge computing where resources are limited.
Innovation Solution
Implementing stateful CI/CD pipelines that store and utilize metadata from previous runs to set flags for tasks, allowing for the reuse of artifacts and outputs, skip redundant tasks, and perform autonomous self-healing to minimize resource consumption and manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional stateless CI/CD pipelines are used, then automation is achieved, but computing resources are wasted due to repetitive task failures and inability to reuse previous results
Solution Approach 1:
The system stores execution history and metadata from previous pipeline runs, then uses this feedback to determine whether to skip redundant tasks. The stateful pipeline service compares current pipeline requirements with historical execution data to make intelligent decisions about task execution, preventing wasted computing resources on repetitive failures.
Solution Approach 2:
The system performs preliminary analysis by storing and retrieving execution history before actually running pipeline tasks. By examining metadata from previous runs in advance, the system can pre-determine which tasks are redundant and should be skipped, avoiding unnecessary computation entirely.
2Reliability
If all pipeline tasks are executed every run, then completeness is ensured, but time is wasted re-executing unchanged tasks
Solution Approach 1:
The system uses feedback from historical execution data to intelligently determine which tasks need re-execution. By comparing current pipeline requirements with stored metadata from previous runs, the system maintains reliability by executing only necessary tasks while skipping redundant ones, thus reducing execution time without compromising completeness.
Solution Approach 2:
The system changes the execution parameter of individual tasks based on historical analysis. Instead of executing all tasks uniformly, the system dynamically adjusts which tasks are executed versus skipped based on metadata comparison, allowing selective optimization of pipeline execution time while maintaining necessary task completion.
3Extent of automation
If pipeline failures are ignored in automated workflows, then automation is maintained, but resource waste increases due to repeated unsuccessful runs
Solution Approach 1:
The system implements feedback loops that track pipeline execution history and failure patterns. When failures are detected, the system uses stored metadata to analyze whether the failure is due to unchanged code or other factors, then makes intelligent decisions about whether to retry or skip the pipeline, preventing automated repetition of futile execution attempts.
Solution Approach 2:
The stateful pipeline service performs self-service by automatically analyzing its own execution history and making decisions about pipeline continuation or termination. The system serves itself by using stored metadata to determine when to skip redundant executions, reducing resource waste without human intervention while maintaining appropriate automation.
Data Source
AI summary
Techniques described herein relate to modifying executions of a stateful continuous integration and continuous deployment (CI/CD) pipeline. For example, a computing system can execute a CI/CD pipeline by applying tasks to a software project. The computing system can store a resulting state produced by each execution of the CI/CD pipeline. For a particular task of the multiple tasks in the CI/CD pipeline, the computing system can determine a repeated status over multiple prior executions of the CI/CD pipeline based on the stored resulting states. The computing system can modify a subsequent execution of the CI/CD pipeline based on the repeated status of the particular task.