Automated Container Rehydration with Gradual Traffic Rollout
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The frequent updates required in the base layer of software containers for security and OS patches lead to a burdensome deployment process, involving multiple teams and potentially introducing errors that are only detected in production, causing performance degradation and user dissatisfaction.
Innovation Solution
A system and method for automated software container rehydration and deployment that incrementally increases traffic to newly-deployed containers, monitors performance using defined thresholds, and automatically validates functionality, ensuring seamless updates and minimizing disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the base layer of container images is updated frequently to incorporate security and OS updates, then system security and reliability are improved, but the deployment complexity and time required increase significantly
Solution Approach 1:
The patent segments the container image update process into distinct phases: building the updated image in a passive environment, validating it through automated testing, and then gradually rolling it out to production. This segmentation allows security updates to be applied systematically without overwhelming the deployment process.
Solution Approach 2:
The patent performs preliminary validation and testing of updated container images in a passive production environment before full deployment. Automated tests are run on the updated image to detect errors early, and the image is validated against the live environment before being rolled out to avoid impacting end users.
2Manufacturing precision
If multiple teams are involved in the manual deployment process, then thorough validation can be performed, but the time required for deployment increases
Solution Approach 1:
The patent implements self-service automation where the system automatically builds updated container images, runs validation tests, determines rollout strategies, and monitors deployment progress without requiring manual intervention from multiple teams. The automated system performs functions that previously required coordinated human effort across development, QA, and operations teams.
Solution Approach 2:
The patent incorporates automated feedback loops where test results and performance metrics automatically inform deployment decisions. The system monitors service level indicators and automatically adjusts rollout based on observed performance, eliminating the need for manual review cycles while maintaining thorough validation.
3Productivity
If container updates are deployed quickly to production, then productivity is improved, but the risk of introducing errors that affect end users increases
Solution Approach 1:
The patent performs preliminary validation in a passive production environment that mirrors the live environment. Automated tests detect errors before deployment, and the system verifies the updated image works correctly with the current live environment before rolling it out, ensuring rapid deployment does not compromise error detection.
Solution Approach 2:
The patent implements a gradual rollout strategy where the updated container image is first deployed to a small subset of traffic, allowing the system to detect issues with a limited user base before full deployment. This cushioning approach minimizes the impact of potential errors while maintaining deployment speed.
4Reliability
If automated testing and validation are performed on updated images, then deployment reliability is improved, but the time and resources required for the process increase
Solution Approach 1:
The patent implements self-service automation where the system automatically executes validation tests and determines deployment readiness without manual intervention. This automation maintains thorough validation while reducing the perceived time burden by eliminating manual waiting and coordination overhead.
Solution Approach 2:
The patent performs validation continuously as part of the automated deployment pipeline rather than as separate discrete steps. Tests run automatically as the image is built and prepared for deployment, eliminating idle time between build and deploy decisions while maintaining comprehensive validation.
Data Source
AI summary
Methods and apparatuses for automated software container rehydration and deployment include a server that updates a container image for a software application by modifying layers of the container image and deploying the updated container image as a first container in a passive production environment. For a plurality of traffic volumes, the server: a) increases application traffic directed to the first container to a first traffic volume, b) monitors service level indicators associated with performance of the first container, c) increases the application traffic directed to the first container to a higher traffic volume upon determining that the service level indicators are within a performance threshold, and d) repeats steps b) and c) until the application traffic is increased to a highest traffic volume and the service level indicators are within the performance threshold. The server deploys the updated container image as a second container in an active production environment.