Container Dependency Graphs for Pre-Deployment Health Checks
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Solution Overview
Problem
Existing solutions for container-based environments fail to identify critical resource dependency paths, leading to deployment issues and inefficiencies, as they require a successfully deployed system and cannot address missing or unhealthy resources due to unresolved dependencies, and lack real-time collaboration mechanisms for developers and testers.
Innovation Solution
A resource deployment health report graph is generated to identify critical and non-critical dependency paths, enabling real-time collaboration and resolution of issues by displaying the status of each resource and allowing for immediate modification of dependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing deployment solutions are used in container-based environments, then deployment can proceed without specialized dependency analysis tools, but critical resource dependency paths cannot be identified leading to deployment issues and inefficiencies
Solution Approach 1:
The system performs preliminary analysis of resource dependency paths before deployment execution. By generating a resource dependency graph and identifying critical paths in advance, the system enables proactive detection of potential deployment issues, allowing teams to resolve dependencies before they cause failures, thus improving both measurement precision and deployment efficiency
Solution Approach 2:
The patent introduces an intermediary deployment health report graph that visualizes resource dependency relationships. This intermediary tool bridges the gap between complex underlying dependencies and user understanding, enabling precise identification of critical paths without requiring users to manually analyze complex system relationships, thereby improving both accuracy and efficiency
2Loss of time
If deployment validation is performed only after complete deployment, then all resources must be deployed first increasing time to detection, but real-time dependency status cannot be monitored
Solution Approach 1:
The system implements continuous monitoring of resource dependency status throughout the deployment process. By continuously updating the deployment health report graph and monitoring dependency states in real-time, the system eliminates idle validation time while maintaining reliable status monitoring, allowing immediate detection of deployment issues without waiting for complete deployment
Solution Approach 2:
The patent implements feedback mechanisms that provide real-time information about resource dependency status during deployment. The deployment health report graph continuously reflects current dependency states, enabling immediate feedback on deployment health and allowing teams to respond to issues as they arise rather than discovering them after deployment completion, thus reducing time loss while maintaining reliability
3Measurement precision
If comprehensive resource dependency analysis is implemented, then deployment health can be accurately assessed, but system complexity increases requiring additional tools and processes
Solution Approach 1:
The system segments the complex dependency analysis into distinct components: resource identification, dependency relationship mapping, critical path identification, and health status assessment. By dividing the analysis into manageable segments represented in the deployment health report graph, the system achieves comprehensive accuracy while reducing perceived complexity through structured organization of analysis functions
Solution Approach 2:
The patent creates a virtual copy of the deployment system in the form of a deployment health report graph. This graphical representation copies essential dependency relationships and status information without requiring the full complexity of the actual system, enabling accurate health assessment through a simplified visual model that reduces analytical complexity while maintaining measurement precision
4Productivity
If real-time collaboration features are added for developers and testers, then issue resolution speed improves, but system complexity and resource requirements increase
Solution Approach 1:
The system merges collaboration features directly into the deployment health report graph interface. By combining dependency visualization, health monitoring, and real-time collaboration capabilities into a single integrated interface, the system enables fast issue resolution through unified access while avoiding the complexity of separate collaboration tools, allowing developers and testers to collaborate efficiently within the existing system framework
Data Source
AI summary
A resource deployment health report graph that defines a first plurality of resource dependencies set as a needed resource dependency type and a second plurality of resource dependencies set as an optional resource dependency type is generated prior to resources being connected in a container-based environment. An analysis of the resource deployment health report graph is performed to determine a status of each of the first plurality of resource dependencies and each of the second plurality of resource dependencies. It is determined whether each of the first plurality of resource dependencies and the second plurality of resource dependencies is marked ready in the resource deployment health report graph based on the analysis. In response to determining that each of the first plurality of resource dependencies and the second plurality of resource dependencies is marked ready, it is determined that an actual deployment is successfully implemented in the container-based environment.