Deployment Pattern Monitoring via Virtual Machine Testing
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Solution Overview
Problem
Existing deployment pattern monitoring systems lack proactive mechanisms to identify potential issues before actual deployment, leading to potential failures and downtime in cloud environments.
Innovation Solution
A computer-implemented method that monitors candidate deployment components by querying a deployment pattern registry, testing deployment capabilities, and generating notifications for failures, allowing for proactive identification and resolution of issues before deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If deployment patterns are deployed without prior monitoring, then deployment speed is maintained, but deployment reliability deteriorates due to undetected potential failures
Solution Approach 1:
The system performs preliminary monitoring and testing of deployment patterns before actual deployment by creating virtual machine instances to verify candidate deployment components. This advance verification identifies potential failures beforehand, ensuring deployment reliability without significantly impacting deployment time since the monitoring occurs in parallel or during off-peak periods.
2Reliability
If comprehensive testing is performed on all deployment components, then deployment reliability improves, but system complexity increases due to additional monitoring infrastructure
Solution Approach 1:
Instead of directly testing all deployment components in the production environment, the system creates virtual machine copies that simulate the deployment environment. These virtual instances serve as testbeds for verifying candidate deployment components, providing comprehensive testing while isolating the production system from testing complexity and overhead.
3Reliability
If deployment monitoring is implemented, then potential failures are detected earlier, but resource consumption increases due to virtual machine instantiation
Solution Approach 1:
The system applies partial testing by focusing monitoring efforts on critical deployment components and high-risk deployment patterns rather than uniformly testing all components. Virtual machine instances are created selectively based on risk assessment, deployment frequency, and component criticality, reducing overall resource consumption while maintaining deployment reliability for the most important deployments.
Data Source
AI summary
A computer system can detect a request for status information relating to a particular deployment pattern; query, in response to the request, a deployment pattern registry for deployment configuration information about the particular deployment pattern; test deployment capabilities for the particular deployment pattern by: verifying installation files for the particular deployment pattern are accessible; identifying one or more candidate deployment components for a hypothetical deployment of the particular deployment pattern; installing, on the one or more candidate deployment components, a virtual machine that is configured to test computing resources of the one or more candidate deployment components; and receiving test results regarding the resources of the one or more candidate deployment components. The system can generate a notification in response to detecting a failure in the testing.