Recovery Server Boot Status Validation via Metric Analysis
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Solution Overview
Problem
There is no standard, operating system agnostic method to accurately determine the boot status of recovery servers, especially in cloud environments, due to lack of access credentials and varying operating system versions, making it difficult to validate failover tests and ensure disaster recovery readiness.
Innovation Solution
A system and method that uses server metrics stored in a metric store, combined with historic metrics and a machine learning model to determine the probability of successful boot status, allowing for automated validation or alerting of recovery points without requiring access credentials, and enabling manual intervention when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated failover testing is implemented, then productivity is improved by eliminating manual efforts and human error, but reliability deteriorates because there is no standard method to accurately determine boot status of recovery servers
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between the automated testing framework and the recovery server. This intermediary captures and analyzes boot metrics (CPU usage, memory allocation, disk I/O patterns, network connectivity) to indirectly determine boot status without requiring direct login credentials. The intermediary translates unobservable boot states into measurable metrics that can be reliably assessed automatically.
Solution Approach 2:
The patent replaces the mechanical approach of direct login and manual verification with an automated metric-based detection system. Instead of physically accessing the server through login credentials, the system substitutes this with automated collection and analysis of boot metrics through alternative channels, enabling credential-less boot status determination.
2Adaptability or versatility
If cloud-based recovery servers are used, then adaptability is improved by enabling remote failover testing, but measurement precision deteriorates because access credentials are not shared with providers
Solution Approach 1:
The patent introduces an intermediary metric collection system that bridges the gap between cloud service providers and customers. This intermediary captures boot metrics through available channels (platform monitoring APIs, network observations, metric stores) and translates them into reliable boot status indicators, enabling precise measurement without direct credential access.
Solution Approach 2:
The patent implements a feedback mechanism where boot metrics are continuously collected and analyzed to determine boot status. The system establishes feedback loops that monitor metric patterns over time, compare against expected boot signatures, and provide continuous verification of recovery server status without requiring direct access credentials.
3Measurement precision
If traditional login-based boot status checking is used, then measurement precision is improved by directly verifying server status, but ease of operation deteriorates due to credential management requirements
Solution Approach 1:
The patent enables the recovery server to self-report its boot status through automated metric collection and analysis. The system captures boot metrics from the server's own operational state (CPU initialization sequences, memory allocation patterns, service startup metrics) and uses these self-generated indicators to determine boot status, eliminating the need for external credential-based verification.
Data Source
AI summary
Disclosed herein are systems and method for determining a boot status of a failover server. In an exemplary aspect, a method may receive a failover test request for a failover server that provides disaster recovery for a production server, wherein the failover test request queries a successful boot status of the failover server. The method may determine whether a login into the failover server can be performed to execute the failover test request. In response to determining that the login cannot be performed, the method may retrieve server metrics for a failover server from a metric store and may determine a probability of the successful boot status based on both the retrieved server metrics and historic server metrics. In response to determining that the probability is greater than a threshold probability, the method may mark a recovery point of the failover server as validated.


