Cloud Application Patching via HA Metric Segmentation
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Solution Overview
Problem
Current patching methods for cloud applications fail to consider High Availability (HA) metric values of various roles, leading to potential disruptions in service availability during patching processes.
Innovation Solution
A patching process is defined where HA metric values for each server role are determined, allowing a subset of servers to be removed from the rotation framework without impacting overall HA, enabling parallel patching and subsequent reinstatement without affecting end-user availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If regular patching is performed on cloud application servers, then security compliance and system evolution are improved, but service availability is degraded
Solution Approach 1:
The system segments the server fleet into multiple subsets based on HA metric values, allowing independent patching of each subset. The orchestration module identifies servers with HA values above a threshold and removes them from the rotation framework in controlled groups, enabling parallel patching operations that maintain overall service availability while improving security compliance.
Solution Approach 2:
The system performs preliminary assessment of HA metric values for each server before initiating patching operations. Servers are pre-identified and pre-removed from the rotation framework based on their HA values, allowing patching to occur without impacting service availability. This preliminary action ensures that only servers whose removal won't affect HA are selected for patching.
2Productivity
If all servers are patched simultaneously, then patching efficiency is improved, but service availability is degraded
Solution Approach 1:
The system divides the server population into multiple subsets based on HA metric thresholds, enabling parallel patching operations on each subset simultaneously. This segmentation allows the patching process to scale efficiently across the infrastructure while maintaining service availability, as each subset is patched independently without causing system-wide disruptions.
Solution Approach 2:
The system applies patching to only the necessary subset of servers at any given time - specifically those with HA values above the threshold - rather than patching all servers simultaneously. This partial action approach maintains patching efficiency by focusing resources on eligible servers while preserving service availability through selective application of the patching action.
3Ease of manufacture
If servers are removed from rotation framework for patching, then patching can be performed, but overall HA metric value may be degraded
Solution Approach 1:
The system performs preliminary evaluation of each server's HA metric value before removing it from the rotation framework. Only servers with HA values exceeding the threshold are selected for removal and patching, ensuring that the remaining servers maintain the required overall HA metric value. This preliminary filtering prevents degradation of service availability while enabling necessary patching operations.
Solution Approach 2:
The system continuously monitors HA metric values and uses this feedback to dynamically adjust which servers are removed from the rotation framework. The orchestration module evaluates HA values, selects appropriate subsets for patching, and reinstates servers upon completion, creating a feedback loop that maintains overall HA while enabling ongoing patching operations.
Data Source
AI summary
A cyclical patching process associated with a cloud application may be defined to ensure high availability (HA) of the cloud application in order to prevent impacting an availability to end users. A list of server identities corresponding to one or more servers of a datacenter hosting the cloud application may be accepted. HA metric values for each of the server identities may be determined in order to compute an overall HA metric value for the cloud application. A subset of the servers may be removed from a rotation framework of the cloud application based on the determined HA metric values, where the removal does not affect the overall HA metric value of the cloud application. One or more patches may be applied to each server within the subset of servers in parallel, and the subset of servers may be reinstated in the rotation framework of the cloud application.