Cloud Service Outdated Identification via Aggregated Config Data
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Solution Overview
Problem
Cloud computing environments face inefficiencies due to the maintenance of outdated cloud computing resources, which lead to unnecessary resource allocation and impact performance by occupying resources that could be used for active services.
Innovation Solution
A system that identifies outdated cloud computing services by storing configuration data separately for each account, aggregating it, and executing functions to search for user identifiers, thereby identifying and transmitting information about outdated services for deletion, either manually or automatically after a threshold time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud computing resources are maintained for redundancy and low latency, then service availability and performance are improved, but outdated services occupy resources unnecessarily and reduce overall system efficiency
Solution Approach 1:
The system performs preliminary identification of outdated cloud computing services by analyzing configuration data before resources are fully consumed. By proactively detecting services that are no longer needed based on configuration mismatches between actual deployed services and configuration files, the system enables early intervention to free up resources, thus maintaining high availability while improving overall resource utilization efficiency.
2Reliability
If multiple accounts are managed separately, then account security and isolation are maintained, but identifying outdated services across accounts becomes complex and time-consuming
Solution Approach 1:
The system implements a universal identification mechanism that can operate across multiple cloud computing accounts simultaneously. The configuration data analysis function is designed to work with any account structure, automatically adapting to different account configurations while maintaining security boundaries. This multi-functional approach allows the same identification process to be applied across numerous accounts without increasing operational complexity.
3Ease of operation
If configuration data is stored separately for each account, then data organization and security are improved, but aggregating and searching across accounts increases processing time and computational resources
Solution Approach 1:
The system segments the configuration data analysis process into account-specific processing units that operate independently and in parallel. Each account's configuration data is analyzed separately to identify outdated services, then results are aggregated. This segmented approach maintains the organizational benefits of separate storage while reducing total processing time through parallel execution, avoiding the need for sequential analysis of all accounts.
Data Source
AI summary
A cloud tracking system may store configuration data separately for each account of multiple accounts that an entity has with a cloud computing provider and may aggregate the configuration data into a data structure that stores the configuration data together for the multiple accounts. The cloud tracking system may receive a request that includes a user identifier of a user associated with the entity and may search for the user identifier in the data structure. The cloud tracking system may identify a set of deployed cloud computing services associated with the user identifier based on searching for the user identifier in the data structure, wherein the set of deployed cloud computing services is associated with more than one account of the multiple accounts. The cloud tracking system may identify one or more deployed cloud computing services, of the set of deployed cloud computing services, that are outdated.