Dynamic Telemetry Service Model for Computing Resource Monitoring
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Solution Overview
Problem
Conventional monitoring approaches in computing environments often collect excessive data, requiring time and resources to sort through irrelevant information and necessitate agent changes or replacements when service requirements evolve, leading to downtime and productivity losses.
Innovation Solution
A telemetry process is established based on operational metrics, allowing for dynamic deployment of monitoring processes that follow component relocation and on-demand provisioning, enabling efficient monitoring and resource utilization through a service model that defines how to access and compute key quality indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If generic agents collect all types of information and relay to a centralized process, then comprehensive data collection is achieved, but the amount of information collected exceeds what is needed, requiring additional processing to sort through irrelevant data
Solution Approach 1:
The patent extracts only the necessary monitoring data from components by defining specific operational metrics and key quality indicators that are relevant to service status, rather than collecting all possible information. This selective extraction eliminates irrelevant data and reduces processing time.
Solution Approach 2:
The patent implements local quality by allowing different components to have customized monitoring configurations based on their specific roles and the service requirements. Each component can have tailored operational metrics defined, ensuring that only locally relevant data is collected and processed.
2Measurement precision
If special purpose agents are configured to monitor each component, then monitoring precision is improved, but agent change or replacement is required when service requirements evolve, resulting in downtime and productivity loss
Solution Approach 1:
The patent implements dynamics by making the monitoring configuration dynamic rather than static. Operational metrics and key quality indicators can be modified at runtime without requiring agent replacement. The system adapts to changing service requirements by dynamically updating the monitoring parameters through configuration files or database entries.
Solution Approach 2:
The patent creates a universal monitoring framework that can handle multiple service types and component configurations through a common architecture. The same monitoring infrastructure can be applied across different services by simply changing the operational metrics definitions, eliminating the need for specialized agents for each service type.
3Adaptability or versatility
If agents are changed or replaced to accommodate service growth, then monitoring capability is updated, but system downtime occurs during the update process
Solution Approach 1:
The patent applies preliminary action by pre-defining operational metrics and key quality indicators in configuration files or database entries before they are needed. When service requirements change, the system can activate pre-configured metrics without requiring agent replacement or system downtime, as the monitoring infrastructure is already in place and ready to collect the new data.
4Loss of information
If centralized processes sort through output from multiple generic agents, then relevant data is identified, but processing complexity increases
Solution Approach 1:
The patent segments the monitoring system into distributed intelligent agents that each independently determine the relevance of data they collect based on locally defined operational metrics. This segmentation eliminates the need for a centralized process to sort through all data, as each agent already filters and structures its data according to service-specific requirements before transmission.
Data Source
AI summary
In accordance with one embodiment, there are provided mechanisms and methods for creating a telemetry process for a service in a computing environment. With these mechanisms and methods, it is possible to deploy telemetry processes for the service based upon a specification of one or more operational metrics for determining the status of the service. This ability to deploy telemetry processes for the service based upon a specification of one or more operational metrics for determining the status of the service makes it possible to attain improved monitoring capabilities and more efficient usage of computing resources assigned to monitoring tasks for a service in a computer system.