Two-Tier Cloud Analytics Reporting for Data Sovereignty
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Solution Overview
Problem
Existing cloud infrastructure environments face challenges in efficiently managing and provisioning infrastructure resources, particularly in evolving and deploying applications across various virtual computing environments, leading to complexity and increased costs for organizations.
Innovation Solution
A cloud infrastructure environment with a two-tier reporting system is deployed, featuring a central analytics service and respective instances in each realm, utilizing different data pipelines for data ingestion and transformation, generating reports based on cloud realm usage, and enabling cross-realm communication for comprehensive data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a centralized analytics service is deployed only in the cloud provider realm, then data sovereignty and privacy are maintained, but realm operators cannot generate comprehensive dashboards for their own cloud operations
Solution Approach 1:
The analytics service is segmented into two independent instances: one deployed in the cloud provider realm and another deployed in each operator realm. Each instance processes data locally within its realm, enabling realm operators to generate comprehensive dashboards for their cloud operations while maintaining data sovereignty. The segmentation allows each realm to have autonomous analytics capabilities without compromising data privacy.
Solution Approach 2:
A cross-realm data transfer mechanism acts as an intermediary that selectively transfers aggregated data from operator realms to the cloud provider realm. This intermediary enables the cloud provider to receive necessary visibility for metering and capacity planning while preserving the confidentiality of sensitive operational data. The cross-realm communication bridge facilitates controlled information exchange without direct access to proprietary data.
2Loss of information
If comprehensive data is transferred from operator realms to cloud provider realm, then cloud providers gain visibility for metering and capacity planning, but operator proprietary data may be exposed
Solution Approach 1:
The system extracts only the essential aggregated data elements needed for metering and capacity planning from operator realms, leaving sensitive operational details within the operator's controlled environment. The cross-realm data transfer mechanism selectively transfers specific data types (usage metrics, resource consumption) while excluding proprietary operational data, thus providing cloud provider visibility without exposing sensitive information.
Solution Approach 2:
Different data quality levels are applied to different realms: operator realms maintain high-quality detailed data for their own analytics, while the cloud provider realm receives aggregated, lower-quality data suitable for billing and capacity planning. This local quality differentiation ensures each realm has appropriate data granularity for its specific needs while maintaining security boundaries.
3Reliability
If separate data pipelines are implemented for each realm, then data sovereignty is maintained, but system complexity increases
Solution Approach 1:
The analytics service is designed as a universal, multi-functional platform that can operate independently in any realm while performing the same core analytics functions. The service instance deployed in each realm provides identical capabilities for dashboard generation, data processing, and reporting. This universality simplifies deployment and maintenance despite the distributed architecture, as the same service blueprint is replicated across multiple realms.
Solution Approach 2:
The analytics service instances are nested within their respective realms, with each realm containing its own self-contained analytics instance. The cloud provider realm contains an analytics instance that can receive aggregated data from nested operator realm instances. This nesting structure maintains clear boundaries and data sovereignty while creating a hierarchical relationship that manages complexity through organized containment.
Data Source
AI summary
In accordance with an embodiment, systems and methods are provided for two-tier reporting for cloud computing realms. An exemplary method can deploy a central instance of an analytics service in a central cloud realm. The method can further deploy a respective instance of the analytics service in each of a plurality of cloud realms. The method can implement a respective different data pipeline for each deployed respective instance of the analytics service, wherein a respective different data pipeline is configured to perform at least one of ingest or transform data for the deployed respective instance of the analytics service, said data being descriptive of use of services associated with a respective cloud realm of the plurality of cloud realms.