Multi-Cloud Network Resource Evaluation System
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Solution Overview
Problem
The manual process of provisioning cloud accounts is labor-intensive, time-consuming, and lacks automation, leading to delays, mistakes, and inconsistencies, particularly in the software development process, where account creation spans multiple cloud platforms and requires coordination across various groups, resulting in lengthy manual provisioning and restricted scalability.
Innovation Solution
An automated, integrated system for provisioning and evaluating cloud services across multiple cloud service providers, allowing application developers to automatically collect performance data without network administrator intervention, enabling rapid evaluation and optimization of user applications on cloud-based platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual provisioning process is used for cloud accounts, then account creation can be performed with existing systems, but the process takes up to 6 weeks and involves multiple manual steps across different groups
Solution Approach 1:
The system enables self-service account provisioning where developers can automatically create and manage their own cloud accounts through an automated workflow system, eliminating the need for manual intervention by administrators and reducing provisioning time from weeks to minutes
Solution Approach 2:
The system performs preliminary actions by pre-configuring account templates, security policies, and resource allocations before provisioning is requested, allowing automated instantiation of accounts without manual setup steps during the provisioning process
2Reliability
If manual account provisioning is performed, then flexibility in handling different requests is maintained, but mistakes and inconsistencies occur due to manual intervention
Solution Approach 1:
The system uses parameter-based account templates that define standardized configurations for different account types, ensuring consistent provisioning across all accounts while allowing customization through parameter selection rather than manual configuration
Solution Approach 2:
The automated provisioning system incorporates validation and verification steps that provide feedback on provisioning status, detect errors automatically, and ensure consistency across all provisioned accounts, eliminating manual review mistakes
3Productivity
If developers wait for network administrators to provide performance data, then accurate evaluation can be obtained, but development time is lost waiting for data collection
Solution Approach 1:
The system enables developers to self-serve performance data collection by automatically instrumenting their applications with evaluation code, allowing them to collect and analyze performance metrics independently without administrator involvement
Solution Approach 2:
The system replaces the manual mechanical process of administrators collecting and analyzing performance data with automated software agents that continuously monitor, collect, and process performance metrics, delivering results instantly to developers
Data Source
AI summary
A method is disclosed for evaluating network resources on a multi-cloud network platform. A network resource load balancer executes a network resource evaluation application on a server for automatic evaluation of implementing a user application via a first cloud based platform and a second cloud based platform. In response to an evaluation request, automatically and without user intervention, the server identifies a first server located in a first location on the first cloud based platform based on a source identifier; identifies a second server located in a second location on the second cloud based platform based on a target identifier; evaluates performance of the user application on the first server and the second server; in real time, determines performance data including a function latency for implementing the user application; and generates instructions to display the performance data according to a predefined format.