Cloud Region Data Orchestration for Scalable Resource Bootstrapping
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Solution Overview
Problem
Conventional methods for building data centers in cloud regions require significant manual effort, are time-consuming, error-prone, and do not scale well, limiting the ability of cloud service providers to quickly respond to growing customer demands.
Innovation Solution
A Cloud Infrastructure Orchestration Service (CIOS) automates the provisioning and deployment of resources in data centers using predefined configuration files, identifies dependencies, and optimizes parallel processing to reduce build time and errors, utilizing a virtual bootstrap environment to manage region data in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual methods are used to build data centers in cloud regions, then flexibility and control are maintained, but significant manual effort is required, making the process time-consuming and error-prone
Solution Approach 1:
The system enables automated self-service through the cloud infrastructure orchestration service, which automatically provisions, configures, and deploys infrastructure resources without requiring manual intervention. The service monitors and manages the entire region build process autonomously, reducing manual effort while maintaining productivity.
Solution Approach 2:
Manual mechanical operations are replaced with an automated orchestration service that uses software-based control to provision and configure infrastructure resources. The service substitutes human operators with automated algorithms that can rapidly execute build tasks without fatigue or errors.
2Adaptability or versatility
If manual updates are performed for modifying region data, then direct control is achieved, but the effort increases significantly as the number of service teams and regions grows
Solution Approach 1:
The cloud infrastructure orchestration service provides universal modification capabilities that work across all regions and service teams through a unified interface. A single automated system handles modifications for multiple regions simultaneously, eliminating the need for separate manual update processes for each team or region.
Solution Approach 2:
The service performs preliminary actions by pre-configuring region data templates and automated update workflows before modifications are needed. When changes are required, the system automatically applies pre-defined modification patterns across all affected regions, reducing the time and effort required for maintenance.
3Device complexity
If conventional tools are used for building regions, then simplicity is maintained, but the process does not scale well with increasing numbers of service teams and regions
Solution Approach 1:
The orchestration service segments the region build process into modular, independent tasks that can be executed in parallel across multiple regions. Each service team's build operations are segmented into discrete provisioning, configuration, and deployment steps that can be managed and scaled independently, enabling the system to handle increasing numbers of teams and regions efficiently.
Data Source
AI summary
Techniques are described for performing an automated region build with real time region data. Region data including region identifiers and execution target identifiers for the region may be maintained. When a modification of the region data is detected (or new region data is detected), configuration files corresponding to bootstrapping resources (e.g., at the execution targets) within the region may be obtained. Operations are executed to cause the configuration files to be updated. This may include recompiling or otherwise injecting region data into the configuration files. A region build may be executed to bootstrap resources within the region using the updated configuration files.