Cloud Platform Independent Data Center Orchestration
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Solution Overview
Problem
Configuring and managing data centers on cloud platforms is complex and prone to errors, requiring expertise in specific cloud technologies and leading to potential downtime due to manual steps and security violations, especially for multi-tenant systems that need to manage multiple data centers across different cloud platforms.
Innovation Solution
A cloud platform-independent declarative specification is used to generate a platform-specific data center representation, allowing for the creation of data centers on various cloud platforms using a cloud platform infrastructure language, which compiles instructions for execution on the target platform, thereby reducing the need for platform-specific expertise and minimizing errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration steps are used for datacenter creation on cloud platforms, then flexibility in customization is improved, but error rate and security violations increase
Solution Approach 1:
The system performs self-service by automatically generating configuration files, provisioning resources, and deploying software without manual intervention. The orchestration engine autonomously manages the entire datacenter creation process, eliminating human errors while maintaining customization through declarative specifications.
Solution Approach 2:
The patent introduces an orchestration engine as an intermediary between the user's declarative specification and the cloud platform's implementation details. This intermediary automatically translates high-level requirements into platform-specific configurations, reducing errors while preserving customization flexibility.
2Manufacturing precision
If platform-specific expertise is required for datacenter configuration, then configuration accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The orchestration engine provides universal functionality by handling multiple cloud platforms through a single interface. It automatically adapts declarative specifications to different platform requirements, eliminating the need for platform-specific expertise while maintaining configuration accuracy through automated validation and generation.
Solution Approach 2:
The patent replaces manual mechanical configuration processes with automated computational processes. The orchestration engine uses algorithms to generate configurations, validate requirements, and provision resources automatically, substituting human expertise with automated intelligence that maintains accuracy while improving ease of operation.
3Adaptability or versatility
If manual provisioning and deployment processes are used, then adaptability to specific requirements is improved, but productivity and time efficiency deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-compiling declarative specifications into executable configuration files and pre-validating requirements before actual provisioning. The orchestration engine prepares all necessary configurations, resource allocations, and deployment parameters in advance, enabling rapid execution while maintaining adaptability to specific requirements.
Solution Approach 2:
The orchestration engine enables continuous provisioning by automating the entire workflow from specification to deployment without manual interruptions. It continuously manages resource allocation, configuration generation, and software deployment, eliminating idle time and manual transitions while maintaining adaptability through declarative input processing.
4Reliability
If complex manual configuration processes are used, then security control is improved, but downtime and service disruption increase
Solution Approach 1:
The orchestration engine implements feedback mechanisms by continuously validating configurations against security policies and requirements during automated provisioning. It provides real-time feedback on configuration correctness, security compliance, and resource availability, enabling rapid correction of issues without manual intervention or service disruption.
Solution Approach 2:
The system applies beforehand cushioning by pre-validating all configurations and checking security compliance before actual deployment. The orchestration engine performs preliminary security checks, resource availability verification, and configuration validation to prevent errors and security violations before they cause downtime or service disruption.
Data Source
AI summary
Computing systems, for example, multi-tenant systems deploy software artifacts in data centers created in a cloud platform using a cloud platform infrastructure language that is cloud platform independent. The system receives a declarative specification for creating a datacenter on a cloud platform. The system generates an aggregate pipeline comprising a hierarchy of pipelines. The system generates an aggregate deployment version map associating data center entities of the data center with versions of software artifacts targeted for deployment on the datacenter entities. The system collects a set of software artifacts according to the aggregate deployment version map. The system executes the aggregate pipeline in conjunction with the aggregate deployment version map to create the datacenter in accordance with the cloud platform independent declarative specification.