Declarative Deployment Specification for Cloud Artifact Delivery
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Solution Overview
Problem
Conventional continuous delivery platforms for cloud computing require complex and fragmented deployment pipelines, necessitating significant development effort and maintenance, especially when changes are made to deployment strategies, which complicates debugging and troubleshooting.
Innovation Solution
A cloud platform-independent declarative specification is used to generate cloud platform-specific data centers and deployment pipelines, allowing for the implementation of various deployment strategies without requiring cloud platform-specific instructions, thereby simplifying the deployment process and reducing maintenance overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional continuous delivery platforms are used to manage deployment pipelines, then software deployment can be automated, but the pipelines become complex and fragmented requiring significant development effort and maintenance
Solution Approach 1:
The patent introduces a deployment strategy specification as an intermediary layer between the continuous delivery platform and the actual deployment pipelines. This specification acts as a mediator that translates high-level deployment strategies into concrete pipeline configurations, eliminating the need for complex fragmented pipelines while maintaining automation. The specification serves as an abstract interface that simplifies the connection between deployment goals and implementation details.
Solution Approach 2:
The deployment strategy specification is designed to be universal and platform-independent, capable of describing multiple deployment strategies (such as blue-green, canary, rolling updates) in a unified manner. This universal specification can be applied across different cloud platforms and continuous delivery tools, reducing complexity by providing a single source of truth for deployment logic rather than requiring separate complex pipelines for each strategy.
2Adaptability or versatility
If deployment strategies are changed to meet different application requirements, then deployment flexibility is improved, but significant changes to pipelines are required increasing development effort
Solution Approach 1:
The patent segments the deployment configuration into two independent parts: the deployment strategy specification (which defines the what and how) and the pipeline implementation (which defines the execution details). When deployment strategies need to be changed, only the specification portion needs to be modified, while the underlying pipeline infrastructure remains unchanged. This segmentation isolates the changes required, significantly reducing development effort compared to modifying entire pipelines.
Solution Approach 2:
The deployment strategy specification is designed to be dynamic and adaptable, allowing organizations to switch between different deployment strategies (blue-green, canary, rolling updates, etc.) by simply changing the specification parameters. The system dynamically interprets the updated specification and adjusts the deployment process accordingly, without requiring static, hard-coded pipeline modifications for each strategy type.
3Adaptability or versatility
If complex pipelines are implemented to support multiple deployment strategies, then deployment capability is enhanced, but debugging and troubleshooting become difficult requiring significant effort
Solution Approach 1:
The patent extracts the deployment strategy logic from the complex pipeline implementation and places it in the deployment strategy specification. This extraction separates the strategic decision-making layer from the operational execution layer, making it easier to debug and troubleshoot. When issues arise, developers can focus on the simplified specification rather than navigating through complex pipeline code, significantly reducing debugging difficulty while maintaining full deployment strategy support.
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 an artifact version map that identifies versions of software artifacts for data center entities of the data center and a cloud platform independent master pipeline that includes instructions for performing operations related to services on the data center, for example, deploying software artifacts, provisioning computing resources, and so on. The system receives a deployment manifest that provides declarative specification of deployment strategies for deploying software artifacts in data centers. The system implements a deployment operator that executes on a cluster of computing systems of the cloud platform to implement the deployment strategies.


