Cloud Platform Independent Software Release Pipeline
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Managing software releases across multiple cloud platforms is complex due to differences in tools, network policies, and access control mechanisms, leading to high maintenance costs and expertise requirements for multi-tenant systems.
Innovation Solution
A cloud platform-independent declarative specification is used to generate data centers and software release pipelines, allowing for platform-agnostic operations, including deployment, rollback, and resource provisioning, using a domain-specific language that compiles to platform-specific instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a multi-tenant system supports multiple cloud platforms with different tools and mechanisms, then the system can serve more organizations and provide greater versatility, but the maintenance cost and complexity increase significantly
Solution Approach 1:
The patent implements a universal declarative specification language that can describe data centers and software releases independently of any specific cloud platform. This specification language serves multiple functions by being able to represent different cloud platform configurations (AWS, Azure, Google Cloud) using a common syntax and semantics, thereby reducing maintenance costs while supporting multiple platforms
Solution Approach 2:
The patent introduces a compilation system as an intermediary layer between the platform-independent declarative specification and platform-specific cloud infrastructure. This compiler translates the universal specification into cloud-platform-specific configurations, eliminating the need to maintain separate implementation code for each cloud platform and significantly reducing maintenance burden
2Adaptability or versatility
If different versions of software are deployed on different services running on different cloud computing resources, then the system can meet diverse organizational requirements, but the deployment process becomes more complex
Solution Approach 1:
The patent segments the deployment specification into hierarchical components including data center definitions, service group configurations, and individual service specifications. Each service can independently specify its software version requirements within the declarative specification, allowing fine-grained control over software versions across different services while maintaining an organized, manageable structure
Solution Approach 2:
The patent uses parameter-based specifications where software versions, service configurations, and deployment parameters are defined as variables in the declarative specification. This allows dynamic configuration of different software versions across services by simply changing specification parameters rather than rewriting deployment logic, thereby simplifying the deployment process
3Reliability
If each cloud platform uses different tools for managing resources, then each platform can optimize for its specific architecture, but cross-platform management becomes difficult
Solution Approach 1:
The declarative specification language is designed with universal constructs that map to platform-specific tools through compilation. Common data center elements like compute resources, storage, networking, and load balancers are defined in a platform-agnostic manner, allowing the same specification to be compiled for different cloud platforms while maintaining consistent management practices across platforms
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 datacenter entities of the datacenter and a cloud platform independent master pipeline that includes instructions for performing operations related to services on the datacenter, for example, deploying software artifacts, provisioning computing resources, and so on. The system compiles the cloud platform independent master pipeline in conjunction with the artifact version map to generate cloud platform specific detailed pipeline that deploys the appropriate versions of deployment artifacts on the datacenter entities in accordance with the artifact version map. The system sends the cloud platform specific detailed pipeline to a target cloud platform for execution.