Distributed Cloud Application Deployment via Segmented Universal Descriptors
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Solution Overview
Problem
Current cloud computing techniques lack the ability to effectively deploy cloud applications across heterogeneous distributed environments, including private and public clouds, and do not adequately address load-balancing and fail-over scenarios, especially in hybrid cloud solutions where security and data privacy are concerns.
Innovation Solution
A method for describing cloud applications as compositions of nodes with defined deployment requirements and interfaces, allowing deployment into multiple cloud environments, with mechanisms for load-balancing and fail-over, and the use of machine-processable renditions to automate deployment into heterogeneous cloud provider environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud applications are deployed into a single cloud provider environment, then deployment simplicity is maintained, but adaptability to heterogeneous cloud environments and ability to leverage hybrid cloud benefits is limited
Solution Approach 1:
The cloud application is segmented into multiple deployable units or components, each with its own deployment descriptor. This allows different parts of the application to be deployed to different cloud providers independently, enabling heterogeneous cloud deployment while maintaining manageable complexity through modular organization of deployment configurations.
Solution Approach 2:
A universal deployment descriptor format is defined that can describe cloud applications in a cloud-provider-independent manner. This universal descriptor can be adapted to multiple cloud providers through standardized interfaces and abstractions, allowing the same application description to work across heterogeneous cloud environments without requiring provider-specific customization for each deployment target.
2Reliability
If enterprise-sensitive data and logic are kept within private cloud environments, then security and data privacy are improved, but ability to utilize public cloud benefits such as elastic scaling and resource efficiency is reduced
Solution Approach 1:
The application is segmented into sensitive components that require private cloud deployment and non-sensitive components that can leverage public cloud resources. The deployment descriptor explicitly specifies which components should be deployed to which cloud environment based on security requirements, enabling selective placement that maintains security while maximizing public cloud utilization for appropriate workloads.
Solution Approach 2:
A standardized interface layer or abstraction mechanism is introduced that allows secure communication between private cloud components (handling sensitive data) and public cloud components (providing elastic scaling). This intermediary enables the system to maintain security boundaries while still achieving the benefits of public cloud resources through controlled, secure interactions.
3Reliability
If additional instances are deployed dynamically for load-balancing and fail-over, then system reliability and availability are improved, but deployment management complexity increases
Solution Approach 1:
The deployment descriptor includes automated configuration information that enables the system to self-manage the deployment of additional instances for load-balancing and fail-over. The standardized descriptor format allows automated deployment tools to interpret configuration requirements and automatically provision, configure, and manage redundant instances across different cloud providers without requiring manual intervention, thereby reducing management complexity while maintaining high availability.
4Ease of operation
If cloud applications are described with provider-specific formats, then ease of deployment to that specific provider is improved, but ability to deploy to heterogeneous cloud environments is reduced
Solution Approach 1:
A universal, cloud-provider-independent deployment descriptor format is defined that can describe cloud applications in a vendor-neutral manner. This universal descriptor incorporates standardized elements that can be mapped to multiple cloud providers' specific requirements, allowing the same application description to be deployed to heterogeneous cloud environments while maintaining ease of deployment through automated translation or interpretation to provider-specific formats when needed.
Data Source
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AI summary
In certain example embodiments, distributed cloud application deployment systems (DCADS), and/or associated methods are provided. A formal description of the cloud application is created. The cloud application's formal representation, with its constituent nodes and their associated properties and interfaces, etc., is exported to a machine processable form. The exported DCADS machine processable rendition and any needed implementation artifacts are retrieved by a cloud application deployer that helps facilitate the deployment of the cloud application into the distributed and heterogeneous cloud environments as prescribed in the DCADS.