Manifest-Driven Application Provisioning Across Distributed Tiers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In complex distributed multi-tiered computing environments, efficiently provisioning applications across diverse devices and domains becomes challenging due to increased complexity and the need to meet service level agreements and objectives, necessitating improved management and scheduling strategies.
Innovation Solution
A hierarchical management approach is implemented, involving global, domain, and device-level controllers to manage application provisioning, using manifests to extract deployment information and schedule applications efficiently, with global controllers parsing manifests for high-speed key-value databases and local controllers performing domain-level scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If applications are provisioned in complex distributed multi-tiered computing environments with more devices and data, then the capability to handle diverse workloads is improved, but the difficulty to determine where to provision applications and how to efficiently schedule them increases
Solution Approach 1:
The system segments the distributed computing environment into multiple domains (edge domain, core domain, cloud domain) with different resource characteristics and service level agreements. Each domain is independently managed and scheduled, allowing the complex environment to be broken down into manageable segments that can be provisioned separately based on specific requirements.
Solution Approach 2:
Different domains are assigned different quality characteristics through service level agreements (SLAs). Edge domains prioritize low latency for real-time applications, core domains provide balanced performance, and cloud domains offer high scalability. This local quality differentiation allows applications to be provisioned to appropriate domains based on their specific quality requirements.
2Ease of operation
If manual provisioning methods are used in complex distributed environments, then flexibility in customization is maintained, but the time and resources required for provisioning increase significantly
Solution Approach 1:
Service level agreements are pre-configured with deployment templates that contain predetermined provisioning parameters, resource requirements, and scheduling policies. When an application needs to be provisioned, the system selects and applies the appropriate pre-configured template, eliminating the need for manual customization and significantly reducing provisioning time while maintaining flexibility through template selection.
Solution Approach 2:
The system enables automated self-service provisioning by parsing deployment manifests and automatically matching applications with appropriate domains based on service level agreements and resource availability. This automated process eliminates manual intervention while maintaining the ability to customize provisioning through manifest configuration.
3Productivity
If automated provisioning is implemented to reduce manual effort, then provisioning speed is improved, but the complexity of managing the provisioning system increases
Solution Approach 1:
A global controller acts as an intermediary between deployment requests and domain controllers. It parses deployment manifests, determines appropriate target domains based on service level agreements, and coordinates provisioning across multiple domains. This intermediary layer simplifies the overall system management by centralizing decision-making logic while allowing individual domain controllers to maintain operational independence.
4Reliability
If service level agreements are enforced to ensure performance requirements, then reliability of service delivery is improved, but the complexity of configuring and managing agreements increases
Solution Approach 1:
Service level agreements are defined using configurable parameters such as minimum performance thresholds, resource allocation limits, and priority levels. These parameters can be adjusted based on application requirements and domain capabilities, allowing flexible configuration of reliability requirements without hardcoding complex rules. The system automatically translates these parameters into provisioning and scheduling decisions.
Data Source
AI summary
Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a global controller, an DMC environment management request from a user, and the DMC environment management request is associated with scheduling an application in the DMC environment; and in response to obtaining the request: providing acknowledgment that the request is received to the user; obtaining an order identifier and a manifest from the user; providing a correlation identifier associated with the request to the user; parsing the manifest to extract application deployment information; scheduling the application to target domains of the DMC based on the application deployment information; and providing the user with the correlation identifier, a success indicator, and application information.