Policy-Based Provisioning for Collaborative Computing Environments
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Solution Overview
Problem
Conventional collaborative computing environments are rigid and lack centralized management controls, leading to issues such as excessive resource usage, uncontrolled data storage, and unauthorized access, as end-user self-provisioning shifts responsibility from IT departments to users, conflicting with the need for professional IT management.
Innovation Solution
A policy-based provisioning and management system that limits collaborative context creation and operation through defined rules, monitors usage data, and enforces policies to prevent violations, including resource allocation, idleness, and access control, allowing for centralized monitoring and remediation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If end-user self-provisioning is implemented to allow collaborators to create and manage collaborative environments on demand, then ease of operation and adaptability are improved, but IT management control and security are worsened
Solution Approach 1:
A policy server is introduced as an intermediary component between end-users and the collaborative environment infrastructure. The policy server receives provisioning requests from users, evaluates them against defined policies, and grants or denies access accordingly. This mediator enables self-service while maintaining IT control through centralized policy enforcement.
Solution Approach 2:
The system implements feedback mechanisms where the policy server continuously monitors provisioning requests and user actions against defined policies. When policy violations are detected, the system provides feedback by denying access or triggering remediation processes, creating a closed-loop control system that balances user autonomy with IT management requirements.
2Productivity
If self-service collaborative systems allow collaborators to manage resources on demand, then adaptability and productivity are improved, but resource consumption control and security are worsened
Solution Approach 1:
Policies are defined in advance that specify acceptable resource consumption limits, usage patterns, and security requirements before users provision environments. The policy server evaluates provisioning requests and ongoing operations against these pre-defined policies, preventing excessive resource consumption and security violations before they occur rather than reacting after problems arise.
Solution Approach 2:
The system dynamically adjusts resource allocation parameters based on policy requirements and usage patterns. The policy server can modify resource limits, access permissions, and configuration parameters in real-time based on defined policies, enabling flexible resource management that adapts to user needs while enforcing security and consumption controls.
3Adaptability or versatility
If customized collaborative computing environments are created to meet specific needs, then adaptability is improved, but rigidity and immutability increase
Solution Approach 1:
The system provides dynamic customization capabilities where users can provision collaborative environments with customized configurations, and these configurations can be dynamically adjusted during operation. The policy server enables dynamic policy application and modification, allowing the environment to adapt its composition and behavior while maintaining stability through enforced policy constraints.
Data Source
AI summary
The present invention is a method, system and apparatus for the policy based provisioning and management of a collaborative context. A policy based application provisioning system for use in a collaborative environment can include a policy having rules for limiting collaborative context creation and operation in the collaborative environment. A context provisioning process can be coupled to the policy and configured to create collaborative contexts in the collaborative environment limited by the rules in the policy. Finally, a context management process can be coupled to a data store of usage data for created ones of created collaborative contexts in the collaborative environment.