The Policy Creation component of OpenECOMP provides a centralized environment for the creation and management of easily-updatable conditional rules. This subsystem enables users to validate policies and rules, identify and resolve overlaps and conflicts, and derive additional policies where needed. Policies can support infrastructure, products and services, operation automation, and security. Users, who can be a variety of stakeholders such as network and service designers, operations engineers, and security experts, can easily create or change policy rules from the OpenECOMP Portal.
Policies are used to control, to influence, and to help ensure compliance with goals. A policy can be defined at a high level to create a condition, requirement, constraint, or need that must be provided, maintained, and enforced. A policy can also be defined at a lower or functional level, such as a machine-readable rule or software condition/assertion which enables actions to be taken based on a trigger or request, specific to particular selected conditions in effect at that time. Software policies that are supported include XACML policies, Drools policies, and lower level policies that are embodied in modeling languages such as YANG and TOSCA.
The Policy Creation subsystem also provides additional functionality once policies are initially created:
- Offline analysis of performance, fault, and closed-loop actions, enabling the discovery of new and signatures and refinement of existing ones
- Derivation of lower-level policies from higher-level policies
- Identification of conflicts and mitigation of them before deployment
Once validated and corrected for any conflicts, the policies are placed in an appropriate repository, and are made available to the other subsystems and components that might make use of them. In addition, the decisions and actions taken by the policy are distributed. Distribution occurs either in conjunction with the distribution of recipes (if for example they are related to service instantiation) or independently, if the policy is unrelated to a particular service. With this methodology, policies will already be available when needed by a component, minimizing real-time requests to a central policy engine or PDP (Policy Decision Point). This improves scalability and reduces latency.
Policy Distribution
After a policy has been initially created or an existing policy has been modified, the Policy Distribution Framework sends the policy from the repository to its points of use, before it is actually needed. This distribution is precisely targeted so that each distributed policy-enabled function automatically receives only the specific policies that match its needs and scope.
Separate notifications or events communicate the link or URL for a policy to the components that need it. Then, when a component needs the policy, it uses the link to fetch it. Components in some cases might also publish events indicating that they need new policies, eliciting a response with updated links or URLs. Also, in some cases, policies can indicate to components that they should subscribe to one or more policies, so that they receive automatic updates to those policies as they become available.
Policy Decision and Enforcement
Run-time policy decision and enforcement is done by the other applicable OpenECOMP subsystems. For example, policy rules for data collection are enforced by the data collection functionality of DCAE. Analytic policy rules, identification of anomalous or abnormal conditions, and publication of events signaling detection of such conditions are enforced by DCAE analytic applications. Policy rules for associated remedial actions, or for further diagnostics, are enforced by the correct component in a control loop such as the MSO, a Controller, or DCAE.
Figure 9 shows Policy Creation on the left, Policy Repository & Distribution at the bottom, and Policy use on the right (e.g., in Control Loops, or in VNFs). As shown in Figure 9, Policy Creation is in close association with Service & Design Creation (SDC).
Policy Unification and Organization
Because the policy framework is expandable and multipurpose, it might contain many types of policies. Policies can be organized according to whatever dimensions are useful. Users can define attributes that specify the scope of policies, and these attributes can be extended to the policy-enabled functions and components. Attributes can be defined for each dimension. Useful policy organizing dimensions might include:
- Policy type or category (taxonomical)
- Policy ownership or administrative domain
- Geographic area or location,
- Technology type
- Policy language and version
- Security level or other security-related values, specifiers, or limiters
Policy Use
At runtime, policies that were previously distributed to policy-enabled components will be used by those components to control or influence their functionality and behavior, including any actions that are taken.
By then setting values for these attributes, Policy Scope can be used to specify the precise Policy “scope” of: (A) Policy events or requests/triggers to allow each event/request to self-indicate its scope, e.g., which can then be examined by a suitable function for specifics of routing/delivery, (B) Policy decision/enforcement functions or other Policy functions to allow each Policy function to self-indicate its scope of decision making, enforcement, or other capabilities, (C) Virtual Functions of any type for auto-attachment to the appropriate Policy Framework and distribution mechanism instances, and most importantly to (D) individual policies to aid in management and distribution of the policies.
7.5 Policy Technologies
D2 Policy will utilize rather than replace various technologies; examples of possible policy areas are shown in the following table. These will be used, e.g., via translation capabilities, to achieve the best possible solution that takes advantage of helpful technologies while still providing in effect a single D2.0 Policy “brain.”
many cases, those policies will be utilized to make decisions, where these decisions will often be conditional upon the current situation.
A major example of this approach is the feedback/control loop pattern driven by DCAE. Many specific control loops can be defined. In a particular control loop, each participant (e.g., orchestrator, controller, DCAE, virtual function) will have received policies determining how it should act as part of that loop. All of the policies for that loop will have been previously created together, ensuring proper coordinated closed-loop action. DCAE can receive specific policies for data collection (e.g., what data to collect, how to collect, and how often), data analysis (e.g., what type and depth of analysis to perform), and signature and event publishing (e.g., what analysis results to look for as well as the specifics of the event to be published upon detecting those results). Remaining components of the loop (e.g., orchestrators, controllers, etc.) can receive specific policies determining actions to be taken upon receiving the triggered event from DCAE. Each loop participant could also receive policies determining the specific events to which it subscribes.