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| -rw-r--r-- | docs/architecture/architecture.rst | 72 | ||||
| -rw-r--r-- | docs/conf.py | 2 |
2 files changed, 60 insertions, 14 deletions
diff --git a/docs/architecture/architecture.rst b/docs/architecture/architecture.rst index 9a587c50..f5fbc8b9 100644 --- a/docs/architecture/architecture.rst +++ b/docs/architecture/architecture.rst @@ -32,7 +32,7 @@ benefit from the ONAP policy Framework because they can use the capabilities of their policies rather than embedding the decision making in their applications. The Policy Framework is deployment agnostic, it manages Policy Execution (in PDPs) and Enforcement (in PEPs) regardless -of how the PDPs and PEPs are deployed. This allows policy execution and enforcement can be deployed in a manner that +of how the PDPs and PEPs are deployed. This allows policy execution and enforcement to be deployed in a manner that meets the performance requirements of a given application or use case. In one deployment, policy execution could be deployed in a separate executing entity in a Docker container. In another, policy execution could be co-deployed with an application to increase performance. An example of co-deployment is the Drools PDP Control Loop image, which is a @@ -41,7 +41,8 @@ Docker image that combines the ONAP Drools use case application and dependencies The ONAP Policy Framework architecture separates policies from the platform that is supporting them. The framework supports development, deployment, and execution of any type of policy in ONAP. The Policy Framework is metadata (model) driven so that policy development, deployment, and execution is as flexible as possible and can support modern rapid -development ways of working such as DevOps. A metadata driven approach also allows the amount of programmed support +development ways of working such as `DevOps +<https://en.wikipedia.org/wiki/DevOps>`__. A metadata driven approach also allows the amount of programmed support required for policies to be reduced or ideally eliminated. We have identified five capabilities as being essential for the framework: @@ -66,21 +67,66 @@ policy specification. The ONAP Policy Framework complies with the `TOSCA approach for policies, see the :ref:`TOSCA Policy Primer <tosca-label>` for more information on how policies are modeled in TOSCA. -1. A Policy Type is a general implementation of a policy for a feature. For example, a Policy Type could be written to - manage Service Level Agreements for VPNs. The Policy Type is designed by a domain expert, who specifies the - parameters, triggers, and actions that the Policy Type will have. The implementation (the logic, rules, and tasks of - the Policy Type) is implemented by a skilled policy developer in consultation with domain experts. + 1. A *Policy Type* describes the properties, targets, and triggers that the policy for a feature can have. A Policy type is + implementation independent. It is the metadata that specifies: - a. For example, the VPN Policy Type is used to create VPN policies for a bank network, a car dealership network, or a - university with many campuses. + - the *configuration* data that the policy can take. The Policy Type describes each property that a policy of a + given type can take. A Policy Type definition also allows the default value, optionality, and the ranges of properties + to be defined. - b. In ONAP, specific ONAP Policy Types are used to create specific policies that drive the ONAP Platform and - Components. + - the *targets* such as network element types, functions, services, or resources on which a policy of the given type + can act. -2. A Policy is created by configuring a Policy Type with parameters. For example, the SLA values in the car dealership - VPN policy for a particular dealership are configured with values appropriate for the expected level of activity in - that dealership. + - the *triggers* such as the event type, filtered event, scheduled trigger, or conditions that can activate a policy + of the given type. + Policy Types are hierarchical, A Policy Type can inherit from a parent Policy Type, inheriting the properties, targets, + and triggers of its parent. Policy Types are developed by domain experts in consultation with the developers that + implement the logic and rules for the Policy Type. + + 2. A *Policy* is defined using a Policy Type. The Policy defines: + + - the values for each property of the policy type + - the specific targets (network elements, functions, services, resources) on which this policy will act + - the specific triggers that trigger this policy. + + 3. A *Policy Type Implementation* or *Raw Policy*, is the logic that implements the policy. It is implemented by a + skilled policy developer in consultation with domain experts. The implementation has software that reads the Policy + Type and parses the incoming confiuration properties. The software has domain logic that is triggered when one of the + triggers described in the Policy Type occurs. The software logic executes and acts on the targets specified in the + Policy Type. + + +For example, a Policy Type could be written to describe how to manage Service Level Agreements for VPNs. The VPN Policy +Type can be used to create VPN policies for a bank network, a car dealership network, or a university with many campuses. +The Policy Type has two parameters: + + - The *maximumDowntime* parameter allows the maximum downtime allowed per year to be specified + - The *mitigationStrategy* parameter allows one of three strategies to be selected for downtime breaches + + - *allocateMoreResources*, which will automatically allocate more resources to mitigate the problem + - *report*, which report the downtime breach to a trouble ticketing system + - *ignore*, which logs the breach and takes no further action + +The Policy Type defines a trigger event, an event that is received from an analytics system when the maximum downtime +value for a VPN is breached. The target of the policy type is an instance of the VPN service. + +The Policy Type Implementation is developed that can configure the maximum downtime parameter in an analytics system, +can receive a trigger from the analytics system when the maximum downtime is breached, and that can either request more +resources, report an issue to a trouble ticketing system, and can log a breach. + +VPN Policies are created by specifying values for the properties, triggers, and targets specifed in VPN Policy Type. + +In the case of the bank network, the *maximumDowntime* threshold is specified as 5 minutes downtime per year and the +*mitigationStrategy* is defined as *allocateMoreResources*, and the target is specified as being the bank's VPN service +ID. When a breach is detected by the analytics system, the policy is executed, the target is identified as being the +bank's network, and more resources are allocated by the policy. + +For the car dealership VPN policy, a less stringent downtime threshold of 60 minutes per year is specified, and the +mitigation strategy is to issue a trouble ticket. The university network is best effort, so a downtime of 4 days per +year is specified. Breaches are logged and mitigated as routine network administration tasks. + +In ONAP, specific ONAP Policy Types are used to create specific policies that drive the ONAP Platform and Components. For more detailed information on designing Policy Types and developing an implementation for that policy type, see :ref:`Policy Design and Development <design-label>`. diff --git a/docs/conf.py b/docs/conf.py index 526ec693..8f40e8b8 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -12,4 +12,4 @@ intersphinx_mapping = {} html_last_updated_fmt = '%d-%b-%y %H:%M' def setup(app): - app.add_stylesheet("css/ribbon_onap.css")
\ No newline at end of file + app.add_stylesheet("css/ribbon_onap.css") |