Policy Framework Architecture


This document describes the ONAP Policy Framework. It lays out the architecture of the framework and shows the APIs provided to other components that interwork with the framework. It describes the implementation of the framework, mapping out the components, software structure, and execution ecosystem of the framework.


1. Overview

The ONAP Policy Framework is a comprehensive policy design, deployment, and execution environment. The Policy Framework is the decision making component in an ONAP system. It allows you to specify, deploy, and execute the governance of the features and functions in your ONAP system, be they closed loop, orchestration, or more traditional open loop use case implementations. The Policy Framework is the component that is the source of truth for all policy decisions.

One of the most important goals of the Policy Framework is to support Policy Driven Operational Management during the execution of ONAP control loops at run time. In addition, use case implementations such as orchestration and control benefit from the ONAP policy Framework because they can use the capabilities of the framework to manage and execute 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 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 Docker image that combines the ONAP Drools use case application and dependencies with the Drools PDP engine.

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 required for policies to be reduced or ideally eliminated.

We have identified five capabilities as being essential for the framework:

  1. Most obviously, the framework must be capable of being triggered by an event or invoked, and making decisions at run time.

  2. It must be deployment agnostic; capable of managing policies for various Policy Decision Points (PDPs) or policy engines.

  3. It must be metadata driven, allowing policies to be deployed, modified, upgraded, and removed as the system executes.

  4. It must provide a flexible model driven policy design approach for policy type programming and specification of policies.

  5. It must be extensible, allowing straightforward integration of new PDPs, policy formats, and policy development environments.

Another important aim of the architecture of a model driven policy framework is that it enables much more flexible policy specification. The ONAP Policy Framework complies with the TOSCA modelling approach for policies, see the TOSCA Policy Primer for more information on how policies are modeled in TOSCA.

  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:

  • 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.

  • the targets such as network element types, functions, services, or resources on which a policy of the given type can act.

  • 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.

  1. 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.

  1. 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 configuration 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 specified 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 Policy Design and Development.

The ONAP Policy Framework for building, configuring and deploying PDPs is extendable. It allows the use of ONAP PDPs as is, the extension of ONAP PDPs, and lastly provides the capability for users to create and deploy their own PDPs. The ONAP Policy Framework provides distributed policy management for all policies in ONAP at run time. Not only does this provide unified policy access and version control, it provides life cycle control for policies and allows detection of conflicts across all policies running in an ONAP installation.

2. Architecture

The diagram below shows the architecture of the ONAP Policy Framework at its highest level.


The PolicyAPI component implements the functionality for CRUD of policy types and policies. PolicyAdministration is responsible for the deployment life cycle of policies as well as interworking with the mechanisms required to orchestrate the nodes and containers on which policies run. PolicyAdministration is also responsible for the administration of policies at run time; ensuring that policies are available to users, that policies are executing correctly, and that the state and status of policies is monitored. PolicyExecution is the set of PDPs running in the ONAP system and is responsible for making policy decisions and for managing the administrative state of the PDPs as directed by PolicyAdministration.

PolicyAPI provides APIs that allow creation of policy artifacts and supporting information in the policy database. PolicyAdministration reads those artifacts and the supporting information from the policy database whilst deploying policy artifacts. Once the policy artifacts are deployed, PolicyAdministration handles the run-time management of the PDPs on which the policies are running. PolicyAPI interacts with the database, and has no programmatic interface with PolicyAdministration, PolicyExecution or any other run-time ONAP components.

The diagram below shows a more detailed view of the architecture, as inspired by RFC-2753 https://tools.ietf.org/html/rfc2753 and RFC-3198 https://tools.ietf.org/html/rfc3198.


PolicyAPI provides a CRUD API for policy types and policies. The policy types and policy artifacts and their metadata (information about policies, policy types, and their interrelations) are stored in the PolicyDB. The PolicyDevGUI, PolicyDistribution, and other applications such as CLAMP can use the PolicyAPI API to create, update, delete, and read policy types and policies.

PolicyAdministration has two important functions:

  • Management of the life cycle of PDPs in an ONAP installation. PDPs register with PolicyAdministration when they come up. PolicyAdministration handles the allocation of PDPs to PDP Groups and PDP Subgroups, so that they can be managed as microservices in infrastructure management systems such as Kubernetes.

  • Management of the deployment of policies to PDPs in an ONAP installation. PolicyAdministration gives each PDP group a set of domain policies to execute.

PolicyAdministration handles PDPs and policy allocation to PDPs using asynchronous messaging over DMaaP. It provides three APIs:

  • a CRUD API for policy groups and subgroups

  • an API that allows the allocation of policies to PDP groups and subgroups to be controlled

  • an API allows policy execution to be managed, showing the status of policy execution on PDP Groups, subgroups, and individual PDPs as well as the life cycle state of PDPs

PolicyExecution is the set of running PDPs that are executing policies, logically partitioned into PDP groups and subgroups.


The figure above shows how PolicyExecution looks at run time with PDPs running in Kubernetes. A PDPGroup is a purely logical construct that collects all the PDPs that are running policies for a particular domain together. A PDPSubGroup is a group of PDPs of the same type that are running the same policies. A PDPSubGroup is deployed as a Kubernetes Deployment. PDPs are defined as Kubernetes Pods. At run time, the actual number of PDPs in each PDPSubGroup is specified in the configuration of the Deployment of that PDPSubGroup in Kubernetes. This structuring of PDPs is required because, in order to simplify deployment and scaling of PDPs in Kubernetes, we gather all the PDPs of the same type that are running the same policies together for deployment.

For example, assume we have policies for the SON (Self Organizing Network) and ACPS (Advanced Customer Premises Service) domains. For SON,we have XACML, Drools, and APEX policies, and for ACPS we have XACML and Drools policies. The table below shows the resulting PDPGroup, PDPSubGroup, and PDP allocations:

PDP Group

PDP Subgroup

Kubernetes Deployment

Kubernetes Deployment Strategy

PDPs in Pods




Always 2, be geo redundant




At Least 4, scale up on 70% load, scale down on 40% load, be geo-redundant

>= 4 PDP-D



At Least 3, scale up on 70% load, scale down on 40% load, be geo-redundant

>= 3 PDP-A




Always 2




At Least 2, scale up on 80% load, scale down on 50% load

>=2 PDP-D

For more details on PolicyAdministration APIs and management of PDPGroup and PDPSubGroup, see the documentation for Policy Administration Point (PAP) Architecture.

2.1 Policy Framework Object Model

This section describes the structure of and relations between the main concepts in the Policy Framework. This model is implemented as a common model and is used by PolicyAPI, PolicyAdministration, and PolicyExecution.


The UML class diagram above shows thePolicy Framework Object Model.

2.2 Policy Design Architecture

This section describes the architecture of the model driven system used to develop policy types and to create policies using policy types. The output of Policy Design is deployment-ready artifacts and Policy metadata in the Policy Framework database.

Policy types that are expressed via natural language or a model require an implementation that allows them to be translated into runtime policies. Some Policy Type implementations are set up and available in the platform during startup such as Control Loop Operational Policy Models, OOF placement Models, DCAE microservice models. Policy type implementations can also be loaded and deployed at run time.

2.2.1 Policy Type Design

Policy Type Design is the task of creating policy types that capture the generic and vendor independent aspects of a policy for a particular domain use case.

All policy types are specified in TOSCA service templates. Once policy types are defined and created in the system, PolicyAPI manages them and uses them to allow policies to be created from these policy types in a uniform way regardless of the domain that the policy type is addressing or the PDP technology that will execute the policy.

A PolicyTypeImpl is developed for a policy type for a certain type of PDP (for example XACML oriented for decision policies, Drools rules or Apex state machines oriented for ECA policies). While a policy type is implementation independent, a policy type implementation for a policy type is specific for the technology of the PDP on which policies that use that policy type implementation will execute. A Policy Type may have many implementations. A PolicyTypeImpl is the specification of the specific rules or tasks, the flow of the policy, its internal states and data structures and other relevant information. A PolicyTypeImpl can be specific to a particular policy type or it can be more general, providing the implementation of a class of policy types. Further, the design environment and tool chain for implementing implementations of policy types is specific to the technology of the PDP on which the implementation will run.

In the xacml-pdp and drools-pdp, an application is written for a given category of policy types. Such an application may have logic written in Java or another programming language, and may have additional artifacts such as scripts and SQL queries. The application unmarshals and marshals events going into and out of policies as well as handling the sequencing of events for interactions of the policies with other components in ONAP. For example, drools-applications handles the interactions for operational policies running in the drools PDP. In the apex-pdp, all unmarshaling, marshaling, and component interactions are captured in the state machine, logic, and configuraiton of the policy, a Java application is not used.

PolicyAPI provides the RESTful Policy Design API, which allows other components to query policy types, Those components can then create policies that specify values for the properties, triggers, and targets specified in a policy type. This API is used by components such as CLAMP and PolicyDistribution to create policies from policy types.

Consider a policy type created for managing faults on vCPE equipment in a vendor independent way. The policy type implementation captures the generic logic required to manage the faults and specifies the vendor specific information that must be supplied to the type for specific vendor vCPE VFs. The actual vCPE policy that is used for managing particular vCPE equipment is created by setting the properties specified in the policy type for that vendor model of vCPE. Generating Policy Types

It is possible to generate policy types using MDD (Model Driven Development) techniques. Policy types are expressed using a DSL (Domain Specific Language) or a policy specification environment for a particular application domain. For example, policy types for specifying SLAs could be expressed in a SLA DSL and policy types for managing SON features could be generated from a visual SON management tool. The ONAP Policy framework provides an API that allows tool chains to create policy types, see the Policy Design and Development page.


A GUI implementation in another ONAP component (a PolicyTypeDesignClient) may use the API_User API to create and edit ONAP policy types. Programming Policy Type Implementations

For skilled developers, the most straightforward way to create a policy type is to program it. Programming a policy type might simply mean creating and editing text files, thus manually creating the TOSCA Policy Type YAML file and the policy type implementation for the policy type.

A more formal approach is preferred. For policy type implementations, programmers use a specific Eclipse project type for developing each type of implementation, a Policy Type Implementation SDK. The project is under source control in git. This Eclipse project is structured correctly for creating implementations for a specific type of PDP. It includes the correct POM files for generating the policy type implementation and has editors and perspectives that aid programmers in their work

2.2.2 Policy Design

The PolicyCreation function of PolicyAPI creates policies from a policy type. The information expressed during policy type design is used to parameterize a policy type to create an executable policy. A service designer and/or operations team can use tooling that reads the TOSCA Policy Type specifications to express and capture a policy at its highest abstraction level. Alternatively, the parameter for the policy can be expressed in a raw JSON or YAML file and posted over the policy design API described on the Policy Design and Development page.

A number of mechanisms for policy creation are supported in ONAP. The process in PolicyAPI for creating a policy is the same for all mechanisms. The most general mechanism for creating a policy is using the RESTful Policy Design API, which provides a full interface to the policy creation support of PolicyAPI. This API may be exercised directly using utilities such as curl.

In future releases, the Policy Framework may provide a command line tool that will be a loose wrapper around the API. It may also provide a general purpose Policy GUI in the ONAP Portal for policy creation, which again would be a general purpose wrapper around the policy creation API. The Policy GUI would interpret any TOSCA Model that has been loaded into it and flexibly presents a GUI for a user to create policies from. The development of these mechanisms will be phased over a number of ONAP releases.

A number of ONAP components use policy in manners which are specific to their particular needs. The manner in which the policy creation process is triggered and the way in which information required to create a policy is specified and accessed is specialized for these ONAP components.

For example, CLAMP provides a GUI for creation of Control Loop policies, which reads the Policy Type associated with a control loop, presents the properties as fields in its GUI, and creates a policy using the property values entered by the user.

The following subsections outline the mechanisms for policy creation and modification supported by the ONAP Policy Framework. Policy Design in the ONAP Policy Framework

Policy creation in PolicyAPI follows the general sequence shown in the sequence diagram below. An API_USER is any component that wants to create a policy from a policy type. PolicyAPI supplies a REST interface that exposes the API and also provides a command line tool and general purpose client that wraps the API.


An API_User first gets a reference to and the metadata for the Policy type for the policy they want to work on from PolicyAPI. PolicyAPI reads the metadata and artifact for the policy type from the database. The API_User then asks for a reference and the metadata for the policy. PolicyAPI looks up the policy in the database. If the policy already exists, PolicyAPI reads the artifact and returns the reference of the existing policy to the API_User with the metadata for the existing policy. If the policy does not exist, PolicyAPI informs the API_User.

The API_User may now proceed with a policy specification session, where the parameters are set for the policy using the policy type specification. Once the API_User is happy that the policy is completely and correctly specified, it requests PolicyAPI to create the policy. PolicyAPI creates the policy, stores the created policy artifact and its metadata in the database. Model Driven VF (Virtual Function) Policy Design via VNF SDK Packaging

VF vendors express policies such as SLA, Licenses, hardware placement, run-time metric suggestions, etc. These details are captured within the VNF SDK and uploaded into the SDC Catalog. The SDC Distribution APIs are used to interact with SDC. For example, SLA and placement policies may be captured via TOSCA specification. License policies can be captured via TOSCA or an XACML specification. Run-time metric vendor recommendations can be captured via the VES Standard specification.

The sequence diagram below is a high level view of SDC-triggered concrete policy generation for some arbitrary entity EntityA. The parameters to create a policy are read from a TOSCA Policy specification read from a CSAR received from SDC.


PolicyDesign uses the PolicyDistribution component for managing SDC-triggered policy creation and update requests. PolicyDistribution is an API_User, it uses the Policy Design API for policy creation and update. It reads the information it needs to populate the policy type from a TOSCA specification in a CSAR received from SDC and then uses this information to automatically generate a policy.

Note that SDC provides a wrapper for the SDC API as a Java Client and also provides a TOSCA parser. See the documentation for the Policy Distribution Component.

In Step 4 above, the PolicyDesign must download the CSAR file. If the policy is to be composed from the TOSCA definition, it must also parse the TOSCA definition.

In Step 11 above, the PolicyDesign must send back/publish status events to SDC such as DOWNLOAD_OK, DOWNLOAD_ERROR, DEPLOY_OK, DEPLOY_ERROR, NOTIFIED. Scripted Model Driven Policy Design

Service policies such as optimization and placement policies can be specified as a TOSCA Policy at design time. These policies use a TOSCA Policy Type specification as their schemas. Therefore, scripts can be used to create TOSCA policies using TOSCA Policy Types.


One straightforward way of generating policies from Policy types is to use commands specified in a script file. A command line utility such as curl is an API_User. Commands read policy types using the Policy Type API, parse the policy type and uses the properties of the policy type to prepare a TOSCA Policy. It then issues further commands to use the Policy API to create policies.

2.2.3 Policy Design Process

All policy types must be certified as being fit for deployment prior to run time deployment. Where design is executed using the SDC application, it is assumed the life cycle being implemented by SDC certifies any policy types that are declared within the ONAP Service CSAR. For other policy types and policy type implementations, the life cycle associated with the applied software development process suffices. Since policy types and their implementations are designed and implemented using software development best practices, they can be utilized and configured for various environments (eg. development, testing, production) as desired.

2.3 Policy Runtime Architecture

The Policy Framework Platform components are themselves designed as microservices that are easy to configure and deploy via Docker images and K8S both supporting resiliency and scalability if required. PAPs and PDPs are deployed by the underlying ONAP management infrastructure and are designed to comply with the ONAP interfaces for deploying containers.

The PAPs keep track of PDPs, support the deployment of PDP groups and the deployment of a policy set across those PDP groups. A PAP is stateless in a RESTful sense. Therefore, if there is more than one PAP deployed, it does not matter which PAP a user contacts to handle a request. The PAP uses the database (persistent storage) to keep track of ongoing sessions with PDPs. Policy management on PDPs is the responsibility of PAPs; management of policy sets or policies by any other manner is not permitted.

In the ONAP Policy Framework, the interfaces to the PDP are designed to be as streamlined as possible. Because the PDP is the main unit of scalability in the Policy Framework, the framework is designed to allow PDPs in a PDP group to arbitrarily appear and disappear and for policy consistency across all PDPs in a PDP group to be easily maintained. Therefore, PDPs have just two interfaces; an interface that users can use to execute policies and interface to the PAP for administration, life cycle management and monitoring. The PAP is responsible for controlling the state across the PDPs in a PDP group. The PAP interacts with the Policy database and transfers policy sets to PDPs, and may cache the policy sets for PDP groups.

See also Section 2 of the Policy Design and Development page, where the mechanisms for PDP Deployment and Registration with PAP are explained.

2.3.1 Policy Framework Services

The ONAP Policy Framework follows the architectural approach for microservices recommended by the ONAP Architecture Subcommittee.

The ONAP Policy Framework uses an infrastructure such as Kubernetes Services to manage the life cycle of Policy Framework executable components at runtime. A Kubernetes service allows, among other parameters, the number of instances (pods in Kubernetes terminology) that should be deployed for a particular service to be specified and a common endpoint for that service to be defined. Once the service is started in Kubernetes, Kubernetes ensures that the specified number of instances is always kept running. As requests are received on the common endpoint, they are distributed across the service instances. More complex call distribution and instance deployment strategies may be used; please see the Kubernetes Services documentation for those details.

If, for example, a service called policy-pdpd-control-loop is defined that runs 5 PDP-D instances. The service has the end point https://policy-pdpd-control-loop.onap/<service-specific-path>. When the service is started, Kubernetes spins up 5 PDP-Ds. Calls to the end point https://policy-pdpd-control-loop.onap/<service-specific-path> are distributed across the 5 PDP-D instances. Note that the .onap part of the service endpoint is the namespace being used and is specified for the full ONAP Kubernetes installation.

The following services will be required for the ONAP Policy Framework:






The PAP service, used for policy administration and deployment. See Policy Design and Development for details of the API for this service



A PDP service is defined for each PDP group. A PDP group is identified by the domain on which it operates.

For example, there could be two PDP-X domains, one for admission policies for ONAP proper and another for admission policies for VNFs of operator Supacom. Two PDP-X services are defined:






There is one and only one PAP service, which handles policy deployment, administration, and monitoring for all policies in all PDPs and PDP groups in the system. There are multiple PDP services, one PDP service for each domain for which there are policies.

2.3.2 The Policy Framework Information Structure

The following diagram captures the relationship between Policy Framework concepts at run time.


There is a one to one relationship between a PDP SubGroup, a Kubernetes PDP service, and the set of policies assigned to run in the PDP subgroup. Each PDP service runs a single PDP subgroup with multiple PDPs, which executes a specific Policy Set containing a number of policies that have been assigned to that PDP subgroup. Having and maintaining this principle makes policy deployment and administration much more straightforward than it would be if complex relationships between PDP services, PDP subgroups, and policy sets.

The topology of the PDPs and their policy sets is held in the Policy Framework database and is administered by the PAP service.


The diagram above gives an indicative structure of the run time topology information in the Policy Framework database. Note that the PDP_SUBGROUP_STATE and PDP_STATE fields hold state information for life cycle management of PDP groups and PDPs.

2.3.3 Startup, Shutdown and Restart

This section describes the interactions between Policy Framework components themselves and with other ONAP components at startup, shutdown and restart. PAP Startup and Shutdown

The sequence diagram below shows the actions of the PAP at startup.


The PAP is the run time point of coordination for the ONAP Policy Framework. When it is started, it initializes itself using data from the database. It then waits for periodic PDP status updates and for administration requests.

PAP shutdown is trivial. On receipt or a shutdown request, the PAP completes or aborts any ongoing operations and shuts down gracefully. PDP Startup and Shutdown

The sequence diagram below shows the actions of the PDP at startup. See also Section 4 of the Policy Design and Development page for the API used to implement this sequence.


At startup, the PDP initializes itself. At this point it is in PASSIVE mode. The PDP begins sending periodic Status messages to the PAP. The first Status message initializes the process of loading the correct Policy Set on the PDP in the PAP.

On receipt or a shutdown request, the PDP completes or aborts any ongoing policy executions and shuts down gracefully.

2.3.4 Policy Execution

Policy execution is the execution of a policy in a PDP. Policy enforcement occurs in the component that receives a policy decision.


Policy execution can be synchronous or asynchronous. In synchronous policy execution, the component requesting a policy decision requests a policy decision and waits for the result. The PDP-X and PDP-A implement synchronous policy execution. In asynchronous policy execution, the component that requests a policy decision does not wait for the decision. Indeed, the decision may be passed to another component. The PDP-D and PDP-A implement asynchronous polic execution.

Policy execution is carried out using the current life cycle mode of operation of the PDP. While the actual implementation of the mode may vary somewhat between PDPs of different types, the principles below hold true for all PDP types:

Lifecycle Mode



Policy execution is always rejected irrespective of PDP type.


Policy execution is executed in the live environment by the PDP.


Policy execution proceeds, but changes to domain state or context are not carried out. The PDP returns an indication that it is running in SAFE mode together with the action it would have performed if it was operating in ACTIVE mode. The PDP type and the policy types it is running must support SAFE mode operation.


Policy execution proceeds and changes to domain and state are carried out in a test or sandbox environment. The PDP returns an indication it is running in TEST mode together with the action it has performed on the test environment. The PDP type and the policy types it is running must support TEST mode operation.

* SAFE Mode and TEST Mode will be implemented in future versions of the Policy Framework.

2.3.5 Policy Lifecycle Management

Policy lifecycle management manages the deployment and life cycle of policies in PDP groups at run time. Policy sets can be deployed at run time without restarting PDPs or stopping policy execution. PDPs preserve state for minor/patch version upgrades and rollbacks. Load/Update Policies on PDP

The sequence diagram below shows how policies are loaded or updated on a PDP.


This sequence can be initiated in two ways; from the PDP or from a user action.

  1. A PDP sends regular status update messages to the PAP. If this message indicates that the PDP has no policies or outdated policies loaded, then this sequence is initiated

  2. A user may explicitly trigger this sequence to load policies on a PDP

The PAP controls the entire process. The PAP reads the current PDP metadata and the required policy and policy set artifacts from the database. It then builds the policy set for the PDP. Once the policies are ready, the PAP sets the mode of the PDP to PASSIVE. The Policy Set is transparently passed to the PDP by the PAP. The PDP loads all the policies in the policy set including any models, rules, tasks, or flows in the policy set in the policy implementations.

Once the Policy Set is loaded, the PAP orders the PDP to enter the life cycle mode that has been specified for it (ACTIVE/SAFE*/TEST*). The PDP begins to execute policies in the specified mode (see section 2.3.4).

* SAFE Mode and TEST Mode will be implemented in future versions of the Policy Framework. Policy Rollout

A policy set steps through a number of life cycle modes when it is rolled out.


The user defines the set of policies for a PDP group. It is deployed to a PDP group and is initially in PASSIVE mode. The user sets the PDP Group into TEST mode. The policies are run in a test or sandboxed environment for a period of time. The test results are passed back to the user. The user may revert the policy set to PASSIVE mode a number of times and upgrade the policy set during test operation.

When the user is satisfied with policy set execution and when quality criteria have been reached for the policy set, the PDP group is set to run in SAFE mode. In this mode, the policies run on the target environment but do not actually exercise any actions or change any context in the target environment. Again, as in TEST mode, the operator may decide to revert back to TEST mode or even PASSIVE mode if issues arise with a policy set.

Finally, when the user is satisfied with policy set execution and when quality criteria have been reached, the PDP group is set into ACTIVE state and the policy set executes on the target environment. The results of target operation are reported. The PDP group can be reverted to SAFE, TEST, or even PASSIVE mode at any time if problems arise.

* SAFE Mode and TEST Mode will be implemented in future versions of the Policy Framework. In current versions, policies transition directly from PASSIVE mode to ACTIVE mode. Policy Upgrade and Rollback

There are a number of approaches for managing policy upgrade and rollback. Upgrade and rollback will be implemented in future versions of the Policy Framework.

The most straightforward approach is to use the approach described in section Policy Rollout for upgrading and rolling back policy sets. In order to upgrade a policy set, one follows the process in Policy Rollout with the new policy set version. For rollback, one follows the process in Policy Rollout with the older policy set, most probably setting the old policy set into ACTIVE mode immediately. The advantage of this approach is that the approach is straightforward. The obvious disadvantage is that the PDP group is not executing on the target environment while the new policy set is in PASSIVE, TEST, and SAFE mode.

A second manner to tackle upgrade and rollback is to use a spare-wheel approach. An special upgrade PDP group service is set up as a K8S service in parallel with the active one during the upgrade procedure. The spare wheel service is used to execute the process described in Policy Rollout. When the time comes to activate the policy set, the references for the active and spare wheel services are simply swapped. The advantage of this approach is that the down time during upgrade is minimized, the spare wheel PDP group can be abandoned at any time without affecting the in service PDP group, and the upgrade can be rolled back easily for a period simply by preserving the old service for a time. The disadvantage is that this approach is more complex and uses more resources than the first approach.

A third approach is to have two policy sets running in each PDP, an active set and a standby set. However such an approach would increase the complexity of implementation in PDPs significantly.

2.3.6 Policy Monitoring

PDPs provide a periodic report of their status to the PAP. All PDPs report using a standard reporting format that is extended to provide information for specific PDP types. PDPs provide at least the information below:






Time the report record was generated


The number of execution invocations the PDP has processed since the last report


The time taken to process the last execution invocation


The average time taken to process an invocation since the last report


The start time of the PDP


The length of time the PDP has been executing


Real time information on running policies.

* SAFE Mode and TEST Mode will be implemented in future versions of the Policy Framework.

Currently, policy monitoring is supported by PAP and by pdp-apex. Policy monitoring for all PDPs will be supported in future versions of the Policy Framework.

2.3.7 PEP Registration and Enforcement Guidelines

In ONAP there are several applications outside the Policy Framework that enforce policy decisions based on models provided to the Policy Framework. These applications are considered Policy Enforcement Engines (PEP) and roles will be provided to those applications using AAF/CADI to ensure only those applications can make calls to the Policy Decision APIs. Some example PEPs are: DCAE, OOF, and SDNC.

See Section 3.4 of the Policy Design and Development for more information on the Decision APIs.

2.3.8 Multi-Cluster Support

Multi-cluster support was added to the Policy Framework during the Istanbul release, enabling redundancy, load-sharing, and inter-site failover.

Note: multi-cluster support has only been minimally tested, and is thus still experimental. Shared DB

Multi-cluster support requires a shared DB. Rather than spinning up a separate DB for each cluster, all of the clusters are pointed to a common DB. Policy-API adds policy types and policies, while Policy-PAP manages PDP Groups and Subgroups, as well as policy deployments. The information in these tables is not segregated, but is, instead, shared across the API and PAP components across all of the clusters.

../_images/MCSharedDB.svg DMaaP Arrangement

As in prior releases, communication between the PAPs and PDPs still takes place via DMaaP. Two arrangements, described below, are supported. Local DMaaP

In this arrangement, each cluster is associated with its own, local DMaaP, and communication only happens between PAPs and PDPs within the same cluster.


The one limitation with this approach is that, when a PAP in cluster A deploys a policy, PAP is only able to inform the PDPs in the local cluster; the PDPs in the other clusters are not made aware of the new deployment until they generate a heartbeat, at which point, their local PAP will inform them of the new deployment. The same is true of changes made to the state of a PDP Group; changes only propagate to PDPs in other clusters in response to heartbeats generated by the PDPs.

../_images/MCLocalHB.svg Shared DMaaP

In this arrangement, the PAPs and PDPs in all of the clusters are pointed to a common DMaaP. Because the PAP and PDPs all communicate via the same DMaaP, when a PAP deploys a policy, all PDPs are made aware, rather than having to wait for a heartbeat.

../_images/MCSharedDmaap.svg Missed Heartbeat

To manage the removal of terminated PDPs from the DB, a record, containing a “last-updated” timestamp, is maintained within the DB for each PDP. Whether using a local or shared DMaaP, any PAP receiving a message from a PDP will update the timestamp in the associated record, thus keeping the records “current”.


Periodically, each PAP will sweep the DB of PDP records whose timestamp has not been updated recently. The frequency with which it is checked is based on the value of the “heartbeatMs” configuration parameter, with a record considered expired if no heartbeat has been received for three cycles.


3. APIs Provided by the Policy Framework

See the Policy Design and Development page.

4. Terminology

PAP (Policy Administration Point)

A component that administers and manages policies

PDP (Policy Deployment Point)

A component that executes a policy artifact (One or many?)


A specific type of PDP

PDP Group

A group of PDPs that execute the same set of policies

Policy Development

The development environment for policies

Policy Type

A generic prototype definition of a type of policy in TOSCA, see the TOSCA Policy Primer


An executable policy defined in TOSCA and created using a Policy Type, see the TOSCA Policy Primer

Policy Set

A set of policies that are deployed on a PDP group. One and only one Policy Set is deployed on a PDP group

End of Document