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  • Upgrade and changes of the configuration data of participants
  • Addition of or removal of participants in an Control Loop
  • Upgrade of software in one or more participants in an Control Loop
  • Maintenance of compatibility between participants when an update of more than one participant must be doneĀ  together to ensure compatibility, for example, when a protocol being used by two participants to communicate is upgraded

4.4.2 Scalability

The system is designed to be inherently scalable. The control loop runtime server is stateless, all state is preserved in the run time inventory in the database. When the user requests a control loop operation (such as an instantiation, activation, passivation, or an ininitialization) the server broadcasts the request to participants over DMaaP and saves details of the request to the database. The server does not directly wait for responses to requests.

When a request is broadcast on DMaaP, the request is asynchronously picked up by participants of the types required for the control loop instance and those participants manage the life cycle of its control loop elements. Periodically, each participant reports back on the status of operations it has picked up for the control loop elements it controls, together with statistics on the control loop elements over DMaaP. On reception of these participant messages, the server stores this information to its database.

The server periodically runs a supervion function, which checks the status of all existing control loop instances and the status of outstanding requests. It builds a picture of the current status of each control loop instance from the reports on the elements of the control loop instances. Once the server has a full picture, it checks that the control loop instance is in the correct state as requested by the user of the system. If the control loop is not in the correct state, the supervision function can initiate actions such aas performing retries on operations or issuing alarms or notificaitons on control loop instances.

This approach makes it easy to scale control loop LCM. As control loop instance counts increase, more than one runtime server can be deployed and REST/supervision operations on control loop instances can run in parallel. The number of participants can scale because an asynchronous broadcast mechanism is used for server-participant communication and there is no direct connection or communication channel between participants and runtime servers. Participant state, control loop instance state, and control loop element state is held in the database, so any runtime server can handle operations for any participant. Because many participants of a particular type can be deployed and participant instances can load balance control loop element instances for different control loops of many types across themselves using a mechanism such as a Kubernetes cluster.

5: Goals

5.1: MVP

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