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diff --git a/src/site-docs/adoc/fragments/apex-intro/policy-matrix.adoc b/src/site-docs/adoc/fragments/apex-intro/policy-matrix.adoc deleted file mode 100644 index b3c626522..000000000 --- a/src/site-docs/adoc/fragments/apex-intro/policy-matrix.adoc +++ /dev/null @@ -1,90 +0,0 @@ -// -// ============LICENSE_START======================================================= -// Copyright (C) 2016-2018 Ericsson. All rights reserved. -// ================================================================================ -// This file is licensed under the CREATIVE COMMONS ATTRIBUTION 4.0 INTERNATIONAL LICENSE -// Full license text at https://creativecommons.org/licenses/by/4.0/legalcode -// -// SPDX-License-Identifier: CC-BY-4.0 -// ============LICENSE_END========================================================= -// -// @author Sven van der Meer (sven.van.der.meer@ericsson.com) -// - -== APEX Policy Matrix - -APEX offers a lot of flexibility for defining, deploying, and executing policies. -Based on a theoretic model, it supports virtually any policy model and allows to translate legacy policies into the APEX execution format. -However, the most important aspect for using APEX is to decide what policy is needed, what underlying policy concepts should be used, and how the decision logic should be realized. -Once these aspects are decided, APEX can be used to execute the policies. -If the policy evolves, say from a simple decision table to a fully adaptable policy, only the policy definition requires change. -APEX supports all of that. - -The figure below shows a (non-exhaustive) matrix, which will help to decide what policy is required to solve your problem. -Read the matrix from left to right choosing one cell in each column. - -.APEX Policy Matrix -image::apex-intro/ApexPolicyMatrix.png[APEX Policy Matrix] - -The policy can support one of a number of stimuli with an associated purpose/model of the policy, for instance: - -* Configuration, i.e. what should happen. - An example is an event that states an intended network configuration and the policy should provide the detailed actions for it. - The policy can be realized for instance as an obligation policy, a promise or an intent. -* Report, i.e. something did happen. - An example is an event about an error or fault and the policy needs to repair that problem. - The policy would usually be an obligation, utility function, or goal policy. -* Monitoring, i.e. something does happen. - An example is a notification about certain network conditions, to which the policy might (or might not) react. - The policy will mitigate the monitored events or permit (deny) related actions as an obligation or authorization. -* Analysis, i.e. why did something happen. - An example is an analytic component sends insights of a situation requiring a policy to act on it. - The policy can solve the problem, escalate it, or delegate it as a refrain or delegation policy. -* Prediction, i.e. what will happen next. - An example are events that a policy uses to predict a future network condition. - The policy can prevent or enforce the prediction as an adaptive policy, a utility function, or a goal. -* Feedback, i.e. why did something happen or not happen. - Similar to analysis, but here the feedback will be in the input event and the policy needs to something with that information. - Feedback can be related to history or experience, for instance a previous policy execution. - The policy needs to be context-aware or be a meta-policy. - -Once the purpose of the policy is decided, the next step is to look into what context information the policy will require to do its job. -This can range from very simple to a lot of different information, for instance: - -* No context, nothing but a trigger event, e.g. a string or a number, is required -* Event context, the incoming event provides all information (more than a string or number) for the policy -* Policy context (read only), the policy has access to additional information related to its class but cannot change/alter them -* Policy context (read and write), the policy has access to additional information related to its class and can alter this information (for instance to record historic information) -* Global context (read only), the policy has access to additional information of any kind but cannot change/alter them -* Global context (read and write), the policy the policy has access to additional information of any kind and can alter this information (for instance to record historic information) - -The next step is to decide how the policy should do its job, i.e. what flavor it has, how many states are needed, and how many tasks. -There are many possible combinations, for instance: - -* Simple / God: a simple policy with 1 state and 1 task, which is doing everything for the decision-making. - This is the ideal policy for simple situation, e.g. deciding on configuration parameters or simple access control. -* Simple sequence: a simple policy with a number of states each having a single task. - This is a very good policy for simple decision-making with different steps. - For instance, a classic action policy (ECA) would have 3 states (E, C, and A) with some logic (1 task) in each state. -* Simple selective: a policy with 1 state but more than one task. - Here, the appropriate task (and it's logic) will be selected at execution time. - This policy is very good for dealing with similar (or the same) situation in different contexts. - For instance, the tasks can be related to available external software, or to current work load on the compute node, or to time of day. -* Selective: any number of states having any number of tasks (usually more than 1 task). - This is a combination of the two policies above, for instance an ECA policy with more than one task in E, C, and A. -* Classic directed: a policy with more than one state, each having one task, but a non-sequential execution. - This means that the sequence of the states is not pre-defined in the policy (as would be for all cases above) but calculated at runtime. - This can be good to realize decision trees based on contextual information. -* Super Adaptive: using the full potential of the APEX policy model, states and tasks and state execution are fully flexible and calculated at runtime (per policy execution). - This policy is very close to a general programming system (with only a few limitations), but can solve very hard problems. - -The final step is to select a response that the policy creates. -Possible responses have been discussed in the literature for a very long time. -A few examples are: - -* Obligation (deontic for what should happen) -* Authorization (e.g. for rule-based or other access control or security systems) -* Intent (instead of providing detailed actions the response is an intent statement and a further system processes that) -* Delegation (hand the problem over to someone else, possibly with some information or instructions) -* Fail / Error (the policy has encountered a problem, and reports it) -* Feedback (why did the policy make a certain decision) |