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+.. This work is licensed under a Creative Commons Attribution 4.0 International License.
+.. http://creativecommons.org/licenses/by/4.0
+.. SPDX-License-Identifier CC-BY-4.0
+.. (c) optionally add copywriters name
+
+
+================================================================
+Auto User Guide: Use Case 2 Resiliency Improvements Through ONAP
+================================================================
+
+This document provides the release notes for Fraser release of Auto,
+specifically for Use Case 2: Resiliency Improvements Through ONAP.
+
+.. contents::
+   :depth: 3
+   :local:
+
+
+Description
+===========
+
+This use case illustrates VNF failure recovery time reduction with ONAP, thanks to its automated monitoring and management.
+It simulates an underlying problem (failure, stress, etc.: any adverse condition in the network that can impact VNFs),
+tracks a VNF, and measures the amount of time it takes for ONAP to restore the VNF functionality. 
+
+The benefit for NFV edge service providers is to assess what degree of added VIM+NFVI platform resilience for VNFs is obtained by
+leveraging ONAP closed-loop control, vs. VIM+NFVI self-managed resilience (which may not be aware of the VNF or the corresponding
+end-to-end Service, but only of underlying resources such as VMs and servers).
+
+Preconditions:
+#. hardware environment in which Edge cloud may be deployed
+#. Edge cloud has been deployed and is ready for operation
+#. ONAP has been deployed onto a cloud and is interfaced (i.e. provisioned for API access) to the Edge cloud
+#. Components of ONAP have been deployed on the Edge cloud as necessary for specific test objectives
+
+In future releases, Auto Use cases will also include the deployment of ONAP (if not already installed), the deployment
+of test VNFs (pre-existing VNFs in pre-existing ONAP can be used in the test as well), the configuration of ONAP for
+monitoring these VNFs (policies, CLAMP, DCAE), in addition to the test scripts which simulate a problem and measures recovery time.
+
+Different types of problems can be simulated, hence the identification of multiple test cases corresponding to this use case,
+as illustrated in this diagram:
+
+.. image:: auto-UC02-testcases.jpg
+
+
+Test execution high-level description
+=====================================
+
+The following two MSCs (Message Sequence Charts) show the actors and high-level interactions.
+
+The first MSC shows the preparation activities (assuming the hardware, network, cloud, and ONAP have already been installed):
+onboarding and deployment of VNFs (via ONAP portal and modules in sequence: SDC, VID, SO), and ONAP configuration
+(policy framework, closed-loops in CLAMP, activation of DCAE).
+
+.. image:: auto-UC02-preparation.jpg
+
+The second MSC illustrates the pattern of all test cases for the Resiliency Improvements:
+* simulate the chosen problem (a.k.a. a "Challenge") for this test case, for example suspend a VM which may be used by a VNF
+* start tracking the target VNF of this test case
+* measure the ONAP-orchestrated VNF Recovery Time
+* then the test stops simulating the problem (for example: resume the VM that was suspended),
+
+In parallel, the MSC also shows the sequence of events happening in ONAP, thanks to its configuration to provide Service
+Assurance for the VNF.
+
+.. image:: auto-UC02-pattern.jpg
+
+
+Test design: data model, implementation modules
+===============================================
+
+The high-level design of classes shows the identification of several entities:
+* Test Case: as identified above, each is a special case of the overall use case (e.g., categorized by challenge type)
+* Test Definition: gathers all the information necessary to run a certain test case
+* Metric Definition: describes a certain metric that may be measured, in addition to Recovery Time
+* Challenge Definition: describe the challenge (problem, failure, stress, ...) simulated by the test case
+* Recipient: entity that can receive commands and send responses, and that is queried by the Test Definition or Challenge Definition
+(a recipient would be typically a management service, with interfaces (CLI or API) for clients to query)
+* Resources: with 3 types (VNF, cloud virtual resource such as a VM, physical resource such as a server)
+
+Three of these entities have execution-time corresponding classes:
+* Test Execution, which captures all the relevant data of the execution of a Test Definition
+* Challenge Execution, which captures all the relevant data of the execution of a Challenge Definition
+* Metric Value, which captures the a quantitative measurement of a Metric Definition (with a timestamp)
+
+.. image:: auto-UC02-data1.jpg
+
+The following diagram illustrates an implementation-independent design of the attributes of these entities:
+.. image:: auto-UC02-data2.jpg
+
+This next diagram shows the Python classes and attributes, as implemented by this Use Case (for all test cases):
+
+.. image:: auto-UC02-data3.jpg
+
+Test definition data is stored in serialization files (Python pickles), while test execution data is stored in CSV
+files, for easier post-analysis.
+
+The module design is straightforward: functions and classes for managing data, for interfacing with recipients,
+for executing tests, and for interacting with the test user (choosing a Test Definition, showing the details
+of a Test Definition, starting the execution).
+
+.. image:: auto-UC02-module1.jpg
+
+This last diagram shows the test user menu functions:
+
+.. image:: auto-UC02-module2.jpg
+
+In future releases of Auto, testing environments such as FuncTest and Yardstick might be leveraged.
+
+Also, anonymized test results could be collected from users willing to share them, and aggregates could be
+maintained as benchmarks.
+
+
+
+
+
+
+
+