Exercise,Journey,Environment,Profiles,Definition / version reference,Business / instance reference,Preparation,Screen order,Actions,Expected evidence,Engineering evidence,Actual result,Result,Evidence reference,Defect / follow-up,Retest result
RG-01,Govern a subscription approval policy and its replacement,,,,,Policy code = RG_DEMO_SUBSCRIPTION; Policy name = Subscription onboarding review; Rule code = SUBSCRIPTION_ONBOARDING; Checker required = Yes for the first version; Reason = Demonstrate reviewed subscription onboarding,IAM approval rules → Rule Definitions,"1. Select the authorized policy author profile and open IAM approval rules. Inspect existing entries for SUBSCRIPTION_ONBOARDING. 2. Create the training policy with the values above and submit it with the reason. Retain the proposed change reference. 3. Attempt review using an ordinary author account, then reopen the same item as an eligible different checker. 4. Approve the policy on its originating record and reopen the effective policy. 5. Create a replacement version changing Checker required to No; submit and review that replacement. 6. Inspect an unrelated role change and its review requirements. 7. Retire the training policy through its governed action when the exercise is finished.","Show the policy proposal, reviewer decision, version 1, replacement version 2 and the originating business route. Keep the effective policy identity separate from the user or subscription identity.",RG-E01,,Awaiting client execution,,,
RG-02,Create and evaluate the score-threshold decision table,,,,,"Name / training code = Score threshold / RG_DEMO_SCORE_THRESHOLD; Definition family = Decision table; Input = score: number; Hit policy = FIRST; Rule row = score >= 700 → result = ACCEPT; Start evaluation input = {""score"":750}",Rule Design → DMN Library → Rule Definitions → Decision Logs,"1. Open Rule Design, enter the training name and choose the decision-table family. 2. Declare score as numeric, select FIRST, and add the accept row shown above. Save the draft. 3. Run the supported test/preview with score 750. Inspect the matched row and output. 4. Test 699, 700 and 701 separately. Retain the actual result for each. 5. Use the supported review/publication controls for the exact saved artifact. Reopen Rule Definitions. 6. Evaluate the eligible model again with score 750, then open the associated Decision Log. 7. If selecting an environment or alias, choose a configured reviewed binding rather than inventing an alias name.","Show the saved row, input 750, matched row, ACCEPT output, 699 no-match case, 700 boundary and the model reference in the evaluation history.",RG-E02,,Awaiting client execution,,,
RG-03,Start and complete the exercised human-review process,,,,,Process name = Training Human Review; Human stage = Review request; Assignment policy = Approved reviewer policy selected from the configured policies; Business key = RG-DEMO-HUMAN-001; Initial variables = {},BPMN Design → Process Definitions → Process Instances → Work Queue,"1. In BPMN Design build the review-to-end process and select the eligible assignment policy. Save and validate. 2. Complete the configured definition review/publication and select the eligible version in Process Definitions. 3. Start once with business key RG-DEMO-HUMAN-001. Record the returned instance reference. 4. Open Process Instances and select that instance. Inspect definition, business key, current task and assignment. 5. As the ordinary initiating profile, attempt the checker-only completion. 6. Open the same current task as an eligible checker and complete its required input. 7. Read back the instance and its history after completion.","Show the definition, the waiting instance, the denied initiator completion and the same instance completed by the eligible checker.",RG-E03,,Awaiting client execution,,,
RG-04,"Follow event correlation, a decision gateway and four review stages",,,,,"Process name = Training Routed Review; Input = Credit Score: number; Approved path sample = {""Credit Score"":750}; Default review sample = {""Credit Score"":650}; Review assignments = requester, risk, legal, finance, release; Event correlation = Configured event + scope + the instance business key; Service binding = Reviewed registered action with a completion contract",BPMN Design → Event Registry → Assignment Policies → Process Instances,"1. Prepare the process with the shown nodes and connect its reviewed decision, assignment, event and service dependencies. Validate the full graph. 2. Start the approved training version with Credit Score 750 and a unique business key. Complete the requester task. 3. Correlate the configured event using the correct scope and business key. 4. Use the permitted runtime advance action or configured worker. Inspect the returned decision and selected node. 5. Follow the service completion and inspect its result reference. 6. Start a second instance with Credit Score 650 and a different business key. Complete the requester and event steps. 7. Complete Risk, Legal, Finance and Release using the actual eligible stage identities. 8. Inspect both instance histories and compare their paths.","Show the two input payloads, event wait, gateway result, selected path, four assigned review roles and final histories.",RG-E04,,Awaiting client execution,,,
RG-05,"Complete a staged case, its required tasks and milestone",,,,,Case name = Training Evidence Case; Stage = Evidence review; Task A = Review documents; Task B = Confirm review outcome; Milestone = Evidence review completed; Business key = RG-DEMO-CASE-001; Case variables = A structured object matching the definition,Case Management Design → Case Definitions → Case Instances,"1. Create the named case, stage, two required human plan items and milestone. Configure the dependencies shown above. 2. Bind eligible assignment policies, validate, and complete the configured definition review/publication. 3. Start RG-DEMO-CASE-001 once and open its Case Instance. 4. Complete task A using the assigned reviewer and reopen the current case state. 5. Complete task B using the eligible assignee and inspect the stage/milestone timeline. 6. Prepare a separate case variant with a condition such as approved = true on task A. Start with that condition false. 7. Update the permitted case facts and use the supported sentry/advance action.","Show task A, task B’s entry dependency, the required stage, milestone, actual reviewer and final case history.",RG-E05,,Awaiting client execution,,,
RG-06,Build the exercised weighted scorecard and reconcile its total,,,,,"Name = Training Weighted Score; Factor credit = Weight 60; score 100 when credit >= 700, otherwise 20; Factor income = Weight 40; score 80 when income >= 50, otherwise 0; Bands = LOW: 0–49; HIGH: 50–100; Input = {""credit"":750,""income"":60}",Rule Design → Rule Definitions → Decision Logs,"1. Create the training scorecard in Rule Design and add the two named factors. 2. Enter each factor’s conditions and point scores, then add the LOW and HIGH bands. 3. Preview with credit 750 and income 60. Expand the factor result. 4. Save and complete the eligible artifact review/publication. Evaluate that exact version. 5. Inspect the scorecard result and associated log reference. 6. Change a factor only in a new draft version and compare the expected new total before adoption.","Show both factor definitions, weight total 100, input values, 60 + 32 = 92, HIGH band and the recorded model reference.",RG-E06,,Awaiting client execution,,,
RG-07,Connect two decisions as a chain and dependency graph,,,,,"First child = Training Credit Flag; Second child = Training Allow High; Root family = Chain or graph; Child selection = Each exact reviewed model and version/content reference; Start input = {""score"":750}",Rule Design → Artifact Graph → Rule Definitions → Decision Logs,1. Prepare and review both child tables with the shown inputs and outputs. 2. Create a chain using first followed by second; select exact child versions. 3. Preview/evaluate the eligible root with score 750. 4. Create the equivalent graph and make second depend on first. 5. Run the same input against the graph and inspect intermediate outputs. 6. Inspect root and child decisions in the available history.,"Show each child result, dependency direction, root final output and linked root/child history.",RG-E07,,Awaiting client execution,,,
RG-08,Explain four policy-combining algorithms with the same facts,,,,,"Policy deny-restricted = DENY when resource.class = restricted and subject.role != admin; Policy permit-active-read = PERMIT when action.name = read and subject.active = true; Facts = subject.role=user; subject.active=true; resource.class=restricted; action.name=read; Algorithm = DENY_OVERRIDES, PERMIT_OVERRIDES, FIRST_APPLICABLE or ONLY_ONE_APPLICABLE",Policy Set Library → Rule Design → Decision Logs,"1. Prepare the two policies and the structured input facts shown above. Inspect the order. 2. Evaluate the approved DENY_OVERRIDES example. 3. Evaluate the equivalent PERMIT_OVERRIDES example. 4. Evaluate FIRST_APPLICABLE with deny-restricted first. 5. Evaluate ONLY_ONE_APPLICABLE using the same facts. 6. Test subject.role=admin, subject.active=true, resource.class=public and action.name=write. 7. Open the evaluation trace and then explain the separate IAM/business enforcement boundary.","Show the same input facts, both matching policies, four combining outcomes and the separate enforcement boundary.",RG-E08,,Awaiting client execution,,,
RG-09,"Test warning and breach boundaries, then inspect an incident",,,,,Rule name = Training Review Deadline; Target = BPMN_ACTIVITY; Warning threshold = 1000 ms; Breach threshold = 2000 ms; Incident policy = SLA_BREACH; severity HIGH; Calendar / time zone = The approved values required by the intended obligation,SLA Library → SLA Policy Master → SLA Incident Policy → SLA Incidents,"1. Create or open the training SLA rule and enter the thresholds above. 2. Prepare the four valid preview inputs and the deliberately invalid started_at input. 3. Run the supported SLA test suite and inspect each case. 4. Explain the invalid-case result before presenting the suite summary. 5. Create the draft incident policy referencing this rule, then read it back. 6. For a live obligation, complete its required review and binding to the activity/calendar before waiting for a deadline. 7. Open an actual resulting SLA incident where one exists and inspect its source obligation and action history.","Show the exact thresholds, all five preview outcomes, saved incident-policy reference and the distinction between preview and a monitored obligation.",RG-E09,,Awaiting client execution,,,
RG-10,Recover updates and retries without losing the original instance,,,,,Selected instance = The existing waiting training instance; Variable change = postRouteNote = reviewing for the process example; Expected version = The current version returned by read-back; Request identity = The existing identity for an exact uncertain retry; Outcome reference = The recorded checkpoint and command receipt,Process Instances → Case Instances → Decision Logs,"1. Open a waiting process or case instance and record its current version and task. 2. Use the offered variable-update action to set the training note. Read back the result. 3. Inspect an exact replay of the same command in the prepared exercise evidence. 4. Inspect the deliberately stale update attempt. 5. Complete the permitted task with the eligible reviewer and retain the completion result. 6. Inspect the transport-restart recovery result in the prepared engineering evidence. 7. For a real uncertain external effect, inspect the producer result before initiating recovery.","Show the original instance, version change, stable retry receipt, rejected stale command and persisted completion result.",RG-E10,,Awaiting client execution,,,