the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the casestudy has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, clickthe Question button to return to the question. Background - You are a developer for Proseware, Inc. You are developing an application that applies a set of governance policies forProseware's internal services, external services, and applications. The application will also provide a shared library for common functionality. Requirements - Policy service - Youdevelop and deploy a stateful ASP.NET Core 2.1 web application named Policy service to an Azure App Service Web App. The application reacts to events from Azure Event Gridand performs policy actions based on those events. The application must include the Event Grid Event ID field in all Application Insights telemetry. Policy service must useApplication Insights to automatically scale with the number of policy actions that it is performing. Policies - Log policy - All Azure App Service Web Apps must write logs to AzureBlob storage. All log files should be saved to a container named logdrop. Logs must remain in the container for 15 days. Authentication events - Authentication events are used tomonitor users signing in and signing out. All authentication events must be processed by Policy service. Sign outs must be processed as quickly as possible. PolicyLib - You have ashared library named PolicyLib that contains functionality common to all ASP.NET Core web services and applications. The PolicyLib library must: Exclude non-user actions fromApplication Insights telemetry. Provide methods that allow a web service to scale itself. Ensure that scaling actions do not disrupt application usage. Other - Anomaly detection service- You have an anomaly detection service that analyzes log information for anomalies. It is implemented as an Azure Machine Learning model. The model is deployed as a web service.If an anomaly is detected, an Azure Function that emails administrators is called by using an HTTP WebHook. Health monitoring - All web applications and services have healthmonitoring at the /health service endpoint. Issues - Policy loss - When you deploy Policy service, policies may not be applied if they were in the process of being applied during thedeployment. Performance issue - When under heavy load, the anomaly detection service undergoes slowdowns and rejects connections. Notification latency - Users report thatanomaly detection emails can sometimes arrive several minutes after an anomaly is detected. App code - Relevant portions of the app files are shown below. Line numbers are
included for reference only and include a two-character prefix that denotes the specific file to which they belong.
Relevant portions of the app files are shown below. Line numbers are included for reference only and include a two-character prefix that denotes the specific file to which they belong.