Explanation:
Box 1: Azure Monitor Agent
Operating system logs from VM1 must be collected and stored in a Log Analytics workspace.
In this scenario, to collect Windows 11 operating system logs from an Azure VM jump box and store them in a Log Analytics workspace, you should use the Azure Monitor Agent (AMA) combined with Data Collection Rules (DCRs).
Key Components to Use:
*-> Azure Monitor Agent (AMA): This is the recommended, modern agent for collecting guest OS logs (Windows Event Logs, security logs) and performance data from Azure virtual machines.
Data Collection Rules (DCR): These define what data (e.g., Security, System, Application events) is collected and where it is sent (the Log Analytics workspace).
Log Analytics Workspace: The central repository where the logs are stored, analyzed, and queried using Kusto Query Language (KQL).
Implementation Steps:
Install AMA: Enable the Azure Monitor Agent extension on the Windows 11 virtual machine.
Configure DCR: Create a Data Collection Rule in the Azure Portal, select the Windows 11 VM as the resource, and define the Windows Event Log channels (e.g., Security, Application) to collect.
Set Destination: Set the Log Analytics workspace as the destination for the data collected by the DCR.
Box 2: Azure Monitor Agent
Syslog data logs from VM2 must be archived to a storage account.
To archive Syslog data from an Ubuntu virtual machine to an Azure Storage account, you should use Azure Monitor Agent (AMA) in conjunction with a Log Analytics workspace and its Data Export feature.
While the Azure Monitor Agent (AMA) collects the Syslog data from the Ubuntu VM and delivers it to a Log Analytics workspace, the workspace itself acts as the bridge for long-term archiving to storage.
Key Components to Use
*-> Azure Monitor Agent (AMA): Installed on the Ubuntu VM to collect and forward Syslog events.
Data Collection Rule (DCR): Used to define which Syslog facilities and levels to collect and specify the Log Analytics workspace as the destination.
Log Analytics Workspace: Serves as the primary repository where Syslog data is initially ingested.
Log Analytics Workspace Data Export: This feature continuously exports data from specific tables (like the Syslog table) to your designated Azure Storage account.
Reference:
https://learn.microsoft.com/en-us/azure/azure-monitor/vm/data-collection
https://docs.azure.cn/en-us/azure-monitor/vm/data-collection-syslog

Access reviews in Microsoft Entra ID, part of Microsoft Entra, enable organizations to efficiently manage group memberships, access to enterprise applications, and role assignments. User access can be reviewed regularly to make sure only the right people have continued access.
Reference:
https://learn.microsoft.com/en-us/entra/id-governance/access-reviews-overview

Explanation:
Serverless is a compute tier for single databases in Azure SQL Database that automatically scales compute based on workload demand and bills for the amount of compute used per second. The serverless compute tier is available in the General Purpose service tier and currently in preview in the Hyperscale service tier.
https://learn.microsoft.com/en-us/azure/azure-sql/database/serverless-tier-overview

Collaborate with any partner using their identities
With Azure AD B2B, the partner uses their own identity management solution, so there is no external administrative overhead for your organization. Guest users sign in to your apps and services with their own work, school, or social identities.
The partner uses their own identities and credentials, whether or not they have an Azure AD account.
You don't need to manage external accounts or passwords.
You don't need to sync accounts or manage account lifecycles.
Reference:
https://docs.microsoft.com/en-us/azure/active-directory/external-identities/what-is-b2b

Explanation:
Box 1: A OneLake shortcut
Link your Dataverse environment to Microsoft Fabric and unlock deep insights With shortcuts from Dataverse directly into OneLake, your data stays in Dataverse while authorized users get to work with data in Fabric.
Box 2: A SQL analytics endpoint
Work with Dataverse data and generate Power BI reports
You can work with Dataverse data in Fabric and generate reports in Power BI.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/data-platform/azure-synapse-link-view-in-fabric