Instead use Azure Network Watcher to run IP flow verify to analyze the network traffic.
Note: Wire Data looks at network data at the application level, not down at the TCP transport layer. The solution doesn't look at individual ACKs and SYNs.
Reference:
https://docs.microsoft.com/en-us/azure/network-watcher/network-watcher-monitoring-overview
https://docs.microsoft.com/en-us/azure/network-watcher/network-watcher-ip-flow-verify-overview

Scenario: Once App1 is migrated to Azure, you must ensure that new data can be written to the app, and the modification of new and existing data is prevented for a period of three years.
As an administrator, you can lock a subscription, resource group, or resource to prevent other users in your organization from accidentally deleting or modifying critical resources. The lock overrides any permissions the user might have.
Reference:
https://docs.microsoft.com/en-us/azure/azure-resource-manager/management/lock-resources

You use Azure Policy to enforce tagging rules and conventions. By creating a policy, you avoid the scenario of resources being deployed to your subscription that don't have the expected tags for your organization. Instead of manually applying tags or searching for resources that aren't compliant, you create a policy that automatically applies the needed tags during deployment.
Note: Organizing cloud-based resources is a crucial task for IT, unless you only have simple deployments. Use naming and tagging standards to organize your resources for these reasons:
Resource management: Your IT teams will need to quickly locate resources associated with specific workloads, environments, ownership groups, or other important information. Organizing resources is critical to assigning organizational roles and access permissions for resource management.
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/decision-guides/resource-tagging
https://docs.microsoft.com/en-us/azure/azure-resource-manager/management/tag-policies

Azure Data Factory is the platform that solves such data scenarios. It is the cloud-based ETL and data integration service that allows you to create data-driven workflows for orchestrating data movement and transforming data at scale. Using Azure Data Factory, you can create and schedule data-driven workflows (called pipelines) that can ingest data from disparate data stores. You can build complex ETL processes that transform data visually with data flows or by using compute services such as Azure HDInsight Hadoop, Azure Databricks, and Azure SQL Database.
Reference:
https://docs.microsoft.com/en-gb/azure/data-factory/introduction