azure-kusto

To query telemetry data in Azure Data Explorer, you can run Kusto Query Language (KQL) queries to extract insights from large-scale log and time series datasets. This skill facilitates schema exploration and querying via the Kusto REST API or Azure CLI.

Yes, you can manage Azure Data Explorer clusters and databases by listing resources and exploring schemas to understand tables, columns, and data types. It ensures compatibility with Azure CLI for resource management operations.

The best way to explore a Kusto database schema for log analytics is to discover available tables, columns, and data types. This skill helps you understand your data models before executing KQL queries on telemetry or logs.

Yes, querying logs is compatible with Azure CLI and the Kusto REST API. It provides fallback options to ensure robust operations when managing clusters or analyzing large-scale time series data.

To detect anomalies in IoT telemetry, you can run targeted KQL queries to investigate specific events within your Azure Data Explorer environment. This allows network security teams to extract insights from large datasets.

Yes, there are fallback options for robust operations when interacting with Azure Data Explorer. This ensures you can reliably query telemetry and manage clusters even if primary API operations encounter issues.