Skip to content

Commit fe0bf0e

Browse files
authored
Fix Log Analytics workspace docs link in Monitor Query README (Azure#25859)
1 parent 9bf4428 commit fe0bf0e

File tree

1 file changed

+1
-1
lines changed

1 file changed

+1
-1
lines changed

sdk/monitor/Azure.Monitor.Query/README.md

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,7 @@
22

33
The Azure Monitor Query client library is used to execute read-only queries against [Azure Monitor][azure_monitor_overview]'s two data platforms:
44

5-
- [Logs](https://docs.microsoft.com/azure/azure-monitor/logs/data-platform-logs) - Collects and organizes log and performance data from monitored resources. Data from different sources such as platform logs from Azure services, log and performance data from virtual machines agents, and usage and performance data from apps can be consolidated into a single [Azure Log Analytics workspace](https://docs.microsoft.com/azure/azure-monitor/logs/data-platform-logs#log-analytics-workspaces). The various data types can be analyzed together using the [Kusto Query Language][kusto_query_language].
5+
- [Logs](https://docs.microsoft.com/azure/azure-monitor/logs/data-platform-logs) - Collects and organizes log and performance data from monitored resources. Data from different sources such as platform logs from Azure services, log and performance data from virtual machines agents, and usage and performance data from apps can be consolidated into a single [Azure Log Analytics workspace](https://docs.microsoft.com/azure/azure-monitor/logs/data-platform-logs#log-analytics-and-workspaces). The various data types can be analyzed together using the [Kusto Query Language][kusto_query_language].
66
- [Metrics](https://docs.microsoft.com/azure/azure-monitor/essentials/data-platform-metrics) - Collects numeric data from monitored resources into a time series database. Metrics are numerical values that are collected at regular intervals and describe some aspect of a system at a particular time. Metrics are lightweight and capable of supporting near real-time scenarios, making them particularly useful for alerting and fast detection of issues.
77

88
**Resources:**

0 commit comments

Comments
 (0)