Query Azure Monitor Logs and Metrics
Deprecated Java SDK skill for querying Azure Monitor Logs (KQL) and Metrics - migrate to the split query packages.
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Why it matters
Access and analyze logs and metrics from Azure Monitor to gain insights into resource performance and activity. This SDK facilitates querying Log Analytics workspaces and Azure resources for operational data.
Outcomes
What it gets done
Query Azure Monitor Logs using Kusto Query Language.
Retrieve time-series metrics data from Azure resources.
Integrate with Azure Monitor for data retrieval and analysis.
Map query results to custom Java objects for easier processing.
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-azure-monitor-query-java | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Overview
Azure Monitor Query SDK for Java
A deprecated Java SDK skill for querying Azure Monitor Logs via KQL and Azure Monitor Metrics, covering single/batch/multi-resource queries, aggregations, sovereign cloud endpoints, and error handling. Use it to maintain or migrate an existing integration - new work should target the split azure-monitor-query-logs and azure-monitor-query-metrics packages instead.
What it does
This skill covers com.azure:azure-monitor-query for Java, a client library for querying Azure Monitor Logs and Metrics. The package is deprecated in favor of two split packages, azure-monitor-query-logs and azure-monitor-query-metrics. Four clients exist: LogsQueryClient and LogsQueryAsyncClient run Kusto Query Language queries against a Log Analytics workspace or an Azure resource, while MetricsQueryClient and MetricsQueryAsyncClient (plus a separate MetricsClient for multi-resource queries) pull numeric time-series metrics. Sovereign clouds are supported by overriding the endpoint - for example api.loganalytics.azure.cn for logs or management.chinacloudapi.cn for metrics in Azure China.
When to use - and when NOT to
Use it to run KQL queries against Log Analytics or pull Azure Monitor metrics from a Java application, or to understand an existing integration before migrating it. New work should target azure-monitor-query-logs and azure-monitor-query-metrics directly - this combined package is explicitly deprecated, and the SDK's own best practices list migration as a planning item.
Inputs and outputs
A basic logs query returns rows of a result table:
LogsQueryResult result = logsClient.queryWorkspace(
"{workspace-id}",
"AzureActivity | summarize count() by ResourceGroup | top 10 by count_",
new QueryTimeInterval(Duration.ofDays(7))
);
for (LogsTableRow row : result.getTable().getRows()) {
System.out.println(row.getColumnValue("ResourceGroup") + ": " + row.getColumnValue("count_"));
}
Queries can also target a resource ID instead of a workspace, map rows directly onto a custom model class, or run as a LogsBatchQuery combining several queries into one request (each checked individually for a PARTIAL_FAILURE or FAILURE LogsQueryResultStatus). LogsQueryOptions add a server timeout, statistics/visualization data on the response, and querying across additional workspaces at once. A LogsQueryResult exposes statistics, visualization, error, and a list of tables (each with named/typed columns and rows); a MetricsQueryResult exposes granularity, time interval, namespace, and a list of metrics, each with a time series of dimensioned values (timestamp, count, average, total, maximum, minimum) - metrics queries also support setting granularity and requesting specific AggregationType values like AVERAGE and COUNT.
Integrations
Authenticates via Azure Identity's DefaultAzureCredential, queries Log Analytics workspaces and Azure resource metrics, and is distributed via Maven Central (com.azure:azure-monitor-query) or the Azure SDK BOM; the deprecation points to azure-monitor-query-logs and azure-monitor-query-metrics as the maintained replacements.
Who it's for
Java developers maintaining an existing Azure Monitor Logs/Metrics integration on this package, or migrating one to the split successor packages - and who follow its own guidance: batch multiple queries into a single request, set generous server timeouts for long-running queries, limit result size with top/take and select only needed columns with project, check for PARTIAL_FAILURE explicitly, and cache metrics results since they don't change frequently.
FAQ
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Discussion
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