Introduction

The new Metrics feature in the logs configuration allows you to define custom log metric names and queries, similar to the capabilities available in the log explorer. With this feature, you can create unique log metric names and associate them with specific queries, enabling precise monitoring and tracking of particular data points.

Once the data is calculated for each defined metric, the metrics and their counts are seamlessly integrated into Dashboard 2.0.

To add a metric:

1. Navigate to Infrastructure > Logs.

2. On the left side of this page, click the Menu icon.

3. From the MY LOGS VIEWS page, under QUICK LINKS, select Logs Configuration.
   The configuration page is displayed.

4. From the configurations page, select the METRICs tab.
   The metric details page is displayed.

   

5. Click Add.
   The ADD METRIC page is displayed.

   

6. Enter the following information on the Definition Details page:

   • Name: Provide a unique name for the metric.
   • Filter Query: Build a valid LOGQL query to add filters to refine the log data you want to measure. This helps in targeting specific log entries relevant to your metric.
     You can define how you want to group the data by adding metric labels.

7. Once all the details are provided, click the ADD METRIC to save your new metric.

Your newly created metric will now be available and integrated into Dashboard 2.0.

Enhanced Log Service Metrics Visibility

This feature enables selected log and trace service metrics to be published directly to your tenant. You can use these metrics to monitor operational data, such as log ingestion rates and archival health, through dashboards and alerts.

It provides improved visibility into log processing health and ingestion volumes, helping you monitor system behavior and make informed decisions related to data usage and costs.

Newly Introduced Metrics

• log_archival_health: Indicates the health status of the archival process. Returns 1 for healthy operation and 0 for failure conditions.
• gross_log_records: Tracks the total number of log records processed before filtering or deduplication. Provides visibility into incoming log volume at ingestion.
• gross_log_bytes_received: Measures the total raw payload size (in MB) of received log data. Represents overall incoming data volume before processing.
• net_log_records: Tracks the number of log records after filtering and deduplication. Reflects the effective number of processed records.
• net_log_bytes_received: Measures the processed payload size (in MB) after filtering. Indicates the final data volume retained for analysis.
• trace_querier_requests_total: Counts the total number of requests handled by the querier service. Captures request distribution across endpoints, tenants, and status codes.
• trace_querier_requests_latency: Measures request latency for the querier service in seconds. Helps analyze response time and performance characteristics.
• trace_querier_response_size: Tracks the size of API responses returned by the querier service. Provides visibility into payload sizes per endpoint.
• trace_querier_active_requests: Indicates the number of active in-flight requests per endpoint. Helps monitor real-time request load on the service.