This page provides a conceptual overview of logs-based metrics.
Logs-based metrics are based on the content of log entries. For example, the metrics can record the number of log entries containing particular messages, or they can extract latency information reported in log entries. You can use logs-based metrics in Cloud Monitoring charts and alerting policies.
There are two kinds of logs-based metrics:
- System-defined logs-based metrics, provided by Cloud Logging for use by all Google Cloud projects.
- User-defined logs-based metrics, created by you to track things in your Google Cloud project that are of particular interest to you. For example, you might create a logs-based metric to count the number of log entries that match a given filter.
Logs-based metrics apply only to a single Google Cloud project. You can't create them for logs buckets or for other Google Cloud resources such as Cloud Billing accounts or organizations.
Before you begin
To use logs-based metrics, you must have a Cloud project with billing enabled:
In the Google Cloud Console, go to the project selector page.
To begin creating a Google Cloud project, click Create project.
Name your project. Make a note of your generated project ID.
Edit the other fields as needed.
To create the project, click Create.
Make sure that billing is enabled for your Cloud project. Learn how to confirm that billing is enabled for your project.
To verify that you have the correct permissions to use logs-based metrics for the Cloud project, see Access control guide: Log-based metrics.
View your logs-based metrics
The Logs-based metrics page in the Google Cloud Console lets you create a logs-based metric, and it contains lists of all the logs-based metrics for your Cloud project.
To view a list of logs-based metrics for your Google Cloud project, do the following:
Go to the Logs-based metrics page in the Cloud Console:
Select an existing Cloud project. The lists of logs-based metrics in your Cloud project appear.
The logs-based metrics interface is divided into two metric-type panes: System metrics and User-defined metrics.
Each pane contains a table summary of the metrics. Each metric's row has a menu more_vert that features the following options:
View in Metrics Explorer lets you view the data for a system logs-based metric by opening Metrics Explorer in Cloud Monitoring.
You can use Metrics Explorer to specify a target metric for an alerting policy. The chart next to the Target region gives you visual feedback on the data being captured by the target metric.
Create alert from metric lets you create an alerting policy based on the logs-based metric.
Selecting this option opens the Cloud Monitoring console, where you can create, edit, and manage alerting policies. For details on creating alerting policies for your logs-based metrics, read Creating an alerting policy.
User-defined metrics pane
The User-defined metrics pane of the logs-based metrics interface has several features to help you manage the user-defined metrics on your Cloud project:
The user-defined metrics table includes Name, Description, Type, and Filter columns. These are specified when you create the metric.
The Filter user-defined metrics pane lets you filter your metric list by text search or metric Name, Description, and Filter.
The user-defined metrics table includes columns for Previous month usage and Month-to-date usage (MTD). This usage data is useful, for example, if you want to determine which metrics ingest the most data or to estimate your bills.
Clicking on any of the column names lets you sort data in ascending or descending order.
The menu more_vert for each metric in your user-defined metrics pane contains additional features for managing your metrics:
- View metric details: Shows you the metric's Name, Type, Description, Filter, Units, and Labels, if defined.
- Edit metric: Lets you edit certain fields for the metric.
- Disable metric: Lets you stops the metric from being calculated. You can re-enable a disabled metric from the same menu.
- Delete metric: Lets you delete the metric.
- View logs for metric: Takes you to the Logs Explorer and populates the metric's filter in the Query builder and runs the query.
Overview of logs-based metric types
System logs-based metrics are calculated from included logs only. User-defined logs-based metrics are calculated from both included and excluded logs.
The data for a logs-based metric comes from log entries received after a metric is created. A metric isn't retroactively populated with data from log entries that are already in Logging.
Logging accumulates information for a logs-based metric each time it receives a matching log entry. Logging writes a new data point to the metric's time series at the rate of 1 datapoint per minute, making the data available to Cloud Monitoring.
Each data point in a logs-based metric's time series represents only the additional information (the delta) received since the previous data point.
User-defined logs-based metrics can be of the counter or distribution metric types. Most system-defined logs-based metrics are counters, but some are of the Boolean type.
The following sections describe the characteristics of counter-type and distribution-type metrics.
Counter metrics count the number of log entries matching a given filter. For example, you can do the following:
- Count the log entries that contain a certain specific error message.
Count the number of times each user invokes an operation, by looking for log messages that match this pattern:
... user USERNAME called OPERATION ...
By extracting USERNAME and OPERATION and using them as values for two labels, you can later ask, "How many times did
updateoperation?", "How many people called the
readoperation?", "How many times did
georgecall an operation?", and so on.
For more information, see Configure counter metrics.
Distribution metrics accumulate numeric data from log entries matching a filter. The metrics contain a time series of distribution objects, each of which contains the following:
- A count of the number of values in the distribution.
- The mean of the values.
- The sum of squared deviations: Sumi=1..n(xi–mean)2
- A set of histogram buckets with the count of values in each bucket. You can use the default bucket layout or choose your own.
A common use for distribution metrics is to track latencies. As each log entry is received, a latency value is extracted from somewhere in the log entry and is added to the distribution. At regular intervals, the accumulated distribution is written to Cloud Monitoring.
For information on distributions, including their format within a time series and how they are visualized, see Charting distribution metrics.
For information on creating distribution logs-based metrics, see Configure distribution metrics.
Logs-based metrics can have labels, which allow multiple time series to be collected for the metric. Values for the labels are extracted from fields in the matching log entries. Logging records separate time series for each combination of label values.
User-defined logs-based metrics
User-defined logs-based metrics are created by a user on a Google Cloud project. These metrics count the number of log entries that match a given filter or record particular values within the matching log entries.
System logs-based metrics
Logging provides a set of metrics that includes counters. The counter metrics record the number of logging events that occurred within a specific time period. The metrics have labels that record the counts by log name and severity level.
For a list of these metrics, see Google Cloud metrics: logging.
You can use both system and user-defined logs-based metrics in Cloud Monitoring to create charts and alerting policies. For more information, see Configure charts and alerts.
In Cloud Monitoring, logs-based metrics use the following naming patterns:
Note that user-defined metrics include the string
User-defined logs-based metrics are a class of Cloud Monitoring custom metrics and are chargeable.
For pricing information, see Cloud Logging pricing: Logs-based metrics.
If you encounter issues when using logs-based metrics, see Troubleshoot log-based metrics.