Aggregation
When you read metric data using the Metrics Explorer or the Monitoring API, you can use aggregation to summarize the time series data. Aggregation typically starts with an alignment step in which each time series' data is placed on the same time boundaries. Next, a new time series is created by combining the data points from multiple time series, using operations like average, sum, minimum, maximum, and so forth.
For more information about aggregation, see the
projects.timeSeries.list
API method.
Custom metrics
Cloud Monitoring has a large number of built-in system metrics, but you can also create custom metrics. You must create a metric descriptor that describes your custom metric and one or more time series that contain its data. You can use your custom metric data in charts and alerts. You can also create custom metrics based on logs data. For more information, see the following pages:
- Metrics, Time Series, and Resources provides an overview.
- Using Custom Metrics shows you how to create, write, and read custom metrics.
- Logs-based Metrics describes how to create custom metrics from logs.
- Monitoring API, is the API used to for
custom metrics. See the
projects.metricDescriptorsandprojects.timeSeriescollections.
Filtering
Cloud Logging and Cloud Monitoring provide different kinds of filters that let you select sets of items. Filters are strings that contain combinations of comparisons appropriate to their kind. For example:
- Logging filters let you select particular log entries based on log names, where the logs came from, their payload content, and so on.
- Monitoring filters let you select particular metric descriptors, resource groups, and time series data.
- Trace filters let you select traces based on span names, latency, and label values.
Metrics scope
Monitoring organizes itself around metrics scopes that let you view and monitor metrics for one or more Google Cloud projects. For more information about metrics scopes, see Configuring your Google Cloud project for Cloud Monitoring.