This document describes how Google Cloud Observability stores your telemetry data. It includesinformation about how Cloud Logging, Cloud Monitoring, and Cloud Tracestore data. This document also provides a conceptual overview ofobservability buckets, which Cloud Trace uses as its storage model.

Log data

Log data resides inlog buckets, which are the containers thatLogging uses to store your log data. Every Google Cloud project,billing account, folder, and organization contains log buckets named_Requiredand_Default.

By default, log data resides in the Google Cloud project, billing account, folder,or organization where the data originates. However, you can configureLogging to route log data from the resource where it originatesto another location, like another project or a centralized log bucket.

To learn more, seeStore log entries andRoute log entries.

Metric data

Metric data resides in the Google Cloud project where the data originates.

Trace data

Trace data resides in an observability bucket named in the same Google Cloud projectwhere the data originates. The bucket name is_Trace. The next sectiondescribes observability buckets.

To learn about the storage format of individual spans, seeTrace schema.

Observability storage model

This product or feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of theService Specific Terms. Pre-GA products and features are available "as is" and might have limited support. For more information, see thelaunch stage descriptions.

The Observability API storage model relies on the following architecture:

Observability buckets

An observability bucket is the management entity for datasets, which storedata. An observability bucket is in a specific location and has a dataretention policy. When a Google Cloud service uses theObservability API to store their data, the system creates anobservability bucket based on the name of the service. For example, forthe Cloud Trace service, the system-created bucket is named_Trace.To learn about the structure of an observability bucket, seeBucket.

Datasets

A dataset is a storage entity. Each dataset is a child of anobservability bucket. When the system creates an observability bucket fora Google Cloud service, it also creates one dataset. For example, after thesystem creates the_Trace bucket, it creates the dataset namedSpans.That dataset stores your trace data. To learn about the structure of adataset, seeDataset.

Views on datasets

Each dataset hosts one or more view. Aview provides read access to asubset of entries in the dataset. When a dataset is created, the systemautomatically creates one view. That view includes all data in the dataset.The name of the view depends on the service. For example, for theCloud Trace service, the system creates a view named_AllSpanson theSpans dataset. To learn about the structure of a view, seeView.

Links on datasets

Each dataset can contain at most one link. When you create alink for adataset, the system creates a linked BigQuery dataset. Youcan then query the data in your dataset by using BigQueryor by other services that use the BigQuery API.To learn about the structure of a link, seeLink.

The system doesn't automatically create links on datasets.

For example, your trace data resides in a dataset namedSpans. This datasetis a child of the observability bucket named_Trace. On theSpans dataset,the system creates the view named_AllSpans. This view includes all data inthe dataset.

Limitations

You can't do the following:

• Modify or delete observability buckets.
• Create, delete, or modify datasets.
• Create, delete, or modify views.
• Use the Google Cloud console to list buckets, datasets, views, or links.
• Create observability buckets in the locations other than theus; anobservability bucket must be in theus location.

What's next

• Learn how toManage your observability buckets.
• Learn how toView and analyze your telemetry.