Options for using exported Crashlytics data with Google Cloud services

Firebase Crashlytics and its dashboard in the Firebase console let you explore and analyze stability data about your apps. The standard Crashlytics features can help you with many of the tasks and goals involved with running your app.

Sometimes, though, as your apps and business grow and become more complex, you might need answers to different types of questions, to analyze or join the data in unique ways, or to build custom dashboards or custom alerts based on your data.

To help you do all this, Crashlytics offers options for exporting your data into powerful Google Cloud services: BigQuery and Cloud Logging. Check out What can you do with the exported data? for a more comprehensive list of capabilities for these services.

  • BigQuery: Analyze data using SQL queries, join data from other datasets, export data to another cloud provider, and build data visualizations and custom dashboards (for example, using Looker Studio).
    Set up export to BigQuery

  • Cloud Logging: Create log-based metrics for advanced analysis, set up advanced alerts for custom notification channels, build custom dashboards and charts with Cloud Monitoring, and more.
    Set up export to Cloud Logging

This page describes in more detail how you can use your exported Crashlytics data and (optionally) Firebase sessions data with these Google Cloud services.

What data is exported to each service?

Exports contain raw Crashlytics data (and optionally Firebase sessions data) including device type, operating system, exceptions (Android apps) or errors (Apple apps), and Crashlytics logs, as well as other associated metadata.

The data exported to each service is the same, but the structure is different. For BigQuery, the data is in tables (see dataset schema), and for Cloud Logging, the data is in log format (see log schema).

What can you do with the exported data?

The following are highlights of what's possible when using these Google Cloud services with Crashlytics data. In the Google Cloud documentation, you can learn about all the capabilities of BigQuery and Cloud Logging.

Data exported to BigQuery

  • Analyze data using SQL queries
    You can run queries on your Crashlytics data to generate custom reports and summaries. Since these types of custom reports aren't available in the Crashlytics dashboard of the Firebase console, they can supplement your analysis and understanding of crash data. We even provide you with a collection of example queries.

  • Join data from different datasets
    For example, if you choose to export Firebase sessions data when you set up Crashlytics data export, then you can improve understanding of crash-free users and crash-free sessions. Also, you can export data from various Firebase products (like Performance Monitoring) or from Google Analytics and then join and analyze that data in BigQuery with your Crashlytics data.

  • Create views
    Using the BigQuery UI, you can create a view, which is a virtual table defined by a SQL query. For detailed instructions about the different types of views and how to create them, see the BigQuery documentation.

  • Build data visualizations and custom dashboards
    For example, you can use a premade Crashlytics template to build a dashboard using Looker Studio.

Data exported to Cloud Logging

  • Create log-based metrics for advanced analysis
    Turn your log entries into metrics that track specific app behaviors or stability trends over time. For example, you can create a metric to count how often a specific non-fatal exception occurs and visualize it alongside other system health metrics.

  • Set up advanced alerts for custom notification channels
    Go beyond default email alerts by setting up custom alerting policies in Cloud Monitoring. Trigger notifications based on specific log patterns or thresholds and send them to services like Slack, Jira, or PagerDuty.

  • Build custom dashboards and charts
    Use Cloud Monitoring to create personalized dashboards that highlight the metrics most important to your business. You can visualize crash-free rates, session volumes, and error counts in a single view combined with other Google Cloud product data.

  • Correlate app crashes with backend logs
    Integrate your client-side crash data with your server-side logs in one place.

  • Search and filter raw crash data at scale
    Use the Logs Explorer to run complex queries using LQL (Logging Query Language). You can search for specific log messages, custom keys, or breadcrumbs across all your users and versions to find rare or device-specific issues.

  • Route data for long-term retention or external processing
    Use log sinks to export your Crashlytics logs to Cloud Storage for compliance, BigQuery for massive-scale analytics, or Pub/Sub to stream data into your own external monitoring tools.

When to choose BigQuery versus Cloud Logging?

At a high-level, here are some differences to consider when choosing where to export your data.

Data exported to BigQuery Data exported to Cloud Logging
Applicable business roles Ideal for data analyst roles, especially for joining data from multiple datasets. Helpful for developers and SREs to set up custom alerts and dashboards, as well as to have easier connections to server-side monitoring data.
Options for using the data with Google Cloud products
Options for joining and further export of data
Pricing You pay for both storage and querying.
Learn more in Export Crashlytics data to BigQuery. 		You pay for storage, but not for querying.
Learn more in Export Crashlytics data to Cloud Logging.

What's next?

Set up export to BigQuery Set up export to Cloud Logging

After you've set up export of Crashlytics and (optionally) Firebase sessions data, start using the features of the Google Cloud services: