CodePush analytics

Installation and usage metrics for OTA updates

CodePush analytics are available via the dashboard or CLI so you can use the one suitable to your workflow.

Accessing your metrics

Dashboard

The Codemagic OTA Updates dashboard gives a visual overview of your team’s OTA activity.

The main page shows team-level totals for the current month:

• Downloads - total update downloads across all projects
• Installs - total successful installs across all projects

It also includes a time-series chart of succeeded and failed installs, updated hourly.

Each project is listed below with its latest release and per-release download, install, and failure counts. Clicking through to a project shows time-series charts for downloads, installs, and failures broken down by release version, with a configurable date range.

CLI

You can view per-release metrics directly in the terminal.

Run the following command to list deployment metrics for an app:

code-push deployment ls <app_name>

The following command shows these metrics for all recent releases in a deployment, which is useful for comparing adoption across versions.

code-push deployment history <app_name> Production

Deployment health

Analytics can be used to monitor the overall health of a deployment and ensure OTA updates are being delivered and installed correctly. Some of the key indicators are described below.

Install rates

The ratio between downloads and successful installs can indicate whether updates are installing correctly.

Example signal:

high downloads
low installs

This may indicate:

• Installation failures
• Client-side integration issues
• App crashes during or after install

Rollout monitoring

When using staged rollouts, analytics help verify how an update spreads across the user base.

Example rollout monitoring flow:

release → 10% rollout
observe installs
increase rollout → 25%
monitor crash reports
increase rollout → 100%

If issues appear during rollout, you can:

• Adjust rollout percentage using the CLI (e.g. patch)
• Roll back the deployment
• Pause further exposure until resolved

See Production control for more details.

Failure rates

High failure counts may indicate:

• Corrupted or invalid bundles
• Incompatible updates (version targeting issues)
• Client-side integration problems
• Runtime crashes triggering automatic rollback

Monitoring failures after each release helps teams identify problematic updates quickly.

Using analytics effectively

Analytics are most useful when reviewed after each release to ensure updates are performing as expected.

A typical release monitoring process might look like this:

release deployed
→ monitor installs and downloads
→ track failure rate and crashes
→ evaluate rollout health
→ increase rollout or rollback if needed

Combining CodePush analytics with external monitoring tools such as crash reporting or error tracking helps teams diagnose issues faster and validate release quality.