Monitor EAS Update Health and Adoption from the CLI
Query EAS Update health metrics (crash rates, installs, unique users, bundle size, embedded vs OTA split) directly from the CLI for published Expo updates.
Why it matters
Assess the health, performance, and user adoption of published Expo Application Services (EAS) updates by querying crash rates, install counts, unique users, bundle sizes, and embedded-vs-OTA splits directly from the command line.
Outcomes
What it gets done
Check crash rates and failed launch counts for a specific update group across iOS and Android
Compare how many users are running the embedded build versus over-the-air updates on a channel
Identify the most popular updates by unique user count for a given runtime version
Track daily install and failure trends to detect regressions after a new release
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-eas-update-insights | bash Overview
EAS Update Insights
EAS Update Insights exposes aggregate health and adoption metrics for published EAS Updates through the CLI, surfacing the same data that powers the update and channel detail pages on expo.dev in both human-readable and JSON formats. Use this skill when you need to assess the health or adoption of a published EAS Update: crash rates, install counts, unique users, bundle size, or the split between embedded and OTA users on a channel. It fits post-publish rollout monitoring and regression detection workflows. Do NOT use when you need per-user crash detail or device-level reporting - this skill only exposes aggregate EAS metrics.
What it does
EAS Update Insights exposes aggregate health and adoption metrics for published EAS Updates through the CLI. It surfaces the same data that powers the update and channel detail pages on expo.dev - launches, failed launches, crash rates, unique users, payload size, and the embedded-vs-OTA user split per channel - in both human-readable and JSON formats.
When to use - and when NOT to
Use this skill when you need to assess the health or adoption of a published EAS Update: crash rates, install counts, unique users, bundle size, or the split between embedded and OTA users on a channel. Example scenarios include "How is the latest update doing?", "Is the new release crashing more than the last one?", "How many users are on the latest update vs the embedded build?", "Which update is most popular on production right now?", and "How big is our update bundle?". It fits post-publish rollout monitoring and regression detection workflows.
Do NOT use when you need per-user crash detail or device-level reporting - this skill only exposes aggregate EAS metrics, not individual user or device data.
Inputs and outputs
You provide an update group ID (discovered via eas update:list), a channel name, or a runtime version. The skill requires eas-cli installed (npm install -g eas-cli) and an active login (eas login). For channel:insights, you must run the command from an Expo project directory so it can resolve the project ID from app.json.
You receive per-platform breakdowns of launches, failed launches, crash rate percentage (computed as failedInstalls / (installs + failedInstalls) * 100), unique users, launch asset count, and average payload size. The update:insights command provides a daily breakdown with a time series. The channel:insights command shows embedded vs OTA user counts, most popular updates, and cumulative metrics. All commands support --json --non-interactive for programmatic parsing.
Integrations
This skill integrates with the EAS CLI and requires an Expo project configured with EAS Update. It queries the same backend data that powers the expo.dev web dashboard. Commands include:
eas update:list- Discover recent update groups, their group IDs, and branch nameseas update:insights <groupId>- Per-platform launches, failed launches, crash rate, unique users, payload size, daily breakdowneas update:view <groupId> --insights- Update group details plus the same metrics appendedeas channel:insights --channel <name> --runtime-version <version>- Embedded/OTA user counts, most popular updates, cumulative metrics for a channel and runtime
All commands support --days <N> (default 7) or explicit --start / --end date ranges, and --platform <ios|android> filtering where applicable.
Who it's for
This skill is for Expo developers and DevOps engineers who publish EAS Updates and need to monitor rollout health, detect regressions, and understand adoption patterns. It serves teams that want CLI-based observability for their update pipeline without switching to the web dashboard, and those who need to script health checks or integrate metrics into CI/CD workflows.
Example usage
Discover the latest update group ID on a specific branch:
# Latest group id on a specific branch
eas update:list --branch production --json --non-interactive | jq -r '.currentPage[0].group'
Query insights for that group:
eas update:insights 03d5dfcf-736c-475a-8730-af039c3f4d06
Check channel-level embedded vs OTA split:
eas channel:insights --channel production --runtime-version 1.0.6
The JSON response from update:list looks like:
{
"currentPage": [
{
"branch": "production",
"message": "\"Fix checkout crash\" (1 week ago by someone)",
"runtimeVersion": "1.0.6",
"group": "03d5dfcf-736c-475a-8730-af039c3f4d06",
"platforms": "android, ios",
"isRollBackToEmbedded": false
}
]
}
Source README
EAS Update Insights
Query the health of published EAS Updates directly from the CLI: launches, failed launches, crash rates, unique users, payload size, the embedded-vs-OTA user split per channel, and the most popular updates per runtime version. The data is the same data that powers the update and channel detail pages on expo.dev; these commands expose it in the terminal in human and JSON form.
When to use this skill
Use this when the user wants to assess the health or adoption of a published EAS Update: crash rates, install counts, unique users, bundle size, or the split between embedded and OTA users on a channel.
Example prompts:
- "How is the latest update doing?"
- "Is the latest update healthy?"
- "Is the new release crashing more than the last one?"
- "How many users are on the latest update vs the embedded build?"
- "Which update is most popular on production right now?"
- "How big is our update bundle?"
Also fits: post-publish rollout monitoring and regression detection.
Don't use when the user needs per-user crash detail or device-level reporting; this skill only exposes aggregate EAS metrics.
Prerequisites
eas-cliinstalled (npm install -g eas-cli).- Logged in:
eas login. - For
channel:insights: run from an Expo project directory (the command resolves the project ID fromapp.json).update:insightsonly needs a login.
Commands at a glance
| Command | Purpose |
|---|---|
eas update:list |
Discover recent update groups, their group IDs, and branch names |
eas update:insights <groupId> |
Per-platform launches, failed launches, crash rate, unique users, payload size, daily breakdown |
eas update:view <groupId> --insights |
Update group details + the same metrics appended |
eas channel:insights --channel <name> --runtime-version <version> |
Embedded/OTA user counts, most popular updates, cumulative metrics for a channel + runtime |
All of these support --json --non-interactive for programmatic parsing.
Discovering IDs
Before querying insights for an update group, you need its group ID. Use eas update:list with either --branch <name> (updates on that branch) or --all (updates across all branches). Always pass --json --non-interactive when running non-interactively; without a branch/--all flag the command will otherwise prompt for a branch selection:
### Latest group id across all branches
eas update:list --all --json --non-interactive | jq -r '.currentPage[0].group'
### Latest group id on a specific branch
eas update:list --branch production --json --non-interactive | jq -r '.currentPage[0].group'
The JSON response has a currentPage array with one entry per update group (both platforms of the same publish are collapsed into one entry):
{
"currentPage": [
{
"branch": "production",
"message": "\"Fix checkout crash\" (1 week ago by someone)",
"runtimeVersion": "1.0.6",
"group": "03d5dfcf-736c-475a-8730-af039c3f4d06",
"platforms": "android, ios",
"isRollBackToEmbedded": false
}
]
}
Entries also carry codeSigningKey and rolloutPercentage, but only when those features are in use for the group (undefined values are omitted from the JSON output).
When called with --branch <name>, the response also includes name (the branch name) and id (the branch ID) at the top level.
eas update:insights <groupId>
Shows launches, failed launches, crash rate, unique users, launch asset count, and average payload size for a single update group, broken down per platform (iOS, Android), plus a daily breakdown of launches and failures.
Basic use
eas update:insights 03d5dfcf-736c-475a-8730-af039c3f4d06
Flags
| Flag | Description |
|---|---|
--days <N> |
Look back N days. Default: 7. Mutually exclusive with --start/--end. |
--start <iso-date> / --end <iso-date> |
Explicit time range, e.g. --start 2026-04-01 --end 2026-04-15. |
--platform <ios|android> |
Filter to a single platform. Omit to see all platforms in the group. |
--json |
Machine-readable output. Implies --non-interactive. |
--non-interactive |
Required when scripting. |
JSON output shape
Top level: groupId, timespan (start, end, daysBack), and platforms[] with one entry per platform the group was published to. Each platform entry has updateId, totals (uniqueUsers, installs, failedInstalls, crashRatePercent), payload (launchAssetCount, averageUpdatePayloadBytes), and a daily[] time series of { date, installs, failedInstalls }.
For the complete schema and field reference, see references/update-insights-schema.md.
Fields that matter for health assessment:
platforms[].totals.crashRatePercent, computed asfailedInstalls / (installs + failedInstalls) * 100. Zero when there are no installs.platforms[].totals.installsanduniqueUsersgive the adoption signal.platforms[].dailyis a time series, useful for spotting a sudden spike in failures.
Errors
Could not find any updates with group ID: "<id>"- group doesn't exist or you lack access.Update group "<id>" has no ios update (available platforms: android)---platform ioswas used but the group wasn't published for iOS.EAS Update insights is not supported by this version of eas-cli. Please upgrade ...- the server deprecated a field the CLI relies on. Runnpm install -g eas-cli@latest.
eas update:view <groupId> --insights
Extends the standard update:view output with the same per-platform insights, inline.
### Human-readable
eas update:view 03d5dfcf-... --insights
eas update:view 03d5dfcf-... --insights --days 30
### JSON: wrapped as { updates: [...], insights: {...} }
eas update:view 03d5dfcf-... --json --insights
Without --insights, update:view behaves exactly as before - no JSON shape change for existing consumers. The --days / --start / --end flags only apply when --insights is set; passing them alone errors.
eas channel:insights --channel <name> --runtime-version <version>
Shows, per channel, how many users are on the embedded build vs over-the-air updates and which updates are pulling the most traffic. Must be run from an Expo project directory.
Basic use
eas channel:insights --channel production --runtime-version 1.0.6
Flags
| Flag | Description |
|---|---|
--channel <name> |
Required. The channel name (e.g. production, staging). |
--runtime-version <version> |
Required. Match exactly what was published. Check runtimeVersion values in update:list. |
--days <N> |
Look back N days. Default: 7. |
--start / --end |
Explicit time range, like update:insights. |
--json / --non-interactive |
Machine-readable output. |
JSON output shape
Top level: channel, runtimeVersion, timespan, embeddedUpdateTotalUniqueUsers, otaTotalUniqueUsers, mostPopularUpdates[] (each with rank, groupId, message, platform, totalUniqueUsers), cumulativeMetricsAtLastTimestamp[], plus chart-shaped uniqueUsersOverTime and cumulativeMetricsOverTime objects with labels and datasets.
For the complete schema and field reference, see references/channel-insights-schema.md.
Fields that matter:
embeddedUpdateTotalUniqueUsersis the count of users running the embedded (binary-bundled) build.mostPopularUpdates[]is updates ranked bytotalUniqueUsers. Caveat: this is the top-N the server returns;otaTotalUniqueUsersis a sum of that list and may undercount total OTA reach if more than top-N updates are active.uniqueUsersOverTimeandcumulativeMetricsOverTimeare daily data series for charting.
Errors
Could not find channel with the name <name>- typo or wrong account.- "No update launches recorded" in the table / empty
mostPopularUpdatesin JSON - no OTA update has been launched for that channel + runtime yet. Usually means the channel is still serving the embedded build only.
Common workflows
Verify the update I just published is healthy
### 1. Grab the latest publish on production
GROUP_ID=$(eas update:list --branch production --json --non-interactive \
| jq -r '.currentPage[0].group')
### 2. Give it some adoption time (minutes to hours), then check crash rate
eas update:insights "$GROUP_ID" --json --non-interactive \
| jq '.platforms[] | {platform, installs: .totals.installs, crashRate: .totals.crashRatePercent}'
Compare the crashRate across platforms and against previous releases; sudden spikes or asymmetric behaviour (iOS spiking while Android is flat, or vice versa) is the signal to investigate.
Compare adoption between two channels
for channel in production staging; do
echo "--- $channel ---"
eas channel:insights --channel "$channel" --runtime-version 1.0.6 --json --non-interactive \
| jq '{
channel,
embedded: .embeddedUpdateTotalUniqueUsers,
ota: .otaTotalUniqueUsers,
topUpdate: .mostPopularUpdates[0]
}'
done
Detect a rollout regression in the last 24 hours
eas update:insights "$GROUP_ID" --days 1 --json --non-interactive \
| jq '.platforms[] | select(.totals.crashRatePercent > 1)'
Summarize group metrics for release notes
eas update:view "$GROUP_ID" --insights --days 30
Human-readable group details plus 30 days of launches/failures per platform - suitable for pasting into a changelog or incident review.
Output tips
- Pipe JSON through
jq; payloads are structured for easy filtering. --jsonimplies--non-interactive, but passing both is explicit and scripting-friendly.- Dates in
daily[].dateare UTC ISO timestamps; the human-readable table renders them asYYYY-MM-DD(UTC). - The CLI table labels say "Launches" / "Crashes" while JSON uses
installs/failedInstalls. Same field, different display name.
Limitations
- Unique users across platforms may double-count users who run the same publish on both iOS and Android. The same caveat applies to
otaTotalUniqueUsersin channel insights, which is a sum overmostPopularUpdates. - Fresh publishes may show zeros for a short period while the metrics pipeline catches up.
- Installs are downloads, not launches: the
installs/ "Launches" field counts users who downloaded the manifest and launch asset. A confirmed run only registers on the user's next update check (typically up to 24h later, depending on the app's update policy). So metrics lag the real-world state slightly. - Crashes are self-reported:
failedInstalls/ "Crashes" counts updates that errored during install/launch and were reported on the next update check. Crashes that don't trigger an update request (e.g. process kill before recovery) won't appear.
FAQ
Common questions
Discussion
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