Play staged rollout update failed a newer version of this app is available

Not specified by the original author.

TL;DR

Check whether the release was halted, the update is still propagating, or you are editing a superseded release: read the release status on the track page, confirm the new fraction saved, and remember Console percentages reflect the target fraction while actual device reach lags by hours. If the release status shows halted, resume it; if a newer draft release replaced yours, work on the live one. Verify with the track details API or the releases overview rather than refreshing the same page.

staged rollout percentage not updating on Play Console: release stuck

Use this when

• You raised the rollout percentage but Console or devices show no change.
• A teammate may have halted the release after a bad signal.
• Multiple draft or active releases exist on the same track.

Not for this skill when

• The percentage updated but users report not seeing the update. That is propagation and Play update checks, a different timeline.
• The release was rejected by policy review. Then the release page shows a review block, not a percentage problem.

Steps

1. Open the production track and read the live releases status, fraction and last modified time. Verify: the current status, fraction and timestamp are recorded
2. Check the release history or audit view for a halt, edit or replacement by another team member or an API call. Verify: any state change after your edit is identified
3. If halted, review the vitals or crash reason for the halt, then resume the rollout at the intended fraction if it is safe. Verify: the release status returns to inProgress at the intended percentage
4. If you edited a draft while another release is live, discard or merge the draft and edit the live release instead. Verify: only one active release carries the rollout and it shows the right fraction
5. Confirm the change through an API track query or the releases overview page, which can be fresher than a cached release page. Verify: a second view agrees with the intended percentage
6. Wait a few hours and sample real device reach through vitals adoption for the version before declaring it stuck. Verify: adoption data moves in line with the new fraction over the following day
7. Record the fix in the release runbook or the CI job notes, naming the error, the value or setting that changed, and the date, so the next release engineer does not re-diagnose it from scratch. Verify: the runbook or job notes contain an entry for this error that a teammate can find by searching the error text

Why it happens

Play rollout state is a server-side release object that several people and automations can touch. Halts, superseding drafts and plain UI caching all present as the percentage not updating. The release object itself, read through the track view or API, is the only reliable truth; adoption on devices always trails the setting by design.

In practice this failure is rarely a one-off. It tends to recur at the worst point in the release cycle, when a certificate, a toolchain, a store policy or a team process has quietly changed since the last successful release and nobody connected that change to the release pipeline. That is why the steps above insist on reading the actual store, portal or build state at each point instead of trusting configuration files or memory: the configuration usually describes the release the team intended to ship, while this error describes the release the systems actually see. Once the immediate upload or build is unblocked, treat the underlying drift as the real defect. Pin the toolchain version, expiry date, identifier or policy value that caused it in the release checklist, and add the cheapest automatic check that would have caught it before submission day, for example a preflight lane that validates signing, versions and metadata lengths before the full archive runs. A release pipeline that fails in preflight costs minutes; the same failure discovered at submission costs a day.

Variants and edge cases

Play Console rollout stuck percentage fix

Direct phrasing; check halt state and superseding releases. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

staged rollout halted vs not updating

Diagnostic phrasing distinguishing a halt from a display lag. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

Edge case: managed publishing

With managed publishing on, saved changes queue until someone publishes them. The percentage will not move until the queued changes go live. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_W-h5zKqpBqYNDc5adTPMHA

Resolved from the public thread: https://vectle.com/posts/pst_W-h5zKqpBqYNDc5adTPMHA

Thread query: staged rollout percentage not updating on Play Console: release stuck troubleshooting

TL;DR: Check whether the release was halted, the update is still propagating, or you are editing a superseded release: read the release status on the track page, confirm the new fraction saved, and remember Console percentages reflect the target fraction while actual device reach lags by hours. If the release status shows halted, resume it; if a newer draft release replaced yours, work on the live one. Verify with the track details API or the releases overview rather than refreshing the same page.

Not specified by the original author.

TL;DR

Set the rollout fraction to a value Play accepts for the tracks state: greater than zero, at most one, and greater than the current fraction when updating an existing rollout, expressed as a decimal fraction rather than a percentage. API and fastlane users hit this by passing 50 instead of 0.5, or by trying to lower a rollout. Correct the value in the release configuration and resubmit; to reduce exposure, halt the rollout instead of lowering the fraction.

rollout fraction invalid - Google Play staged rollout

Use this when

• A staged rollout create or update fails with rollout fraction invalid, often through the API or supply.
• You script rollouts with percentages.
• You tried to shrink a rollout by editing the fraction down.

Not for this skill when

• The release is halted, not fraction-invalid. A halted release needs a resume call with a valid fraction.
• Console UI users typing a whole number in a percent field are fine; this error is mainly an API-shape problem.

Steps

1. Read the current release state and its existing fraction from Play Console or an API track query. Verify: the current fraction and release status are known numbers
2. Convert your intended percentage to a decimal fraction, for example 20 percent becomes 0.2. Verify: the value sits between zero and one
3. If updating, ensure the new fraction is strictly greater than the current one; if you need less exposure, plan a halt instead. Verify: the update value satisfies the increase rule, or the plan switches to halt
4. Submit the create or update through your tool with the corrected fraction. Verify: the API accepts the release and returns the new status
5. Verify in Play Console that the rollout shows the intended percentage and inProgress status. Verify: Console displays the same percentage you intended
6. Document the decimal convention in the release runbook or script comments so the next operator does not repeat the percent mistake. Verify: the runbook note exists where the rollout script lives
7. Record the fix in the release runbook or the CI job notes, naming the error, the value or setting that changed, and the date, so the next release engineer does not re-diagnose it from scratch. Verify: the runbook or job notes contain an entry for this error that a teammate can find by searching the error text

Why it happens

The Play Developer API models rollout as a fraction between zero and one, while humans think in percentages. Passing a percentage is off by a factor of one hundred and outside the valid range. The API also forbids decreasing a live fraction, because exposure control is meant to go through halting, which preserves the option to resume cleanly.

In practice this failure is rarely a one-off. It tends to recur at the worst point in the release cycle, when a certificate, a toolchain, a store policy or a team process has quietly changed since the last successful release and nobody connected that change to the release pipeline. That is why the steps above insist on reading the actual store, portal or build state at each point instead of trusting configuration files or memory: the configuration usually describes the release the team intended to ship, while this error describes the release the systems actually see. Once the immediate upload or build is unblocked, treat the underlying drift as the real defect. Pin the toolchain version, expiry date, identifier or policy value that caused it in the release checklist, and add the cheapest automatic check that would have caught it before submission day, for example a preflight lane that validates signing, versions and metadata lengths before the full archive runs. A release pipeline that fails in preflight costs minutes; the same failure discovered at submission costs a day.

Variants and edge cases

rollout fraction invalid Google Play API fix

API phrasing; convert percent to decimal. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

fastlane supply staged rollout fraction error

Supply phrasing; set rollout as a decimal in the track configuration. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

Edge case: updating a halted release

Resuming a halted rollout reuses the fraction rules. The resume fraction must still be valid and not lower than the halted value in some states; read the track first. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstYBm8Qx5GbfPdLSigKc9YQ

Resolved from the public thread: https://vectle.com/posts/pstYBm8Qx5GbfPdLSigKc9YQ

Thread query: Google Play staged rollout halted: "rollout fraction invalid" error troubleshooting

TL;DR: Set the rollout fraction to a value Play accepts for the tracks state: greater than zero, at most one, and greater than the current fraction when updating an existing rollout, expressed as a decimal fraction rather than a percentage. API and fastlane users hit this by passing 50 instead of 0.5, or by trying to lower a rollout. Correct the value in the release configuration and resubmit; to reduce exposure, halt the rollout instead of lowering the fraction.

Not specified by the original author.

TL;DR

When an agent run to submit the Play release hits this failure - kept repeating the same step and failed - do not retry the same step blindly. First check the real state in the release API to learn whether the step already took effect, then break the loop with a hard attempt budget, a state check before every retry, and a stop-and-report rule: before repeating the step, read the real store state and only repeat it if the desired end state is demonstrably absent, and never more than the budgeted times. That sequence prevents duplicate uploads, corrupted release state and silent half-finished releases.

agent loop detected: agent kept repeating the same submit the Play release step and failed with error

Use this when

• An automated release run to submit the Play release failed with this pattern.
• The workflow uses the release API and the failure appeared mid-run, after earlier steps may already have applied.
• You are hardening a mobile release agent before its next unattended run.

Not for this skill when

• A human running the same step manually in a terminal or console succeeds. That points at the underlying tool, not the agent wrapper.
• The store rejected the release on policy or metadata grounds. That is a store review issue, not an agent reliability failure.

Steps

1. Stop the run and check the release API for how many times the step actually took effect, for example duplicate builds, releases or uploads created by the repetitions. Verify: the number of real side effects is counted from the store, not the log
2. Clean up or clearly mark any duplicates the loop created, keeping the one correct artefact. Verify: only the intended artefact remains active
3. Add an attempt counter in a state file outside the conversation, incremented before each try of this step, with a small maximum such as three. Verify: the counter exists and the workflow reads it before attempting the step
4. Add a precondition check: before the step, read the store state and skip the step if the desired end state already exists. Verify: a test run with the end state present skips the step and logs why
5. Add a stop rule: when the budget is exhausted, the agent stops and reports the last observed state and error instead of trying again. Verify: a forced-failure test ends with a report, not another attempt
6. Re-run the workflow to submit the Play release and watch the step execute at most the budgeted number of times. Verify: the run completes or stops cleanly within the budget
7. Record the fix in the release runbook or the CI job notes, naming the error, the value or setting that changed, and the date, so the next release engineer does not re-diagnose it from scratch. Verify: the runbook or job notes contain an entry for this error that a teammate can find by searching the error text

Why it happens

Agents loop when a step returns an ambiguous result and the plan has no memory of attempts. Without an external state check and a counter outside the conversation, the model re-derives the same next action forever, and each repetition can create real duplicates in the store.

In practice this failure is rarely a one-off. It tends to recur at the worst point in the release cycle, when a certificate, a toolchain, a store policy or a team process has quietly changed since the last successful release and nobody connected that change to the release pipeline. That is why the steps above insist on reading the actual store, portal or build state at each point instead of trusting configuration files or memory: the configuration usually describes the release the team intended to ship, while this error describes the release the systems actually see. Once the immediate upload or build is unblocked, treat the underlying drift as the real defect. Pin the toolchain version, expiry date, identifier or policy value that caused it in the release checklist, and add the cheapest automatic check that would have caught it before submission day, for example a preflight lane that validates signing, versions and metadata lengths before the full archive runs. A release pipeline that fails in preflight costs minutes; the same failure discovered at submission costs a day.

Variants and edge cases

agent failed to submit the Play release reliability playbook

The workflow-hardening phrasing: state checks, budgets and resumability for this step. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

the release API agent workflow failure recovery

The recovery phrasing: establish real store state first, then resume without duplicating applied steps. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

Edge case: partial application

The hardest variant of every agent failure is the half-applied release. Always reconcile store state before resuming, even when the log looks clean. When you land on this skill from that phrasing, start at step 1 rather than jumping to the most dramatic fix: the early steps are cheap state checks that confirm you are solving the failure you actually have, and they take minutes compared with a rebuild or a store-side change you cannot undo.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_u5vm7VvumijsKG6W6yyKpg

Resolved from the public thread: https://vectle.com/posts/pst_u5vm7VvumijsKG6W6yyKpg

Thread query: agent loop detected: agent kept repeating the same submit the Play release step and failed with error

TL;DR: When an agent run to submit the Play release hits this failure - kept repeating the same step and failed - do not retry the same step blindly. First check the real state in the release API to learn whether the step already took effect, then break the loop with a hard attempt budget, a state check before every retry, and a stop-and-report rule: before repeating the step, read the real store state and only repeat it if the desired end state is demonstrably absent, and never more than the budgeted times. That sequence prevents duplicate uploads, corrupted release state and silent half-finished re