Safe Rollouts

ProSafe Rollout is available on Pro and Enterprise plans.

Releasing a new feature always carries risk. Even small changes can introduce regressions. Safe Rollouts reduce this risk by releasing to a subset of users while monitoring key metrics for issues.

Overview

Safe Rollouts are a type of feature rule that releases a feature to a subset of users and automatically monitors guardrail metrics for regressions. Guardrails can be any metrics that matter to your team, such as error rates, latency, or conversions.

The rollout runs as a short-term A/B test:

• The Control receives the existing value.
• The Rollout receives the new value.

GrowthBook analyzes the rollout's impact on your selected guardrail metrics and provides status updates: safe to ship, issues detected, or consider rolling back.

How to Add a Safe Rollout

1. Select "Safe Rollout" When Adding a Rule

When adding a new rule to your feature, select Safe Rollout from the list of options.

2. Configure the Safe Rollout

• Rollout Value: Add or select the value to serve during the rollout. This is compared against the Control (default value).
• Split Attribute: Choose the attribute for assigning users to the Control and Rollout groups (for example, id or organization_id).
• Auto Rollback: Toggle this option to automatically disable the rollout rule if any guardrail metric fails significantly.

3. Define Metrics and Monitoring

• Data Source and Assignment Table: Confirm your data source and the experiment assignment table for exposure tracking.
• Guardrail Metrics: Select one or more metrics to monitor for regressions during the rollout.
• Monitoring Duration: Set how many days to collect data before making a decision.

4. Ramp Up Schedule

Safe Rollouts automatically manage traffic exposure to ensure safety. The rollout follows a gradual ramp-up schedule:

10% → 25% → 50% → 75% → 100%

This ramp-up occurs over the first 25% of the monitoring duration. For example, if your duration is set to 4 days, traffic ramps from 10% to 100% during the first day. The remaining time monitors the fully rolled-out feature for failing guardrail metrics.

5. Monitor the Rollout

Once published, GrowthBook begins monitoring the guardrail metrics. The rollout status updates automatically based on results.

Status indicators:

Status	Meaning
X days left	The rollout is in progress. Monitoring continues.
Unhealthy	Traffic is imbalanced. Check your implementation.
Guardrails Failing	Regression detected. Consider reverting the change.
Ready to ship	No regressions detected and safe rollout duration completed. Ready to release fully.
No Data	No traffic detected after 24 hours. Check setup.

info

Guardrails are analyzed for failure using one-sided sequential testing, allowing you to roll back as soon as statistical significance is reached without fear of false positives. Your safe rollout is automatically monitored for implementation errors with sample ratio mismatch and multiple exposures checks.

6. Take Action

At the end of the monitoring period (or sooner if issues arise), you can:

• Release the feature to 100% of users (if not already there).
• Revert the feature to the control value.
• Continue to monitor.

If Auto Rollback is enabled and a regression is detected, GrowthBook automatically disables the rollout rule to protect your users.

Understanding the Time Series Graph

The safe rollout monitoring interface includes a time series graph showing how your guardrail metrics perform over time. The graph displays two key values:

Metric Boundary

The Metric Boundary is the statistical boundary for whether a safe rollout is failing. When it crosses zero, we have enough statistical certainty that the safe rollout is harming this metric. Technically, it is the [lower/upper] bound of the absolute change confidence interval between the baseline and the safe rollout groups.

Threshold

The threshold for when a metric is considered failing. It's always set to zero — as soon as there's statistical certainty that a metric is being harmed at all (even by very small amounts), the safe rollout is marked as failing.

FAQs

How Does the Traffic Ramp Up Work?

Safe Rollouts use a fixed ramp-up schedule (10% → 25% → 50% → 75% → 100%) that completes within the first 25% of your configured duration. This keeps the initial blast radius small and scales up quickly if no immediate issues appear.

What Happens if a Guardrail Metric Degrades?

If a guardrail metric crosses a significance threshold indicating a regression, the rollout status reflects the issue.

• If Automatic Rollback is enabled, GrowthBook automatically disables the feature to prevent further harm.
• If Automatic Rollback is disabled, you retain control and can manually stop or revert the rollout.

What Should I Use as My Guardrail Metrics?

Choose metrics that represent key system health or business outcomes. This might include error rates, latency, or conversion rates—whatever signals that the change is working as intended and not causing harm.

Choosing too many guardrail metrics increases the chance of false positives. Aim for a focused set of critical metrics.

How Is This Different From an Experiment?

Safe Rollouts use the same analysis engine as GrowthBook experiments but are designed for operational decision-making, not learning. The primary goal is to ensure a safe release, not to measure long-term impact.

What Happens if There Isn't Enough Data?

Safe Rollouts are built to help you ship confidently and reduce the chance of negative regressions. If any guardrail fails, roll back the change.

If results are still inconclusive after the configured duration, ship — there's no clear evidence that the feature is harmful.

Safe Rollouts bias towards action. If you're more uncertain about a feature and want to learn about its impact, run a regular Experiment instead.