rollfuse
live rollout, simulated below

Ship features without shipping risk.

rollfuse gives engineering and product teams feature flags, staged rollouts, and automatic guardrail rollback in one control plane, so releases ship safely.

rollout · checkout-v2Ramping stage
10%of traffic
p95 latency118ms

guardrail threshold · 300ms

the cost of shipping blind

What happens without a guardrail

A regression ships to everyone before anyone notices

No staged rollout means every release is all-or-nothing. Error rate creeps up over days, and the first signal is a support ticket — not a graph.

The 3am page a 5% ramp would have caught

A release goes to 100% of traffic at once, with nothing watching a metric on the way. The pager fires for something that could have stayed contained to a canary.

Revenue drops and nobody can say why

A flag flipped three weeks ago. There's no record of who changed it, what it was compared against, or whether it's even related — just a graph and a guess.

how it works

This is the exact loop the demo above just ran

  1. Ship behind a flag

    Code ships dark, decoupled from release. Turning a capability on is a config change, not a deploy.

  2. Ramp by percentage

    A Rollout stages exposure — 10%, 25%, 50% — instead of flipping every user at once.

  3. A guardrail watches

    A real, connected metric is checked against a threshold on every reconciler tick — not a dashboard someone has to remember to look at.

  4. Breach → auto-abort, explained

    The rollout is aborted through the same path a manual operator would use. The recorded PolicyEvaluation carries the metric value, the threshold, the Configuration Version, and a correlation ID — so no one has to reconstruct what happened after the fact.

what you get

Four pillars, one control plane

Feature Flags & Rollouts

Target by segment, ramp by percentage, one Configuration Version per change. Decouple deploy from release, and roll back without a redeploy.

Guardrails

A threshold on any connected metric, evaluated on every reconciler tick, explainable and idempotent. What could go wrong stops itself before your on-call has to.

Experiments

Compare variations against real outcome metrics, with sample-ratio checks and a documented conclusion required to close one out. Decisions with evidence attached, not vibes.

Governance

Role-based access, SCIM-provisioned Members, and a queryable, exportable audit trail. Revoke a leaver's access immediately, and prove who changed what, when.

how we earn trust

Nothing here asks you to take our word for it

Automation explains itself

Every automatic rollback records the metric value, the threshold, the Configuration Version, and a correlation ID — the same evidence a human reviewer would ask for.

Built API-first

Every capability ships behind a stable programmatic contract before or alongside the console. The Go and JS SDKs evaluate flags locally, refresh in the background, and fail safe if the platform is unreachable — evaluation never blocks on a network call.

Bring your own metrics

Connect an existing metric source instead of migrating your analytics. A guardrail can watch a signal you already trust, without copying its history in.

Minimal data, by design

No field collects personal data it doesn't need to support the capability it's for.

the difference

Ad-hoc feature flags vs. rollfuse

TaskAd-hoc feature flagsrollfuse
Rolling back a bad releaseRedeploy, or a manual toggle someone has to remember existsAutomatic — the guardrail aborts it
Knowing why something changedAsk around, dig through SlackQuery the audit trail
Revoking a leaver's accessFind every place they had it, by handDeprovisioned via SCIM the moment your IdP says so
Connecting to your existing metricsRebuild dashboards in a new toolPoint a guardrail at the metric you already have
before you ask

Questions worth answering upfront

Do I have to migrate off Datadog, Amplitude, or our existing metrics?

No. Connect your existing metric source and a guardrail can watch it directly — rollfuse doesn't require you to abandon a tool you already trust.

What happens if a guardrail misfires?

An automatic rollback goes through the same abort path a manual operator would use, and it's recorded with the metric value, threshold, and Configuration Version that triggered it — nothing happens silently, and nothing is harder to undo than a manual action would be.

Is there a self-serve signup?

Not yet. Request access below and an operator provisions your organization directly — there's no public account creation today.

Will this lock us into a UI-only tool?

No. Every capability is exposed through a stable API/SDK contract; the console is a client of that same contract, not the source of truth for it.

What data do you collect?

Only what a capability needs to function — no unnecessary personal data.

Can everyone on the team change a rollout?

Not by default. Role-based access controls who can perform high-impact operations, and privileged changes are audited.

Ready to ship without the guesswork?

Request access below. There's no self-serve signup yet and no credit card — an operator provisions your organization directly and gets you set up.