Team
Most teams$50/ seat / month
5-seat minimum — a $250 / month floor.
- 100 reproductions included every month
- $4 per reproduction over the included 100
- Time-travel reproduction to any past version, bit-identical to production
Feature-flag reproduction
Loglune is your feature-flag platform. Define flags, config and targeting here; our own SDK evaluates them in your app and records every result. When a bug fires for one tenant, replay the exact ruleset that was live at that moment into dev, CI or staging.
REPRO
RATIO
INCL
OVER
The problem
A defect that only fires under one customer’s flag, plan, and config combination is one your team can’t recreate at their own desk. Support and engineering are left guessing at a state they can’t see.
closed · could-not-reproduce
support → engineering
P1 · blocked
incident · unresolved
config drift
debug closes every one of these: pick the customer’s flag state and reproduce it in your own environment in a single step.
Reproduce from production
Loglune’s own SDK already evaluated the flag in your production process and recorded the result. Point at that record — or any past moment — and the engine folds the event log to that version and replays the exact ruleset into the environment you already ship from. There is no new runtime to adopt — the reproduction runs on your machine, your CI, your staging.
Your production · @ T
loglune · replay
3 flags · folded to 2026-08-22
materialisedYour dev / CI
closed · could-not-reproduce
one command · your machine
How it works
Loglune’s own SDK evaluates the ruleset inside your process — there is no environment of ours for you to wait on. We define, publish and replay; your existing infrastructure runs both the live evaluation and the reproduction.
The console
A JS-free, form-native workspace: define flags, segments and config, publish each state as an immutable version, reproduce a bug from any past version, and read the per-period reproduction meter. Below is the console in its default state — no tenant selected, showing an honestly-labelled example dataset. The real workspace lives at /debug/app.
Exactness
“Almost right” is worthless for a bug repro. A reproduction re-runs the same SDK against the folded ruleset, so four things that a snapshot or a rollback would get wrong are resolved exactly as they were at the moment the bug fired.
| Aspect | Reproduced exactly | Not |
|---|---|---|
| Rule version | Targeting is evaluated against the ruleset that was live at T | not today’s rules |
| Bucketing | Percentage rollout hashes on flag key + context, identically across SDK language and version | not a re-rolled dice |
| Time-dependent rules | Date and schedule conditions are evaluated at the reproduced moment T | not the replay wall-clock |
| Prerequisites | Flag-to-flag dependencies resolve in the log’s causal order | not an arbitrary order |
One reproduction is one replay-source delivery — the single request that hands the folded ruleset to your dev, CI or staging process. Live evaluation delivery is never metered, and there is no environment of ours left running, so there is no idle time to charge for.
1:1
Monthly meter
Data handling
We act as a processor for your flag data. What we hold is configuration — flag rules, targeting and versions — not the people behind them.
Pricing
$50
Get started50+
Contact sales