How to Set Up a Soak Test for Your Game

Setting up a soak test sounds like the kind of heavyweight thing only a big studio does. It is not. At its core it just means you run the game for hours to surface leaks and late-session crashes, done consistently. For a small team, the win is a repeatable habit that keeps your attention on the right failures, not a pile of ceremony you will abandon in a month. This guide covers a lightweight way to set up a soak test for your game.

What a soak test actually requires

At its core, a soak test means you run the game for hours to surface leaks and late-session crashes. That is the whole idea — everything else is detail. The reason it works is that it replaces ad-hoc reaction with a small, repeatable routine, so problems get caught while they are still small instead of after they have spread.

The foundation is data you can trust. Run long unattended sessions and capture the late failures short tests miss. Without that, any process is just shuffling incomplete reports around; with it, the process has something real to act on, and the routine becomes genuinely useful rather than busywork.

What good context actually looks like

The difference between a bug you fix in five minutes and one you chase for a week is almost always context. A bare error message tells you something went wrong; a useful report tells you where, on what, after what sequence of actions, in which build. Stack trace, device model, OS version, available memory, and the breadcrumb trail of recent events are the fields that turn guessing into reading.

When that context is captured automatically and consistently, reproduction stops being the bottleneck. You can often see the cause directly in the trace, and when you cannot, the breadcrumbs show you the exact path to walk to reproduce it yourself.

The silent majority who never report anything

For every player who files a report, a large number simply hit the problem, sigh, and close the game. They do not owe you a bug report, and most will not write one. The failures that churn the most players are therefore the ones least likely to ever reach your inbox, which is a deeply unfair feedback loop: the worse the bug, the quieter it tends to be.

The only way out of that loop is to stop depending on goodwill. When every crash is recorded automatically, the silent majority become data. You finally see the failure that is quietly costing you installs, ranked by how often it actually happens rather than by who happened to be patient enough to complain.

Connecting failures to the build that caused them

Regressions are the cruelest class of bug because they punish your most engaged players — the ones who already own the game and updated to your newest patch. A change meant to improve things quietly breaks something else, and without build-level tracking you have no way to link the dip in retention to the release that caused it.

The fix is to attach a build identifier to every captured failure. Then a new signature that appears the day you ship a patch is unmistakable, and you can roll back or hotfix while only a few players are affected instead of discovering the problem weeks later in your reviews.

Turning a pile of crashes into a ranked worklist

Raw crash data is overwhelming if every occurrence is its own line. The trick is grouping: identical failures, fingerprinted by their stack trace, collapse into one issue with a count. Suddenly the question “what should I fix first?” answers itself, because the bug hitting the most players sits at the top with the biggest number next to it.

That ordering is what makes a small team effective. You are never going to fix everything, but you do not have to. Fixing the top few signatures usually removes the large majority of real-world failures, and prioritising by frequency means your limited hours always go to the bug that matters most right now.

Keeping it light and repeatable

The mistake small teams make is overbuilding this. You do not need heavy ceremony; you need a habit. Capture failures automatically with their stack trace, device, build, and breadcrumbs, group identical ones so the worst is on top, tie each to its build, and review the ranked list on a fixed cadence — every release, plus whenever something spikes.

That is a soak test that a solo developer or a two-person studio can actually sustain. It scales naturally too: the same routine handles ten failures or ten thousand, because grouping does the heavy lifting. Start light, keep it consistent, and let the data make the decisions.

This is where a tool like Bugnet earns its place. Its SDK captures every failure automatically with the full stack trace plus device, OS, memory, build, and game-state context, folds identical failures into one grouped issue with an occurrence count, and ties each to the build it happened on. The result is that the abstract idea above stops being theory and becomes a ranked list you work down — the worst problem first, verified fixed when its signature disappears from the next release.

The players who hit the worst bugs rarely tell you. Capture every failure automatically and you stop flying blind.