How to Plan a Soak Test

Planning a soak test is mostly about making sure it produces something actionable. At its core, a soak test is a long unattended run that surfaces leaks and late-session crashes short tests miss. Run without capture, it generates impressions; run with capture, it generates a ranked list of real failures. That difference is the whole point. This guide covers how to plan a soak test so it pays off: Run for hours with capture on and review the late failures it produces.

Planning a soak test

The purpose of a soak test is clear once you state it: it is a long unattended run that surfaces leaks and late-session crashes short tests miss. Planning it well means setting it up to produce data you can act on. Run for hours with capture on and review the late failures it produces. The most common mistake is running the activity without capture, so it surfaces a feeling that “something broke around there” instead of a specific, reproducible failure.

So the first planning decision is to run a soak test with automatic crash capture on. Then every failure it provokes is recorded with its stack trace, the build, the device, and the breadcrumb trail — which turns the activity from a source of impressions into a source of fixes.

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.

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.

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.

Why the report you get is never the whole story

When a player does take the time to tell you something broke, the message is almost always thin: “it crashed,” maybe a screenshot, rarely a version number, and almost never the exact steps. You are left reconstructing the scene of an accident from a single blurry photo. The information you actually need to fix the bug — the stack trace, the device, the build, the state the game was in — is precisely what a human report leaves out.

That is why working from manual reports alone keeps you slow. Every ticket becomes a back-and-forth interrogation, and half the time the player has moved on before you get an answer. Automatic capture removes the interrogation entirely, because the context travels with the failure the instant it happens.

Turning it into fixes

With capture on, a soak test produces a worklist rather than a vibe. Group identical failures so the highest-impact one is on top, read its trace and breadcrumbs, fix the root, and tie failures to builds so you can confirm it. Because you always work the biggest-impact failure first, the activity pays off fast.

Make it part of a loop. a Soak Test is most valuable when its findings flow straight into fixes you verify against the next build, rather than into a document no one revisits. Plan it that way — capture, group, fix, verify — and it becomes a reliable way to make the game more stable, not just a box you ticked.

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 crashes you never hear about are the ones costing you most. Visibility is what turns them into a list you can actually work down.