How do I decide between raw logs and a crash reporter?

Look at the real impact: logs are the raw material, but a reporter is what gets them off the device and into a ranked worklist. Capturing failures with full context, grouping them by how many players each hits, and tying them to builds turns the judgement call into a reading of the numbers.

What if I make the wrong call?

Working from data limits the downside. Because failures are tied to builds and grouped by impact, you'll see quickly whether the choice worked — a spike, a falling count — and can adjust, rather than discovering it weeks later in your reviews.

Should You Use Logs or a Crash Reporter?

Quick answer: On raw logs versus a crash reporter: a crash reporter, because it collects, symbolicates, groups, and ranks failures instead of leaving logs on players' machines. The way to make the call with confidence rather than instinct is to logs are the raw material, but a reporter is what gets them off the device and into a ranked worklist. That depends on capturing failures with full context, grouping them by impact, and tying each to its build — the data that turns a judgement call into a clear decision.

“Should You Use Logs or a Crash Reporter?” is the kind of question where the honest answer is “it depends,” but it depends on things you can actually measure. On raw logs versus a crash reporter, the rule of thumb is: a crash reporter, because it collects, symbolicates, groups, and ranks failures instead of leaving logs on players' machines. Made from a gut feeling, the choice is a coin flip; made from real failure data, it is straightforward. This guide covers how to decide, and how to make the call with evidence — logs are the raw material, but a reporter is what gets them off the device and into a ranked worklist.

The honest answer

On raw logs versus a crash reporter, the honest answer is: a crash reporter, because it collects, symbolicates, groups, and ranks failures instead of leaving logs on players' machines. The reason it feels hard is that, without data, you are weighing risks you cannot see — and instinct is biased by the fact that everything works on your own machine. Once you can see the real impact of the failures involved, the choice usually makes itself.

It is rarely a permanent, all-or-nothing decision either. The right call this time depends on the specifics — how many players are affected, how severe it is, what changed in the last build — which is exactly the kind of thing real data tells you and a hunch does not.

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.

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.

Deciding with data

To make the call with confidence, logs are the raw material, but a reporter is what gets them off the device and into a ranked worklist. The foundation is failures captured with full context, grouped so you can see how many players each one hits, and tied to builds so you can see what changed and when. With that, the decision stops being a debate about opinions and becomes a reading of the numbers.

This is what lets a small team act decisively under pressure. Whether the answer is one option, the other, or both in sequence, it is grounded in what is actually happening to your players rather than in whoever argues hardest. And because failures stay tied to builds, you can confirm afterwards that the choice was right.

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.

Guessing is the slowest way to debug. Real reports from real devices turn a mystery into a short, ordered to-do list.