Fix: Unreal Mass Entity Fragments Not Replicating

Here is how to fix Unreal Mass Entity simulations where the server runs thousands of entities perfectly but clients see nothing or only a few static positions. Mass replication is opt-in and substantially more involved than standard Actor replication. Without the right module, processors, and network IDs, your fragments simply do not cross the wire.

The Symptom

A Mass simulation runs on the server, populating fragments with position, velocity, animation state. On the client, the entities are missing or appear stuck at spawn position. stat MassEntities shows expected counts on server, near zero on client.

What Causes This

MassReplication module missing. The base Mass framework does not include replication; it is a separate module.

No replication processor. Even with the module, processors must be registered to drive the replication pipeline.

Replication grid missing. Mass replication uses a spatial grid to determine which entities are relevant per client. Without a grid, no entities are flagged for relevance.

FMassNetworkID not assigned. Without per-entity network IDs, the client cannot reconstruct the mapping.

The Fix

Step 1: Add Mass modules.

// MyProject.Build.cs
PublicDependencyModuleNames.AddRange(new string[] {
    "MassEntity",
    "MassCommon",
    "MassReplication",
    "MassActors",
    "MassMovement",
    "MassRepresentation",
    "NetCore"
});

Step 2: Configure the Mass replication grid. Create a UMassReplicationGrid2DSubsystem subclass or use the default. In your level’s WorldSettings or a custom GameMode subsystem:

void AMassNetGameMode::PreInitializeComponents()
{
    Super::PreInitializeComponents();

    UMassReplicationSubsystem* repl = GetWorld()->GetSubsystem<UMassReplicationSubsystem>();
    repl->RegisterBubbleInfoClass(AMyBubbleInfo::StaticClass());
}

Step 3: Define a Bubble Info actor. The Bubble is the per-client replicated container holding networked entity state. AMyBubbleInfo extends AMassClientBubbleInfoBase and pairs with an FBubbleHandler describing serialization.

Step 4: Add networked fragments. Mark fragments you want replicated by including them in the replication processor’s FragmentRequirements:

void UMyReplicationProcessor::ConfigureQueries()
{
    EntityQuery.AddRequirement<FTransformFragment>(EMassFragmentAccess::ReadOnly);
    EntityQuery.AddRequirement<FMassNetworkIDFragment>(EMassFragmentAccess::ReadOnly);
    EntityQuery.AddRequirement<FAgentLastPathFragment>(EMassFragmentAccess::ReadOnly);
}

Step 5: Network LOD for performance. Replicating thousands of entities every tick saturates connections. Use the LOD system:

Replication LOD bands:
  Tier 1 (close):    full fragments, every tick
  Tier 2 (medium):   pos + velocity, every other tick
  Tier 3 (far):      pos only, every 10 ticks
  Tier 4 (very far): not replicated

Configure in the Mass Schema and the NetworkLODProcessor.

Verifying Replication

On a client, run stat MassEntities and stat NetMass. If client count matches server count (or matches the LOD-relevant subset), replication is working. If client count is 0, the bubble is not registered or the grid is missing.

Check the Network Profiler (net dump) to see Mass-related RPC traffic. Lack of any traffic means the replication pipeline is not running.

Common Pitfalls

Adding fragments to entities that the replication processor does not include. Those fragments stay server-only.

Forgetting to call StartUpInternal or the equivalent on your custom subsystem. Without that, processors are never scheduled.

Mismatched fragment definitions between server and client. Replication serialization assumes both sides have identical fragment layouts.

Understanding the issue

This bug class falls into a pattern that's worth understanding beyond the specific case. In Unreal Engine, the underlying behavior is shaped by how the engine layers its abstractions - the public API you call, the runtime systems that respond, and the platform-specific implementations underneath. A bug at any layer can produce symptoms that look like they originate at a different layer. Triaging effectively means recognizing which layer the symptom belongs to, even when the gameplay code is what's visible.

The specific bug described above is the kind that surfaces during integration rather than unit testing. It depends on a combination of factors: the asset configuration, the runtime state, the platform's specific behavior. In isolation, each piece looks correct; in combination, the bug emerges. This is why thorough integration testing - playing the actual game in realistic conditions - catches things that automated tests miss.

Why this happens

This bug class disproportionately affects late-stage development. The work to surface it is interactive testing in realistic conditions, which only really happens after the gameplay is in place and assets are populated. Catching it early requires deliberate testing of conditions that look unimportant.

At the engine level, the behavior comes from a deliberate design decision in Unreal. The engine team chose a particular trade-off - usually performance versus convenience, or generality versus specificity - and that trade-off has consequences when you push against it. Understanding the trade-off is what turns 'this bug is mysterious' into 'this bug is the expected consequence of this design'.

Verifying the fix

For shipping games, the safest verification is a staged rollout. Apply the fix to 1% of players for 24 hours; watch the affected metric; expand if green. Skipping the staged rollout means the verification is the entire player base, which is too high a stakes for most fixes.

Reproducibility is the prerequisite for verification. If you can't reliably reproduce the bug pre-fix, you can't reliably verify it post-fix. Spend time getting a clean reproduction before you write any fix code. The fix is fast once you understand the reproduction; the reproduction is the slow part.

Variations to watch for

There's almost always a less obvious case where the same problem applies. The reported case is the one a player hit; the related cases hide because they're rarer or affect fewer players. After fixing the reported case, search the codebase for the pattern - one fix often unlocks several.

Adjacent bugs often share a root cause. After fixing the case you've found, spend an hour searching the codebase for similar patterns. What's the same call with different arguments? The same data flow with a different entity type? The same lifecycle issue in a sibling system? Each match is a candidate for the same fix, or a related fix that prevents future bugs of the same class.

In production

In shipping builds, this issue may interact with other production-only behavior. Stripping, encryption, asset bundling, and platform-specific code paths can each modify the symptoms. When players report a related issue, capture build SHA, platform, and any feature flags - those three fields cover most of the production-only variations.

When triaging a similar issue in production, prioritize gathering data over hypothesizing causes. A player report describes a symptom; what you need is a build SHA, a session timestamp, and ideally a screen recording or session replay. With those, the bug becomes tractable. Without them, you're guessing at hypothetical reproductions that may not match what the player actually hit.

Performance considerations

If this issue manifests under high load (many actors, many particles, many network connections), profile the post-fix code path with realistic counts. The original cost was a bug; the new cost is real work, and real work has a budget.

Diagnostic approach

Before applying any fix, gather enough context to be confident you're addressing the actual cause and not a similar-looking symptom. The cheapest diagnostic step is reproducing the bug deterministically - if you can't get the same failure twice in a row, your fix attempts will be hard to evaluate. Lock down the reproduction first.

For Unreal-specific diagnostics, the editor's profiler is the canonical starting point. Capture a representative frame with the symptom present; compare against a frame without the symptom; the diff often points directly at the cause. If the symptom is non-deterministic, capture multiple frames and look for the pattern - the cause is usually a state transition or a specific input value rather than a continuous effect.

Tooling and ecosystem

Modern engine versions ship better tooling for this kind of issue than older versions. If you're on an older release, the diagnostic step may take significantly longer because the tools you'd want don't exist yet. Sometimes the right answer is upgrading rather than fighting through limited tooling.

Within Unreal, the relevant diagnostic surfaces include the standard frame debugger, memory profiler, and engine-specific debug overlays. Each one shows a different facet of what's happening. The frame debugger reveals draw call ordering and state transitions; the memory profiler shows allocation patterns; the debug overlay reveals per-system state. Bugs that resist one tool usually surrender to another - the trick is knowing which tool to reach for first.

Edge cases and pitfalls

Edge cases for this class of issue often involve specific timing: the first frame after a state change, the last frame before a transition, frames where multiple subsystems update simultaneously. Reproducing these reliably is part of what makes the bug class hard to test.

When writing a regression test for this fix, focus on the boundary conditions that surfaced the original bug. Tests that exercise the happy path catch obvious regressions; tests that exercise the boundary catch the subtler regressions that look like new bugs but are really the original returning. The latter are the tests that earn their keep over the long life of the project.

Team communication

When this bug class affects multiple teams (often the case for cross-system issues), early communication prevents duplicate work. The team that owns the symptom may not own the cause. A 15-minute conversation at the start of triage often saves hours of independent investigation.

If this fix touches a system several engineers work in, a short writeup in the team's engineering channel helps. Not a full design doc - a paragraph explaining what was wrong, what's fixed, and what to watch for. Future engineers encountering similar symptoms will search for the fix; making it findable is a small investment that pays back later.

“Mass replication is its own subsystem. Module + grid + bubble + processor + LOD. Five pieces, all required.”

Related Issues

For Multicast RPC issues, see Multicast RPC. For physics constraint replication, see Physics Constraint Load.

Module, grid, bubble, processor, LOD. Five pieces and the entities cross the wire.