Unreal performance review

Find what is actually costing you.

Insights traces and GPU captures on your target hardware, memory high-water marks, synchronous loads and shader compilation cost — put into enough production context for your team to act on Monday.

Full-access engagement

Five consulting days, usually spread across one to two calendar weeks. This is the minimum engagement for work inside your build, source and project content.

Remote by default

Remote is the default.

I work inside your approved environment, review material asynchronously and use calls only where conversation adds value.

Scope

What I look at

01CPU and GPU

Insights traces and GPU captures on target hardware: median and p99 frame time, the worst repeatable hitch, per-pass cost, draw-call and shader-permutation counts.

02Memory and loading

High-water mark against the platform ceiling, streaming pool behaviour, level transitions, synchronous loads, growth over a long session and which subsystem owns it.

03Iteration, as far as it affects the build

Cook and shader compilation where they affect what ships. The full loop — DDC hit rates, sync-to-playable, CI turnaround, senior time — is the engineering effectiveness review.

04Delivery context

Who owns each subsystem, what cert dates and milestones allow, and the order the fixes can realistically happen in given who is free.

Still working out whether the symptoms are connected? Take the free project health check. It runs privately in your browser and sends nothing anywhere.

Before full access

Start with evidence, not credentials.

The earlier steps on the pricing page use a brief, a call and evidence your team chooses to provide. They are designed to establish whether a full-access review is the right next move.

Evidence review

A bounded answer from supplied material.

A selected trace, GPU capture, build log or planning document can be enough to answer a specific question without granting access to a repository or working build.

  • The material your team chooses to provide
  • A concise reading of what the evidence does and does not show
  • Findings ranked by the question they answer
  • A 30-minute call to walk through them

No repository, build or project-content access. If the answer needs full access, that is stated plainly.

Review planning

Prepare the work before opening the environment.

Interviews, delivery context and existing evidence establish the questions a full-access review must answer and the conditions it needs to start cleanly.

  • Named technical contact and agreed review questions
  • Build, access and target-hardware readiness requirements
  • A practical plan for the full-access review
  • A readout with the people who will support it

No repository, build or project-content access. The engagement clock starts when the agreed environment is ready.

Method

Evidence in. Priorities out.

01
Access and brief

A build on target hardware, capture permission, the current plan, and the questions the review must answer. The kit stays yours; the pre-engagement checklist goes out before you book.

02
Capture and interviews

Capture sessions across the worst-performing content, then focused conversations with the engineers closest to it.

03
Findings as they emerge

If the p99 is dominated by one synchronous load, you hear about it on day two, not in the report.

04
Report and readout

Severity, evidence, consequence, recommendation, owner and likely effort.

Deliverables

Useful after the readout

Findings register

Each finding with the capture attached, the cost in milliseconds or MiB, the cause, and what happens if it is left.

Priority plan

What to do before cert, what to do after, what to leave alone — with rough engineer-days against each.

Decision readout

A 90-minute session with the engineers who will do the work and the people who decide what they work on.

The evidence

This is what you get sent, and what it tells you.

Findings arrive with the capture attached and the reasoning written out, so your engineers can disagree with the conclusion by looking at the same data rather than by taking my word for it.

Unreal Insights — Timing view · Firebreak_0.8.41_Development · console targetreconstruction
Unreal Insights timing view showing a synchronous load stalling the frame Five tracks — GameThread, RenderThread, RHIThread, GPU and AsyncLoading. Nine frames run at roughly 13 to 16 milliseconds. One frame is 34.8 milliseconds: the GameThread is occupied for 18.4 milliseconds by FlushAsyncLoading while the render thread and GPU sit idle, starved of work. GameThread RenderThread RHIThread GPU AsyncLoading FlushAsyncLoading Stalled on game thread GPU idle — starved Synchronous package load 0 ms 20 ms 40 ms 60 ms 80 ms 100 ms 120 ms 140 ms 160 ms 180 ms 200 ms 34.8 ms frame — one synchronous load, once per session

What a hitch actually looks like. The GPU is idle for most of the bad frame. Nothing is slow — the game thread is blocked, and everything downstream is waiting for it. Reconstruction using the fictional figures from the sample report.

GPU capture — pass cost breakdown · storm approach · console targetreconstruction
GPU capture showing pass costs, with one translucency pass dominating Eight GPU passes ranked by cost. The storm visual effect translucency pass costs 5.10 milliseconds, more than the base pass at 4.10, and well over the 2 millisecond per-pass budget. Total GPU time is 18.6 milliseconds against a 16.67 millisecond frame budget. Base pass 4.10 ms 22.0% Lumen scene lighting 3.05 ms 16.4% Storm VFX — translucency 5.10 ms 27.4% Shadow depths 2.35 ms 12.6% Post process 1.60 ms 8.6% Virtual shadow maps 1.25 ms 6.7% UI / Slate 0.60 ms 3.2% Other 0.55 ms 3.0% 2.0 ms — the budget any single pass was meant to fit inside Total GPU 18.60 ms · 16.67 ms frame budget · storm approach, worst case

Where the GPU frame went. One unbudgeted translucency pass costs more than the entire base pass. That is a conversation with the VFX lead about overdraw and resolution, not an engine problem. Reconstruction using the fictional figures from the sample report.

These two images are reconstructions, not client captures. Real Unreal Insights traces and GPU captures are client material and never leave the client environment, so they cannot be published here. The layout, the tracks and the reasoning are exactly what a real capture session produces — the numbers come from the fictional project in the sample report.

What a finding looks like when it lands

One number, moved, with the work named.

Findings are ranked by what they return, and the report states the before figure, the target and the expected after. Here is the shape, using the figures from the sample report.

Worst repeatable frame timems · lower better
Before34.8 ms
After19.1 ms

−45%Remove one synchronous load on first use. Gold marker is the 16.67 ms budget.

Illustrative, from the fictional sample report.

Iterative cookminutes · lower better
Before41 min
After14 min

−66%Shared DDC reachable from every desk, and shader permutations capped.

Illustrative. Cook and DDC work belongs to the effectiveness review.

Peak memory, consoleGiB · lower better
Before8.7 GiB
After6.8 GiB

−22%Streaming pool retuned and two duplicated texture sets removed. Gold marker is the platform ceiling.

Illustrative, from the fictional sample report.

These are worked examples from a fictional project, not client results. The sample reports show the format used to turn a capture into a decision.

Before kickoff

Introducing this to your team.

An outside review of the build reads to some engineers as an audit of their work. Worth defusing before it starts, not after.

Conversations with individual engineers are confidential from management. Nothing anyone says is attributed to them, in the report or in conversation. Where a finding can only be described in a way that identifies its source, it is aggregated until it cannot be, or raised with that person first and included only with their agreement.

The findings are about the code and the content, not about who wrote them. No individual is rated, no ranking is produced, and none of this is an input to a performance or headcount process. In practice the engineers are usually the ones who most want the review to happen — they have known about half of these findings for months.

Ask and you will get a short written note addressed to the team rather than to you, describing what is being looked at, what is not, and what happens to anything said in a conversation. Most leads send it before kickoff.

Which engines?
Unreal Engine is the core specialism. Work in another engine is accepted only when the exact performance or delivery question fits Dino Sloth's direct experience; the fit call establishes that before anything is sold.
Does this include a best-practice review of every system?
No. I can measure where animation, gameplay, networking, audio or another system costs time and work with its owner on the evidence. That is different from claiming specialist design expertise in that discipline. If the answer needs additional expertise, it is identified and agreed explicitly in the scope.
Can the review be on-site?
Yes. Reviews are remote by default, but I can work on-site worldwide when it will materially improve the answer. Travel is scoped and priced in advance.
What happens after the report?
The scope includes 30 days for clarification. Implementation help is a separate decision; findings are not shaped to create follow-on work.
Worried about granting access? That is usually the real decision, not the fee. Access and confidentiality sets out exactly what access is needed, what can be done with none at all, and when material is deleted — and there is a one-page security summary your infosec team can have without asking.

Need a clear technical picture?

Start with a free 20-minute fit call.