How do you design Three.js testing, debugging, and deployments?

Long Answer

Delivering reliable 3D on the web requires discipline across Three.js testing, debugging, and deployment. Unlike plain DOM apps, tiny timing, GPU, or driver differences can break visuals or tank frame rates. A good system isolates logic, stabilizes rendering, and automates checks from commit to release.

1) Test strategy: unit → integration → visual

Start with unit tests for deterministic logic: vector/matrix math wrappers, geometry builders, procedural color functions, easing utilities, and custom loaders’ parsing. These run in Node with Jest/Vitest and do not require WebGL.
Add integration tests that boot a headless WebGL context (e.g., using @react-three/test-renderer or headless GL shims) to validate scene graphs: camera FOV, aspect, light counts and types, material parameters, and asset loader contracts (GLTF/DRACO/KTX2). Assert that expected nodes exist, bounding boxes match, animations load, and fallbacks trigger when features are missing.
For visual regression, render a small set of golden frames with fixed camera, resolution, devicePixelRatio, and deterministic random seeds. Freeze time, disable post-processing jitter (TAA), and standardize tone mapping, color space, and exposure. Compare PNGs/EXRs against baselines with tolerances for GPU AA differences, mask dynamic regions (e.g., particle systems), and gate merges on approved diffs.

2) Determinism and asset hygiene

Visual flakes often stem from nondeterminism. Pin Three.js and shader libs, fix random seeds, and normalize color management (SRGBColorSpace, tone mapping). Self-host textures, HDRs, and fonts; compress with KTX2/BasisU and Draco to reduce size and driver variance. Pre-bake lightmaps/IBLs, and cache-bust with content hashes. Provide feature fallback ladders (WebGL2 → WebGL1, high → medium → low quality) decided by capability checks.

3) Debugging: CPU/GPU, shaders, assets

Expose a stats panel (CPU frame time, GPU time via timer queries if available), memory footprints, draw calls, triangles, program count, texture count, render target count. For shaders, compile with explicit #define flags and log uniform ranges; dump generated GLSL for inspection. Use browser devtools’ WebGL/Canvas inspector to track state changes and hot paths. Add a “debug HUD” toggle with axes helpers, bounding boxes, and camera bookmarks. For assets, validate GLTFs (validators), report missing tangents, and warn on oversized textures or non-power-of-two usage.

4) Performance profiling and budgets

Define hard budgets: <16.6 ms per frame on target devices, draw calls, triangles, GPU memory, and shader compile time. Track Jank % (frames > 50 ms), input latency, and first interactive render. Pre-warm pipelines: load materials, compile programs during a splash scene, and use renderer.compile() with representative objects. Prefer instancing, batched materials, and mip-mapped KTX2. Avoid overdraw via depth pre-pass or sorted transparent layers. Record per-scene metrics and fail CI if budgets regress.

5) Cross-browser/device QA

Your render must hold across Chrome, Safari, Firefox; Windows/Intel/NVIDIA/AMD; macOS/Apple GPU; iOS/Android. Build a matrix: browsers × OS × GPU tier × DPR. On CI, run smoke renders in containerized Chrome and one alternative engine (e.g., WebKit via Playwright). For device labs or cloud farms, execute scripted “camera tours” that visit critical shots and export frames plus metric logs. Gate releases on a minimal green matrix and promote gradually with canary.

6) CI/CD and artifacts

The CI pipeline: lint and type check (TS), unit tests, integration tests with headless GL, visual regression renders, then build with content hashing. Publish artifacts: baseline images, diff reports, GPU/CPU timing CSVs, shader maps, and WebGL capability snapshots. Deploy via blue/green or canary behind a feature flag. Health checks verify static assets, WebGL context creation, shader program link success counts, and first frame time on a synthetic bot. Keep the last N builds for instant rollback.

7) Telemetry and runtime diagnostics

In production, sample FPS, frame time histogram, GPU adapter info, and context loss events. Track asset load times, shader compile spikes, and texture memory. Send anonymized, rate-limited metrics to your APM. Correlate releases with performance deltas and error spikes (context lost, OOM, NaN transforms). Provide a secret debug query param that enables HUD overlays and logs without shipping them to all users.

8) Release governance and documentation

Every scene or effect should have a Storybook or demo page with known-good baselines and perf notes. PRs must include updated golden frames when visuals intentionally change, with “why this diff is expected.” Maintain a playbook for “black screens” (missing extensions, precision issues, float textures on iOS) and for context-loss recovery.

With this layered approach—deterministic tests, targeted debugging, strict performance budgets, and staged deployments—Three.js testing and deployment becomes predictable, cross-device safe, and easy to evolve.

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Table

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Common Mistakes

• Relying on manual eyeballing instead of golden-frame visual regression.
  
• Allowing nondeterminism: random seeds, TAA jitter, changing exposure, or external CDN textures.
  
• Skipping asset hygiene (no KTX2/Draco), causing huge downloads, GPU memory spikes, and slow start.
  
• Profiling only CPU; ignoring GPU time, shader compile costs, and draw call explosions.
  
• Testing on one desktop Chrome and calling it “done,” then failing on Safari/iOS GPUs.
  
• Shipping without budgets or perf gates; regressions creep in unnoticed.
  
• No canary or rollback; a driver quirk ships to 100% of users.
  
• Logging nothing in production, making black screens impossible to diagnose.
  
  

Sample Answers (Junior / Mid / Senior)

Junior:
“I write unit tests for math helpers and loaders, then an integration test to ensure the scene builds with expected cameras and lights. I render a fixed frame and compare it to a baseline for visual regression. I track FPS with a small stats panel.”

Mid:
“I standardize color space and seeds, disable TAA jitter for tests, and render golden frames in CI. I define budgets for draw calls and memory. Our pipeline artifacts include diff images and timing logs. We test Chrome and WebKit, then canary release and monitor FPS/error rates.”

Senior:
“I enforce deterministic rendering, asset compression (KTX2/Draco), and capability-based fallbacks. CI runs unit/integration, headless golden renders with tolerances, and perf gates. Deployments are blue/green with instant rollback. Telemetry correlates release IDs with FPS, shader compile spikes, and context-loss events. This keeps Three.js testing and deployment predictable across browsers and GPU tiers.”

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Evaluation Criteria

Look for a Three.js testing and deployment plan that:

• Separates logic tests (math/loaders) from rendering checks (scene contracts).
  
• Uses deterministic visual regression with fixed camera/DPR and controlled tone mapping.
  
• Establishes performance budgets and CI gates for FPS, draw calls, triangles, memory.
  
• Covers cross-browser/device QA with a defined matrix and scripted camera tours.
  
• Implements CI/CD with artifacted diffs, canary/blue-green, and rollbacks.
  
• Provides runtime telemetry for FPS, shader events, and context loss.
  
  

Red flags: manual only, no determinism, no perf gates, single-browser testing, mutable builds, or lack of rollback/telemetry.

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Preparation Tips

• Create a small scene with camera presets and save golden frames. Practice rendering them headlessly and diffing in CI.
  
• Add unit tests for math and an integration test that asserts node counts, materials, and bounding boxes.
  
• Normalize color space and tone mapping; disable TAA jitter for tests.
  
• Compress textures with KTX2 and models with Draco; measure load and memory.
  
• Define perf budgets and wire a failing threshold in CI.
  
• Build a two-browser matrix (Chrome + WebKit) and one mobile device check.
  
• Add a debug HUD and a runtime telemetry hook to log FPS and context-loss events, tied to release IDs.
  
  

Real-world Context

An e-commerce configurator’s releases regressed subtly: highlights shifted and load time spiked. The team added deterministic visual regression with fixed camera frames; unintended lighting diffs dropped 90%. Switching textures to KTX2 and DRACO halved GPU memory and improved start FPS by 25%. Safari/iOS crashes were traced via telemetry to float textures; a capability check auto-switched to half-float. CI began failing builds that exceeded draw-call budgets, preventing a particle effect from shipping unbounded. Canary deployments plus instant rollback kept experiments safe while cross-device QA verified stability on Apple and Intel GPUs.

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Key Takeaways

• Layer tests: unit/integration for logic, golden-frame visual regression for rendering.
  
• Enforce determinism: fixed seeds, tone mapping, DPR, and assets.
  
• Set performance budgets with CI gates for FPS, draws, memory, and shader compile time.
  
• Run a browser/OS/GPU matrix and scripted camera tours for cross-device QA.
  
• Deploy with canary/blue-green, telemetry, and one-click rollback tied to release IDs.

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Practice Exercise

Scenario:
You are shipping a Three.js product tour with GLTF models, HDR environment lighting, and post-processing (bloom, SSAO). Recent releases caused brightness drift on Safari/iOS and jank on mid-tier Android devices.

Tasks:

1. Determinism: Lock seeds, tone mapping, exposure, DPR, and disable TAA jitter for tests. Self-host assets and compress textures with KTX2; Draco-compress models.
   
2. Testing: Write unit tests for math/util helpers and an integration test that asserts scene graph contracts (camera FOV, light counts, material params). Add visual regression: render three camera bookmarks (hero, interior, macro) and diff against baselines with masks for particles.
   
3. Performance: Define budgets (≤ 1.5k draws, ≤ 3M tris, ≤ 300 MB GPU memory). Pre-compile shaders on a splash step; fail CI when budgets regress.
   
4. Cross-Device QA: Build a matrix (Chrome/Windows + Safari/macOS + Safari/iOS). Script a camera tour; export frames and metrics.
   
5. CI/CD: Artifact diffs, timing CSVs, and shader logs; deploy canary with runtime telemetry for FPS, shader compile spikes, and context-loss.
   
6. Rollback: Keep last five artifacts promotable; provide a flag to disable SSAO if telemetry spikes on mobile.
   
   

Deliverable:
A repo PR with tests, CI config, golden frames, perf gates, and a rollout plan demonstrating safe, measurable Three.js deployments.