mcpField
B
bevy-diagnostics-profiling

bevy-diagnostics-profiling

github.com/chrisgliddonDevelopment2668 installsUpdated 9w ago
Repository

About bevy-diagnostics-profiling

A diagnostics and profiling skill for Bevy 0.19 developers. It covers combining metrics, tracing, and render diagnostics to investigate execution time and assess platform performance, including diagnostic paths, GPU measurement limits, and repeatable acceptance tests.

Key features

  1. 01Register diagnostics with stable names
  2. 02Inspect historical and smoothed metric values
  3. 03Trace spans to examine execution time
  4. 04Record render CPU and GPU measurements
  5. 05Explain measurement limits by graphics backend
  6. 06Define repeatable performance acceptance tests

Use cases

  1. 01Investigate frame or render-pass timing
  2. 02Track queue depth, latency, and high-water marks
  3. 03Compare performance budgets across target devices
  4. 04Distinguish unsupported GPU measurements from zero time

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/chrisgliddon/bevy-skills --skill bevy-diagnostics-profiling

After installing, type/bevy-diagnostics-profilingin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
budgets-and-telemetry.md
diagnostics-and-tracing.md
render-and-platform-profiling.md

Details

From the project README

Bevy 0.19 — diagnostics and profiling

When to use this skill

  • A frame, render pass, worker pipeline, or upload path needs causal evidence.
  • A queue/task system needs stable gauges, counters, latency, and high-water marks.
  • Performance claims must pass native, Steam Deck, or browser acceptance budgets.
  • Render GPU diagnostics are absent or disagree with CPU traces.

Diagnostics answer “what is happening over time?” Tracing answers “where did this execution spend time?” Render diagnostics expose pass-level renderer measurements. Use all three, but do not treat any one of them as proof of a bottleneck.

Canonical pattern

use bevy::{
    diagnostic::{
        Diagnostic, DiagnosticPath, Diagnostics, RegisterDiagnostic,
    },
    prelude::*,
};

const REMESH_QUEUE_DEPTH: DiagnosticPath =
    DiagnosticPath::const_new("voxel/remesh_queue_depth");

#[derive(Resource, Default)]
struct RemeshQueue {
    valid_jobs: usize,
}

struct VoxelDiagnosticsPlugin;

impl Plugin for VoxelDiagnosticsPlugin {
    fn build(&self, app: &mut App) {
        app.init_resource::<RemeshQueue>()
            .register_diagnostic(
                Diagnostic::new(REMESH_QUEUE_DEPTH).with_suffix(" sections"),
            )
            .add_systems(Update, record_voxel_diagnostics);
    }
}

fn record_voxel_diagnostics(
    queue: Res<RemeshQueue>,
    mut diagnostics: Diagnostics,
) {
    diagnostics.add_measurement(&REMESH_QUEUE_DEPTH, || queue.valid_jobs as f64);
}

Paths are an API: use namespaced, stable names with explicit units in suffixes or documentation. Register before recording. DiagnosticsStore provides latest and historical/smoothed values for displays and exporters. Measurements are deferred telemetry, not a same-system synchronisation mechanism.

Built-in plugins

  • FrameTimeDiagnosticsPlugin: FPS, frame time, and frame count.
  • EntityCountDiagnosticsPlugin: live entity count.
  • SystemInformationDiagnosticsPlugin: process/system CPU and memory on supported native targets. It is unavailable/no-op for WASM, iOS, and dynamic-link builds.
  • LogDiagnosticsPlugin: development output; filter paths and cadence to avoid noise.
  • RenderDiagnosticsPlugin: CPU/GPU time per recorded render span and pipeline statistics where the backend supports them.

Add RenderDiagnosticsPlugin from bevy::render::diagnostic. It creates dynamic paths shaped like render/<span>/elapsed_cpu and, when supported, render/<span>/elapsed_gpu plus invocation/primitive statistics.

Tracing for causality

Enable a backend in an optimised build:

cargo run --release --features bevy/trace_tracy
cargo run --release --features bevy/trace_chrome

trace_tracy_memory adds allocation tracking with extra overhead. Add coarse spans around work whose cause matters:

use bevy::prelude::*;

fn rebuild_visible_sections() {
    let _span = info_span!("rebuild_visible_sections").entered();
    // measured work
}

Avoid high-cardinality span names and per-element spans. Record section/entity IDs as fields only during targeted captures. Keep a low-overhead diagnostic gauge/counter for continuous observability and switch on detailed traces for investigation.

Gotchas and platform truth

Bevy 0.19 render timestamp queries and pipeline statistics are supported on Vulkan and DX12. Metal, WebGPU, and WebGL2 expose CPU render timings only through RenderDiagnosticsPlugin. Missing elapsed_gpu is an unsupported measurement, not zero GPU cost. Use vendor/platform GPU profilers where available; RenderDoc is a graphics debugger, not a performance profiler.

Profile the shipping renderer, resolution, power mode, content, and build profile. Desktop results do not establish Steam Deck or browser budgets.

Choose the relevant deep dive

ProblemRead
Metric types, stable paths, diagnostics store, tracing spansDiagnostics and tracing
Render diagnostics, backend limitations, CPU/GPU tool choiceRender and platform profiling
Acceptance thresholds, replay design, queue/task/upload telemetryBudgets and telemetry

Review checklist

  • Every number has a type (gauge/counter/histogram), unit, scope, and sampling rule.
  • Queue depth excludes obsolete heap entries; latency timestamps use one clock.
  • Spans cover queue wait, worker compute, main-thread apply, and render/upload costs.
  • Captures are release-like, repeatable, warm, and made on each claimed target.
  • Reports include percentiles and worst sustained intervals, not averages alone.
  • Unsupported GPU values remain absent and are never converted to zero.
  • Instrumentation overhead is measured and disabled/reduced in normal shipping runs.

See also

Comments

Markdown supported