Windows Container Build Performance#

Findings from making a large C++23 project build fast inside the Windows toolchain image. Everything here was measured, including the approaches that failed — the dead ends are documented deliberately so nobody spends an afternoon rediscovering them.

Reference project: a ~690-object C++23 modules engine (Vulkan, CMake + ninja + clang-cl, Rust bridged in via corrosion/cxx), built on a Dev Drive host. Concrete script: Kataglyphis-BeschleunigerBallett/scripts/windows/Build-Windows-Container.ps1.

Result#

Approach

Outcome

Reusable container + tar-pipe

9.6 s ninja / 44 s wall, no-change

Reusable container + bind mount

✅ works; 32.7 s ninja / 159 s wall — slower here

Streaming the build tree in and out

🟡 ~230 s (worked, but moved ~17 GB per build)

sccache with a persistent named volume

❌ 0.00 % hit rate, 0 bytes stored

Named volume mounted as the build directory

❌ CMake cannot configure inside it

Fresh container per build (starting point)

352–484 s

Cold builds, for reference: 327.9 s (tar-pipe, fresh container) and 318.1 s (bind mount). The transport barely matters cold — it is the incremental case where the difference is decisive.

Transports: how to set up both#

Getting sources into the container and artifacts back out has two working implementations. Both are supported and worth keeping — which one wins depends on the host, and the answer here was the opposite of what we expected. Keep them behind a switch and measure rather than assume.

Which one should I use?#

tar-pipe

bind mount

Host setup needed

none

elevated fsutil + reboot (Dev Drive only)

Where the build tree lives

inside the container

on the host volume

Incremental cost

copies sources each build (~35 s here)

none

Per-file I/O cost

container-local, fast

crosses the filter, slow

Measured here (no-change)

9.6 s ninja / 44 s wall

32.7 s ninja / 159 s wall

Survives docker rm

❌ tree is lost

✅ tree is on the host

Rules of thumb:

  • Large build tree, incremental edit-build loop → tar-pipe. You pay a fixed bulk copy once per build instead of filtered I/O on every one of ~1000 targets. This is why it wins on the reference project.

  • Small tree, or a host where the transport dominates → bind mount. The fixed copy cost stops being amortised and removing it wins.

  • Non-Dev-Drive volume → measure again. The penalty below is specific to a Dev Drive with filters allow-listed; an ordinary NTFS volume does not behave the same way.

  • You want the build tree to survive the container → bind mount.

Transport A — tar-pipe (no host setup)#

Works everywhere, including Dev Drive hosts with default settings, because it never asks the filesystem to attach anything.

# in:  sources only, excluding .git and build trees
tar -cf - --exclude .git -C $repoRoot . | docker exec -i $c tar -xf - -C C:\ws
# out: only what the host runs, selected by EXCLUSION (tar does not expand globs)
docker exec $c tar -cf - --exclude "*/CMakeFiles" --exclude "*.obj" -C C:\ws build-x | tar -xf - -C $repoRoot

Requirements: none. Caveats: the deletion hazard (safety rail 2 below), and tar aborting a whole transfer on one over-long path (see Gotchas).

Transport B — bind mount (Dev Drive needs setup)#

A Dev Drive refuses bind mounts by default — the minifilter cannot attach (“Der Dateisystem-Minifilter kann nicht an das Entwicklervolume angefügt werden”). Allow-list the two filters, elevated:

fsutil devdrv setFiltersAllowed /volume D: "bindFlt,wcifs"

Four things that cost time here:

  1. The filter list is ONE quoted argument. bindFlt, wcifs unquoted is parsed as two arguments and fails with a bare syntax dump.

  2. It needs a reboot. The setting persists immediately, but the filters only attach when the volume is dismounted. You will see Fehler 5: Zugriff verweigert — that is the dismount failing because the volume is in use, not the setting failing. /f force-dismounts instead; do not use it on the volume holding your repo.

  3. query shows “allowed” before “attached”. After the reboot the filters are listed as allowed but still not attached — they attach on demand, the first time something actually requests a bind mount. Do not read that as failure; probe instead.

  4. Omitting /volume sets it machine-wide. Scope it to the volume you mean.

Verify — allow-list, then an actual mount:

fsutil devdrv query D:        # expect: bindFlt, wcifs under "allowed"
docker run --rm --isolation process `
  --mount "type=bind,source=$repoRoot,target=C:\ws" `
  --entrypoint cmd $image /c "dir C:\ws\CMakePresets.json"

Revert (a Dev Drive is fast because filters do not attach — allow-listing them slows general I/O on that volume, not just container builds):

fsutil devdrv clearFiltersAllowed /volume D:   # + reboot

Mount both transports at the SAME in-container path#

If you support both — and you should — mount at the path the tar-pipe already uses. CMake bakes absolute paths into CMakeCache.txt and refuses to reuse a cache generated elsewhere:

CMake Error: The source "C:/ws-mnt/CMakeLists.txt" does not match
the source "C:/ws/CMakeLists.txt" used to generate cache.

Without a shared path, every switch between transports forces a cold rebuild and the two are not really interchangeable. One path (here C:\ws) fixes it.

The path must still be absent from the image: mounting over a directory baked in (C:\workspace) fails at CreateComputeSystem when the host OS build differs from the image base build. Verify with docker run --rm --entrypoint cmd $image /c "if exist C:\ws (echo BAKED IN)".

Why the bind mount lost here#

With a bind mount the build tree lives on the Dev Drive, so every ninja stat and every object write crosses the bindFlt filter from inside the container. Copying sources in bulk once is cheaper than paying filtered I/O across ~1000 targets — ninja alone tripled, 9.6 s → 32.7 s on an identical tree. Repeated to rule out a first-run artifact.

Cold builds are near-identical (327.9 s vs 318.1 s), which is the tell: the penalty is per-file-operation, not per-byte, so it only shows up once compilation stops dominating.

What works: reuse one container#

Create a single long-lived container instead of one per build. The build tree never leaves it, so ninja’s dependency graph, C++23 module BMIs and object files are all still there next time.

# reuse if running; start if stopped; recreate if the image changed
$state = docker inspect -f '{{.State.Running}}|{{.Image}}' $name 2>$null
  • Inbound: stream sources only. tar preserves mtimes, so ninja rebuilds exactly what changed.

  • Outbound: stream back only what the host needs to run*.exe, *.dll, *.pdb, compile_commands.json, logs. Copying the whole build tree back is unnecessary once the container keeps its own copy.

Safety rails this needs#

Reuse trades isolation for speed, so guard it:

  1. Compare the container’s image ID against the referenced image and recreate on mismatch — otherwise a rebuilt toolchain image is silently ignored and you keep building against the old one.

  2. Provide an explicit reset switch (-FreshContainer, or docker rm -f <name>). Sources are overwritten in place and never pruned, so a file deleted on the host still exists inside the container.

    This is not theoretical - measured 2026-07-19. A probe test file was added, built and observed to run; the file was then deleted on the host and the project rebuilt. The test still ran, and the .cpp was still present inside the container. Consequences worth internalising: tests keep passing against deleted code, and a deletion that breaks the build passes locally and fails in CI, where nothing is reused.

    If you want reuse without this hazard, prune the source tree inside the container before streaming (keeping the build directory and logs) rather than extracting over it. Sources re-stream in seconds; only the build tree is worth preserving. Get the exclusion pattern right first - a wrong one deletes the build tree on every build and silently undoes the whole optimisation.

  3. Keep the build root: if the build script wipes its build directory before configuring, gate that behaviour behind an env var (this project uses KATAGLYPHIS_KEEP_BUILD_ROOT) or reuse buys nothing.

  4. Verify the artifacts exist and arrived. A zero exit code proves neither. Both halves failed silently in the reference project:

    • A build was cut off before linking, reported success, and produced no test executable at all. The log simply stopped partway through the step count ([982/1022]) with no summary and no error.

    • The outbound tar selected files by glob — which tar does not expand. It copied nothing, reported success, and looked correct only because stale artifacts from an earlier build were already on the host. Select by --exclude instead.

    Hours went into diagnosing a “transport bug” that was really a truncated build, because a green build was taken as evidence that binaries existed. After the transfer, list the executables inside the container and assert each one reached the host; fail the build if the container produced none, or if any did not arrive.

    Check existence, not timestamps: on a no-change incremental build the linker does not run, so the executables are legitimately older than the current run. A freshness check would false-fail exactly when the cache is working best.

What does not work#

sccache on a C++23 modules build#

sccache runs, reports the right cache location, and caches nothing:

Compile requests            907
Cache hits rate            0.00 %
Cache misses                780
Cache size                    0 bytes

Zero stored bytes on a byte-identical tree. Module compilations depend on BMIs that sccache cannot hash reliably, so results are never stored. A persistent volume for the cache directory is therefore pointless here — harmless to leave wired up, but do not expect a speedup. On non-module codebases sccache is still worth using; this finding is specific to C++20/23 modules.

A named volume as the build directory#

Mounting a Docker named volume at the build directory looks like the natural fix. CMake cannot configure inside one:

CMakeTestCXXCompiler.cmake:71 (message)
  ninja: error: loading 'build.ninja': The system cannot find the file specified.

Reproduces with a freshly created volume, so it is not stale state. Windows container volumes are filter-driver backed and do not behave like an ordinary directory for the operations CMake’s compiler test performs.

The image does not fit on C:, and that is the default#

On a GitHub-hosted windows-2025 runner, Docker keeps its data-root under the system drive (C:\ProgramData\Docker). That drive is the small one. Measured 2026-08-11 at job start:

DriveLetter FreeGB SizeGB FileSystemLabel
          C  33.00 149.40 Windows
          D 146.60 150.00 Temporary Storage

The winamd64 image needs ~54 GB to import. It does not fit in 33 GB, and the failure is expensive rather than obvious: docker pull grinds for tens of minutes and then dies with hcsshim::ImportLayer ... not enough space on the disk (0x70).

The historical workaround was cleanup-disk-space, which deletes Visual Studio and the tool caches to claw C: up to ~71 GB. That works, costs minutes, is destructive — and leaves a 150 GB drive sitting at 146.6 GB free.

Point the data-root at the big drive instead, with the set-docker-data-root action, before the pull:

- name: 'Put the Docker data-root on D:'
  uses: Kataglyphis/Kataglyphis-ContainerHub/.github/actions/set-docker-data-root@main
  with:
    data-root: 'D:\docker'

Measured on the same job, across the whole run:

Point in the job

C: free

D: free

start

33.00

146.60

after the data-root move

33.00

146.60

after cleanup-disk-space

71.20

146.60

after docker pull

71.20

108.10

D: absorbs 38.5 GB; C: does not move at all, even though 71 GB were free there by then. The daemon confirms it independently: Docker data-root: D:\docker.

Things worth knowing before you copy this:

  • Order is not negotiable. Run it before the pull. Changing the data-root makes images under the old one invisible, so doing it afterwards throws away a pull you already paid for.

  • It merges into an existing daemon.json. The runners ship one — on the measured job it contained {"hosts":["npipe://"]}. Overwriting that would have taken the daemon’s named-pipe listener with it.

  • D: is not the same size everywhere. Two runners on the same day reported 150 GB and 220 GB. The action’s required-free-gb checks the target drive rather than assuming, so a wrong drive letter fails in seconds with a clear message instead of during the import.

  • D: is the ephemeral temp disk on hosted runners — wiped between jobs, which is right for CI and wrong for a self-hosted machine you expect to keep a layer cache on. Point data-root somewhere persistent there.

  • cleanup-disk-space still earns its place — checkout, toolchain and build live on C: — but it is no longer what makes the image fit.

Gotchas that cost real time#

  • Windows path limit inside containers. Deeply nested paths (here: Rust cxxbridge output under cargo/) fail to extract:

    ...out/cxxbridge/include/.../native_only.rs:
      Can't create '\\?\C:\ws\...': Invalid argument
    tar: Error exit delayed from previous errors
    

    One such failure aborts the entire tar transfer, so a single deep path silently turns a full transfer into a partial one. Exclude those subtrees.

  • Dev Drive rejects bind mounts. The filesystem minifilter cannot attach (“Der Dateisystem-Minifilter kann nicht an das Entwicklervolume angefügt werden”), which forces the tar-pipe transport in the first place. Allow- listing the filters lifts the restriction — but measured slower here; see “What does not work” above before reaching for it.

  • Containers survive successful builds (wcifs teardown lock). A lingering container makes it look like a build is still running. Compare the newest build-summary timestamp against the container start time before assuming, and reap stale containers by name.

  • docker exec bypasses the image entrypoint. When driving a long-lived container with docker exec (rather than docker run), the entrypoint that sets up the VS developer environment and the clang-cl ASAN runtime DLL directory never runs. Invoke it explicitly:

    docker exec -w C:\ws $container cmd /S /C C:	emp\scripts\entrypoint.cmd @buildArgs
    

    Symptoms if you forget: compilers “not found”, or ASAN binaries failing to start because clang_rt.asan*.dll is not on PATH.

  • Mount over a fresh path. Mounting onto a directory baked into the image (e.g. C:\workspace) fails at CreateComputeSystem when the host OS build differs from the image base build. Use a path absent from the image — and if you support both transports, make it the same path the tar-pipe extracts to (C:\ws), not a separate one, or CMake rejects the cache on every switch. See Transports.

Reusable implementation#

The pattern is implemented here so consumers do not copy it: windows/scripts/modules/WindowsContainerBuild.Reuse.psm1 (Get-ReusableBuildContainer, Copy-IntoBuildContainer, Copy-FromBuildContainer, Initialize-ContainerPwsh, Remove-StaleContainerSources, Test-BuildArtifactsDelivered, Remove-BuildContainerSafe). Import it via the consumer’s module resolver. Initialize-ContainerPwsh, Remove-StaleContainerSources and Test-BuildArtifactsDelivered are the safety rails of the reusable-container pattern as functions: ensure pwsh exists in the image, prune stale sources on reuse (tar never deletes), and verify every built executable actually reached the host before trusting a green build. Remove-BuildContainerSafe removes a container while tolerating the wcifs teardown lock.

Applying this elsewhere#

The pattern generalises to any large project built in a Windows container:

  1. One reusable container, keyed by name, recreated when the image changes.

  2. Sources in, artifacts out — never the intermediate build tree.

  3. An explicit “start clean” switch, because reuse means staleness.

  4. Exclude deep paths from tar transfers before they abort silently.