Fail bazel.bat early if 8.3 short names are disabled in Windows

[rdesgroppes]

What does this PR do?

Add a preflight check that creates a temp file whose name exceeds 8.3 limits and compare its long name (%%~nxi) against its short name (%%~snxi).

When they are equal, GetShortPathNameW is a no-op, meaning 8.3 short names are disabled and the hook exits with actionable instructions.

Motivation

GetShortPathNameW is a no-op when 8.3 short names are disabled, causing Bazel to fail with an internal path-length error (bazelbuild/bazel#19710), even with the 260-character OS limit lifted.

GitLab runners had the volume state enabled, but Docker containers did not, root cause of #incident-56436.
The latter is now fixed by the combo:

• [#incident-56436] Enable NTFS 8.3 short names at startup datadog-agent-buildimages#1215
• [#incldent-56436] Update dependency windows-images to v120143276 #52561.

The present change makes it fail fast with actionable instructions rather than a cryptic Bazel error.

Describe how you validated your changes

Before #52561 was merged: https://gitlab.ddbuild.io/DataDog/datadog-agent/-/jobs/1788332180#L48

Additional Notes

To be reverted once following upstream fix (or equivalent) is available:

• Fix launching executables whose path can't be shortened on Windows bazelbuild/bazel#29921.

[datadog-datadog-prod-us1-2]

✨ Fix all issues with BitsAI

⚠️ Warnings

🚦 1 Pipeline job failed

DataDog/datadog-agent | oracle: [21.3.0-xe]     

ℹ️ Info

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 51.05% (+0.11%)

Useful? React with 👍 / 👎

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🔗 Commit SHA: 966bcd3 | Docs | Datadog PR Page | Give us feedback!}

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[dd-octo-sts]

Files inventory check summary

File checks results against ancestor 29a81a22:

Results for datadog-agent_7.82.0~devel.git.242.966bcd3.pipeline.120237285-1_amd64.deb:

No change detected

[cit-pr-commenter-54b7da]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 2f65871d-46af-4965-b69b-98720e871406

Baseline: 5b40697
Comparison: 0fffd5d
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gate_logs	% cpu utilization	+1.16	[+0.10, +2.22]	1	Logs bounds checks dashboard
➖	quality_gate_idle	memory utilization	+0.66	[+0.61, +0.71]	1	Logs bounds checks dashboard
➖	quality_gate_security_idle	memory utilization	+0.07	[+0.01, +0.14]	1	Logs bounds checks dashboard
➖	quality_gate_idle_all_features	memory utilization	-0.10	[-0.14, -0.06]	1	Logs bounds checks dashboard
➖	quality_gate_security_no_fs_load	memory utilization	-0.50	[-0.60, -0.40]	1	Logs bounds checks dashboard
➖	quality_gate_security_mean_fs_load	memory utilization	-0.60	[-0.64, -0.56]	1	Logs bounds checks dashboard
➖	quality_gate_metrics_logs	memory utilization	-1.69	[-1.93, -1.44]	1	Logs bounds checks dashboard

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	quality_gate_idle	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	145.44MiB ≤ 154MiB	bounds checks dashboard
✅	quality_gate_idle	total_bytes_received	10/10	574.94KiB ≤ 819.20KiB	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	482.83MiB ≤ 495MiB	bounds checks dashboard
✅	quality_gate_idle_all_features	total_bytes_received	10/10	0.89MiB ≤ 1.25MiB	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10	4 ≤ 6	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	181.33MiB ≤ 195MiB	bounds checks dashboard
✅	quality_gate_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_logs	total_bytes_received	10/10	263.88MiB ≤ 292MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	330.40 ≤ 2000	bounds checks dashboard
✅	quality_gate_metrics_logs	intake_connections	10/10	3 ≤ 6	bounds checks dashboard
✅	quality_gate_metrics_logs	memory_usage	10/10	394.40MiB ≤ 430MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_metrics_logs	total_bytes_received	10/10	0.86GiB ≤ 1.04GiB	bounds checks dashboard
✅	quality_gate_security_idle	cpu_usage	10/10	30.36 ≤ 40	bounds checks dashboard
✅	quality_gate_security_idle	memory_usage	10/10	299.09MiB ≤ 330MiB	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	cpu_usage	10/10	61.91 ≤ 70	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	memory_usage	10/10	274.68MiB ≤ 320MiB	bounds checks dashboard
✅	quality_gate_security_no_fs_load	cpu_usage	10/10	24.23 ≤ 40	bounds checks dashboard
✅	quality_gate_security_no_fs_load	memory_usage	10/10	277.66MiB ≤ 320MiB	bounds checks dashboard

Explanation

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

3. Its configuration does not mark it "erratic".

Replicate Execution Details

We run multiple replicates for each experiment/variant. However, we allow replicates to be automatically retried if there are any failures, up to 8 times, at which point the replicate is marked dead and we are unable to run analysis for the entire experiment. We call each of these attempts at running replicates a replicate execution. This section lists all replicate executions that failed due to the target crashing or being oom killed.

Note: In the below tables we bucket failures by experiment, variant, and failure type. For each of these buckets we list out the replicate indexes that failed with an annotation signifying how many times said replicate failed with the given failure mode. In the below example the baseline variant of the experiment named experiment_with_failures had two replicates that failed by oom kills. Replicate 0, which failed 8 executions, and replicate 1 which failed 6 executions, all with the same failure mode.

Experiment	Variant	Replicates	Failure	Logs	Debug Dashboard
experiment_with_failures	baseline	0 (x8) 1 (x6)	Oom killed		Debug Dashboard

The debug dashboard links will take you to a debugging dashboard specifically designed to investigate replicate execution failures.

❌ Retried Profiling Replicate Execution Failures (ddprof)

Note: Profiling replicas may still be executing. See the debug dashboard for up to date status.

Experiment	Variant	Replicates	Failure	Debug Dashboard
quality_gate_idle_all_features	baseline	10	Oom killed	Debug Dashboard
quality_gate_idle_all_features	comparison	10	Oom killed	Debug Dashboard
quality_gate_metrics_logs	baseline	10	Oom killed	Debug Dashboard
quality_gate_metrics_logs	comparison	10	Oom killed	Debug Dashboard
quality_gate_security_idle	comparison	10	Oom killed	Debug Dashboard
quality_gate_security_no_fs_load	baseline	10	Oom killed	Debug Dashboard
quality_gate_security_no_fs_load	comparison	10	Oom killed	Debug Dashboard

CI Pass/Fail Decision

✅ Passed. All Quality Gates passed.

• quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check total_bytes_received: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check total_bytes_received: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check total_bytes_received: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_security_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_idle, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check total_bytes_received: 10/10 replicas passed. Gate passed.
• quality_gate_security_mean_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_mean_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_no_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_no_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.

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[dd-octo-sts]

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor 29a81a2
📊 Static Quality Gates Dashboard
🔗 SQG Job

33 successful checks with minimal change (< 2 KiB)

	Quality gate	Current Size
✅	agent_deb_amd64	747.917 MiB
✅	agent_deb_amd64_fips	703.861 MiB
✅	agent_heroku_amd64	308.587 MiB
✅	agent_msi	615.907 MiB
✅	agent_rpm_amd64	747.900 MiB
✅	agent_rpm_amd64_fips	703.845 MiB
✅	agent_rpm_arm64	723.523 MiB
✅	agent_rpm_arm64_fips	683.115 MiB
✅	agent_suse_amd64	747.900 MiB
✅	agent_suse_amd64_fips	703.845 MiB
✅	agent_suse_arm64	723.523 MiB
✅	agent_suse_arm64_fips	683.115 MiB
✅	docker_agent_amd64	807.616 MiB
✅	docker_agent_arm64	808.134 MiB
✅	docker_agent_jmx_amd64	998.513 MiB
✅	docker_agent_jmx_arm64	987.683 MiB
✅	docker_cluster_agent_amd64	208.044 MiB
✅	docker_cluster_agent_arm64	221.251 MiB
✅	docker_cws_instrumentation_amd64	7.447 MiB
✅	docker_cws_instrumentation_arm64	6.877 MiB
✅	docker_dogstatsd_amd64	39.008 MiB
✅	docker_dogstatsd_arm64	37.117 MiB
✅	docker_host_profiler_amd64	304.990 MiB
✅	docker_host_profiler_arm64	316.090 MiB
✅	dogstatsd_deb_amd64	29.747 MiB
✅	dogstatsd_deb_arm64	27.798 MiB
✅	dogstatsd_rpm_amd64	29.747 MiB
✅	dogstatsd_suse_amd64	29.747 MiB
✅	iot_agent_deb_amd64	45.675 MiB
✅	iot_agent_deb_arm64	42.390 MiB
✅	iot_agent_deb_armhf	43.175 MiB
✅	iot_agent_rpm_amd64	45.676 MiB
✅	iot_agent_suse_amd64	45.675 MiB

[dd-octo-sts]

Gitlab CI Configuration Changes

Modified Jobs

variables (configuration)

  variables:
    AGENT_API_KEY_ORG2: agent-api-key-org-2
    AGENT_APP_KEY_ORG2: agent-app-key-org-2
    AGENT_BINARIES_DIR: bin/agent
    AGENT_QA_E2E: agent-qa-e2e
    API_KEY_ORG2: ci.datadog-agent.datadog_api_key_org2
    ARTIFACT_DOWNLOAD_ATTEMPTS: 2
    ATLASSIAN_WRITE: atlassian-write
    BTFHUB_ARCHIVE_BRANCH: main
    BUCKET_BRANCH: dev
    CACHE_COMPRESSION_LEVEL: slowest
    CHANGELOG_COMMIT_SHA: ci.datadog-agent.gitlab_changelog_commit_sha
    CHOCOLATEY_API_KEY: ci.datadog-agent.chocolatey_api_key
    CI_IMAGE_BTF_GEN: v118883148-8fa6a628
    CI_IMAGE_BTF_GEN_SUFFIX: ''
    CI_IMAGE_DOCKER_ARM64: v118883148-8fa6a628
    CI_IMAGE_DOCKER_ARM64_SUFFIX: ''
    CI_IMAGE_DOCKER_X64: v118883148-8fa6a628
    CI_IMAGE_DOCKER_X64_SUFFIX: ''
    CI_IMAGE_GITLAB_AGENT_DEPLOY: v118883148-8fa6a628
    CI_IMAGE_GITLAB_AGENT_DEPLOY_SUFFIX: ''
    CI_IMAGE_LINUX: v118883148-8fa6a628
    CI_IMAGE_LINUX_SUFFIX: ''
    CI_IMAGE_RPM_ARM64: v118883148-8fa6a628
    CI_IMAGE_RPM_ARM64_SUFFIX: ''
    CI_IMAGE_RPM_ARMHF: v118883148-8fa6a628
    CI_IMAGE_RPM_ARMHF_SUFFIX: ''
    CI_IMAGE_RPM_X64: v118883148-8fa6a628
    CI_IMAGE_RPM_X64_SUFFIX: ''
-   CI_IMAGE_WIN_LTSC2022_X64: v119961810-e18b0f68
+   CI_IMAGE_WIN_LTSC2022_X64: v120051755-ba1d8fc3
-   CI_IMAGE_WIN_LTSC2022_X64_SUFFIX: ''
?                                     ^^
+   CI_IMAGE_WIN_LTSC2022_X64_SUFFIX: _test_only
?                                     ^^^^^^^^^^
-   CI_IMAGE_WIN_LTSC2025_X64: v119961810-e18b0f68
+   CI_IMAGE_WIN_LTSC2025_X64: v120051755-ba1d8fc3
-   CI_IMAGE_WIN_LTSC2025_X64_SUFFIX: ''
?                                     ^^
+   CI_IMAGE_WIN_LTSC2025_X64_SUFFIX: _test_only
?                                     ^^^^^^^^^^
    CLANG_BUILD_VERSION: v60409452-ee70de70
    CLANG_LLVM_VER: 12.0.1
    CLUSTER_AGENT_BINARIES_DIR: bin/datadog-cluster-agent
    CLUSTER_AGENT_CLOUDFOUNDRY_BINARIES_DIR: bin/datadog-cluster-agent-cloudfoundry
    CODECOV: codecov
    CODECOV_TOKEN: ci.datadog-agent.codecov_token
    COMPARE_TO_BRANCH: main
    CRC_PULL_SECRET: ci.datadog-agent.crc-pull-secret
    CWS_INSTRUMENTATION_BINARIES_DIR: bin/cws-instrumentation
    DATADOG_AGENT_EMBEDDED_PATH: /opt/datadog-agent/embedded
    DDA_CLIENT_TOKEN: dda-feature-flags-client-token
    DDA_FEATURE_FLAGS_CI_SSM_KEY_WINDOWS: ci.datadog-agent.dda-feature-flags-client-token
    DDA_FEATURE_FLAGS_CI_VAULT_KEY: token
    DDA_FEATURE_FLAGS_CI_VAULT_KEY_MACOS: token
    DDA_FEATURE_FLAGS_CI_VAULT_PATH: k8s/gitlab-runner-datadog-agent/datadog-agent/$DDA_CLIENT_TOKEN
    DDA_FEATURE_FLAGS_CI_VAULT_PATH_MACOS: aws/arn:aws:iam::486234852809:role/ci-datadog-agent/$DDA_CLIENT_TOKEN
    DD_AGENT_TESTING_DIR: $CI_PROJECT_DIR/test/new-e2e/tests
    DD_PKG_GITLAB_URL: https://artifact-gateway.us1.ddbuild.io/internal/artifact-gateway/api/v4
    DEB_GPG_KEY_ID: c0962c7d
    DEB_GPG_KEY_NAME: Datadog, Inc. APT key
    DEB_RPM_TESTING_BUCKET_BRANCH: testing
    DEB_S3_BUCKET: apt.datad0g.com
    DEB_TESTING_S3_BUCKET: apttesting.datad0g.com
    DOCKER_REGISTRY_RO: dockerhub-readonly
    DOCKER_REGISTRY_URL: docker.io
    DOGSTATSD_BINARIES_DIR: bin/dogstatsd
    DYNAMIC_TESTS_BREAKGLASS: dynamic-tests-breakglass
    E2E_AZURE: e2e-azure
    E2E_COVERAGE_PIPELINE: false
    E2E_GCP: e2e-gcp
    EXECUTOR_JOB_SECTION_ATTEMPTS: 2
    FF_CLEAN_UP_FAILED_CACHE_EXTRACT: true
    FF_KUBERNETES_HONOR_ENTRYPOINT: true
    FF_SCRIPT_SECTIONS: 1
    FF_TIMESTAMPS: true
    FF_USE_FASTZIP: true
    FF_USE_WINDOWS_JOB_OBJECT: true
    GENERAL_ARTIFACTS_CACHE_BUCKET_URL: https://dd-agent-omnibus.s3.amazonaws.com
    GET_SOURCES_ATTEMPTS: 2
    GIT_STRATEGY: s3
    GO_TEST_SKIP_FLAKE: 'true'
    GPG_TEST_KEY_ID: crypto/k8s/keys/k8s_gitlab-runner-datadog-agent_datadog-agent_testing_signing-key
    INSTALLER_TESTING_S3_BUCKET: installtesting.datad0g.com
    INSTALL_SCRIPT_API_KEY_ORG2: install-script-api-key-org-2
    INTEGRATION_WHEELS_CACHE_BUCKET: dd-agent-omnibus
    KERNEL_MATRIX_TESTING_ARM_AMI_ID: ami-0b5f838a19d37fc61
    KERNEL_MATRIX_TESTING_X86_AMI_ID: ami-05b3973acf5422348
    KITCHEN_INFRASTRUCTURE_FLAKES_RETRY: 2
    MACOS_APPLE_APPLICATION_SIGNING: apple-application-signing
    MACOS_APPLE_DEVELOPER_ACCOUNT: apple-developer-account
    MACOS_APPLE_INSTALLER_SIGNING: apple-installer-signing
    MACOS_KEYCHAIN_PWD: ci-keychain
    MACOS_S3_BUCKET: dd-agent-macostesting
    OMNIBUS_BASE_DIR: /omnibus
    OMNIBUS_GIT_CACHE_DIR: /tmp/omnibus-git-cache
    OMNIBUS_PACKAGE_DIR: $CI_PROJECT_DIR/omnibus/pkg/
    OMNIBUS_PACKAGE_DIR_SUSE: $CI_PROJECT_DIR/omnibus/suse/pkg
    PIPELINE_KEY_ALIAS: alias/ci_datadog-agent_pipeline-key
    PROCESS_S3_BUCKET: datad0g-process-agent
    PYTHONUNBUFFERED: 1
    RESTORE_CACHE_ATTEMPTS: 2
    RPM_GPG_KEY_ID: b01082d3
    RPM_GPG_KEY_NAME: Datadog, Inc. RPM key
    RPM_S3_BUCKET: yum.datad0g.com
    RPM_TESTING_S3_BUCKET: yumtesting.datad0g.com
    RUN_E2E_TESTS: auto
    RUN_KMT_TESTS: auto
    RUN_UNIT_TESTS: auto
    S3_ARTIFACTS_URI: s3://dd-ci-artefacts-build-stable/$CI_PROJECT_NAME/$CI_PIPELINE_ID
    S3_CP_CMD: aws s3 cp $S3_CP_OPTIONS
    S3_CP_OPTIONS: --no-progress --region us-east-1 --sse AES256
    S3_DD_AGENT_OMNIBUS_BTFS_URI: s3://dd-agent-omnibus/btfs
    S3_DD_AGENT_OMNIBUS_JAVA_URI: s3://dd-agent-omnibus/openjdk
    S3_DD_AGENT_OMNIBUS_LLVM_URI: s3://dd-agent-omnibus/llvm
    S3_DSD6_URI: s3://dsd6-staging
    S3_OMNIBUS_CACHE_BUCKET: dd-ci-datadog-agent-omnibus-cache-build-stable
    S3_OMNIBUS_GIT_CACHE_BUCKET: dd-ci-datadog-agent-omnibus-git-cache-build-stable
    S3_PERMANENT_ARTIFACTS_URI: s3://dd-ci-persistent-artefacts-build-stable/$CI_PROJECT_NAME
    S3_PROJECT_ARTIFACTS_URI: s3://dd-ci-artefacts-build-stable/$CI_PROJECT_NAME
    S3_RELEASE_ARTIFACTS_URI: s3://dd-release-artifacts/$CI_PROJECT_NAME/$CI_PIPELINE_ID
    S3_RELEASE_INSTALLER_ARTIFACTS_URI: s3://dd-release-artifacts/datadog-installer/$CI_PIPELINE_ID
    S3_SBOM_STORAGE_URI: s3://sbom-root-us1-ddbuild-io/$CI_PROJECT_NAME/$CI_PIPELINE_ID
    SECRET_GENERIC_CONNECTOR_BINARIES_DIR: bin/secret-generic-connector
    SKIP_WINDOWS: 'false'
    SLACK_AGENT: slack-agent-ci
    SMP_ACCOUNT: smp
    STATIC_BINARIES_DIR: bin/static
    SYSTEM_PROBE_BINARIES_DIR: bin/system-probe
    TEST_KEYS_URL: apttesting.datad0g.com/test-keys
    VCPKG_BLOB_SAS_URL: ci.datadog-agent-buildimages.vcpkg_blob_sas_url
    VIRUS_TOTAL: virus-total
    WINDOWS_BUILDS_S3_BUCKET: $WIN_S3_BUCKET/builds
    WINDOWS_POWERSHELL_DIR: $CI_PROJECT_DIR/signed_scripts
    WINDOWS_SYMBOLS_S3_BUCKET: pipelines/windows-symbols
    WINDOWS_TESTING_S3_BUCKET: pipelines/A7/$CI_PIPELINE_ID
    WINGET_PAT: ci.datadog-agent.winget_pat
    WIN_S3_BUCKET: dd-agent-mstesting

Changes Summary

Removed	Modified	Added	Renamed
0	1	0	0

ℹ️ Diff available in the job log.

[chatgpt-codex-connector]

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[chouquette]

LGTM but what happens when the cache is on a different drive as the bazel output root? (Just kidding, don't hurt me)

[rdesgroppes]

LGTM but what happens when the cache is on a different drive as the bazel output root? (Just kidding, don't hurt me)

@chouquette That's in fact the case in CI: the cache (--output_user_root=C:\bzl) is hosted on a GitLab runner volume, bind-mounted in the container (8.3 enabled, the default), whereas the "volatile" area (--output_base=C:\bob) is the problematic one (8.3 disabled, oops).

In the real life, the problem manifests itself only in Windows containers due to their volume metadata being not persisted as a container layer:

• 8dot3name short name creation not persisted microsoft/Windows-Containers#507.

More details in:

• [#incident-56436] Enable NTFS 8.3 short names at startup datadog-agent-buildimages#1215.

[chouquette]

LGTM but what happens when the cache is on a different drive as the bazel output root? (Just kidding, don't hurt me)

@chouquette That's in fact the case in CI: the cache (--output_user_root=C:\bzl) is hosted on a GitLab runner volume bind-mounted in the container (8.3 enabled, the default), whereas the "volatile" area (--output_base=C:\bob) is the problematic one (8.3 disabled, oops).

In the real life, the problem manifests itself only in Windows containers due to their volume metadata being not persisted as a container layer:

• microsoft/Windows-Containers#507.

More details in:

• DataDog/datadog-agent-buildimages#1215.

@rdesgroppes I should have known better than jokingly asking a question and not expect an answer from you 😁