Build Perf Diagnostics

作者 dotnet0608d8924cd3MIT5.5K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫今天更新

Diagnose MSBuild build performance bottlenecks using binary log analysis. USE FOR: identifying why builds are slow by analyzing binlog performance summaries, detecting ResolveAssemblyReference (RAR) taking >5s, Roslyn analyzers consuming >30% of Csc time, single targets dominating >50% of build time, node utilization below 80%, excessive Copy tasks, NuGet restore running every build. Covers timeline analysis, Target/Task Performance Summary interpretation, and 7 common bottleneck categories. Use after build-perf-baseline has established measurements. DO NOT USE FOR: establishing initial baselines (use build-perf-baseline first), fixing incremental build issues (use incremental-build), parallelism tuning (use build-parallelism), non-MSBuild build systems.

AI 產生的概覽

透過分析二進位記錄檔與效能摘要,診斷 MSBuild 建置效能瓶頸。

功能
此技能提供一套方法,用來找出 MSBuild 建置緩慢的原因,可分析二進位記錄檔(binlog),或將 binlog 重放為附帶效能摘要的診斷文字記錄檔。它說明如何解讀目標與工作效能摘要、檢查節點使用率、分析器耗時與 RAR 耗時是否超過既定門檻,並整理出七類常見瓶頸的症狀、根本原因與修正方式。產出是依影響程度分級的排查結論,而非檔案或程式碼成品。
適用情境
適用於已建立建置效能基準之後,需要找出 MSBuild 或 dotnet 建置緩慢原因的情況。適合排查緩慢的目標、耗時的分析器、過多的 Copy 工作、重複的 NuGet 還原或平行度不足等問題。不適用於建立初始基準、修正增量建置問題、調整平行度或非 MSBuild 建置系統。
執行需求
需要 .NET SDK(dotnet build 與 dotnet msbuild)以及產生的 binlog 檔案。主要流程依賴 binlog MCP 伺服器(Microsoft.AITools.BinlogMcp,位於 binlog MCP 命名空間下);替代流程使用文字記錄檔重放搭配 grep。未隨附指令碼。

Performance Analysis Methodology

  1. Generate a binlog: dotnet build /bl:{} -m
  2. Use the binlog MCP server (Microsoft.AITools.BinlogMcp, exposed under the binlog MCP namespace) which is bundled with this plugin

Alternate flow when MCP is unavailable: binlog replay to text logs

  1. Generate a binlog: dotnet build /bl:{} -m
  2. Replay to diagnostic log with performance summary:
    bash
    dotnet msbuild build.binlog -noconlog -fl "-flp:v=diag;logfile=full.log;performancesummary"
  3. Read the performance summary (at the end of full.log):
    bash
    grep "Target Performance Summary\|Task Performance Summary" -A 50 full.log
  4. Find expensive targets and tasks: The PerformanceSummary section lists all targets/tasks sorted by cumulative time
  5. Check for node utilization: grep for scheduling and node messages
    bash
    grep -i "node.*assigned\|building with\|scheduler" full.log | head -30
  6. Check analyzers: grep for analyzer timing
    bash
    grep -i "analyzer.*elapsed\|Total analyzer execution time\|CompilerAnalyzerDriver" full.log

Key Metrics and Thresholds

  • Build duration: what's "normal" — small project <10s, medium <60s, large <5min
  • Node utilization: ideal is >80% active time across nodes. Low utilization = serialization bottleneck
  • Single target domination: if one target is >50% of build time, investigate
  • Analyzer time vs compile time: analyzers should be <30% of Csc task time. If higher, consider removing expensive analyzers
  • RAR time: ResolveAssemblyReference >5s is concerning. >15s is pathological

Common Bottlenecks

1. ResolveAssemblyReference (RAR) Slowness

  • Symptoms: RAR taking >5s per project
  • Root causes: too many assembly references, network-based reference paths, large assembly search paths
  • Fixes: reduce reference count, use <DesignTimeBuild>false</DesignTimeBuild> for RAR-heavy analysis, set <ResolveAssemblyReferencesSilent>true</ResolveAssemblyReferencesSilent> for diagnostic
  • Advanced: <DesignTimeBuild> and <ResolveAssemblyWarnOrErrorOnTargetArchitectureMismatch>
  • Key insight: RAR runs unconditionally even on incremental builds because users may have installed targeting packs or GACed assemblies (see dotnet/msbuild#2015). With .NET Core micro-assemblies, the reference count is often very high.
  • Reduce transitive references: Set <DisableTransitiveProjectReferences>true</DisableTransitiveProjectReferences> to avoid pulling in the full transitive closure (note: projects may need to add direct references for any types they consume). Use ReferenceOutputAssembly="false" on ProjectReferences that are only needed at build time (not API surface). Trim unused PackageReferences.

2. Roslyn Analyzers and Source Generators

  • Symptoms: Csc task takes much longer than expected for file count (>2× clean compile time)
  • Diagnosis: Check the Task Performance Summary in the replayed log for Csc task time; grep for analyzer timing messages; compare Csc duration with and without analyzers (/p:RunAnalyzers=false)
  • Fixes:
    • Conditionally disable in dev: <RunAnalyzers Condition="'$(ContinuousIntegrationBuild)' != 'true'">false</RunAnalyzers>
    • Per-configuration: <RunAnalyzers Condition="'$(Configuration)' == 'Debug'">false</RunAnalyzers>
    • Code-style only: <EnforceCodeStyleInBuild Condition="'$(ContinuousIntegrationBuild)' == 'true'">true</EnforceCodeStyleInBuild>
    • Remove genuinely redundant analyzers from inner loop
    • Severity config in .editorconfig for less critical rules
  • Key principle: Preserve analyzer enforcement in CI. Never just "remove" analyzers — configure them conditionally.
  • GlobalPackageReference: Analyzers added via GlobalPackageReference in Directory.Packages.props apply to ALL projects. Consider if test projects need the same analyzer set as production code.
  • EnforceCodeStyleInBuild: When set to true in Directory.Build.props, forces code-style analysis on every build. Should be conditional on CI environment (ContinuousIntegrationBuild) to avoid slowing dev inner loop.

3. Serialization Bottlenecks (Single-threaded targets)

  • Symptoms: Performance summary shows most build time concentrated in a single project; diagnostic log shows idle nodes while one works
  • Common culprits: targets without proper dependency declaration, single project on critical path
  • Fixes: split large projects, optimize the critical path project, ensure proper BuildInParallel

4. Excessive File I/O (Copy tasks)

  • Symptoms: Copy task shows high aggregate time
  • Root causes: copying thousands of files, copying across network drives, Copy task unintentionally running once per item (per-file) instead of as a single batch (see dotnet/msbuild#12884)
  • Fixes: use hardlinks (<CreateHardLinksForCopyFilesToOutputDirectoryIfPossible>true</CreateHardLinksForCopyFilesToOutputDirectoryIfPossible>), reduce CopyToOutputDirectory items, use <UseCommonOutputDirectory>true</UseCommonOutputDirectory> when appropriate, set <SkipCopyUnchangedFiles>true</SkipCopyUnchangedFiles>, consider --artifacts-path (.NET 8+) for centralized output layout
  • Dev Drive: On Windows, switching to a Dev Drive (ReFS with copy-on-write and reduced Defender scans) can significantly reduce file I/O overhead for Copy-heavy builds. Recommend for both dev machines and self-hosted CI agents.

5. Evaluation Overhead

  • Symptoms: build starts slow before any compilation
  • Root causes: complex Directory.Build.props, wildcard globs scanning large directories, NuGetSdkResolver overhead (adds 180-400ms per project evaluation even when restored — see dotnet/msbuild#4025)
  • Fixes: reduce Directory.Build.props complexity, use <EnableDefaultItems>false</EnableDefaultItems> for legacy projects with explicit file lists, avoid NuGet-based SDK resolvers if possible
  • See: eval-performance skill for detailed guidance

6. NuGet Restore in Build

  • Symptoms: restore runs every build even when unnecessary
  • Fixes:
    • Separate restore from build: dotnet restore then dotnet build --no-restore
    • Enable static graph evaluation: <RestoreUseStaticGraphEvaluation>true</RestoreUseStaticGraphEvaluation> in Directory.Build.props — can save significant time in large builds (results are workload-dependent)

7. Large Project Count and Graph Shape

  • Symptoms: many small projects, each takes minimal time but overhead adds up; deep dependency chains serialize the build
  • Consider: project consolidation, or use /graph mode for better scheduling
  • Graph shape matters: a wide dependency graph (few levels, many parallel branches) builds faster than a deep one (many levels, serialized). Refactoring from deep to wide can yield significant improvements in both clean and incremental build times.
  • Actions: look for unnecessary project dependencies, consider splitting a bottleneck project into two, or merging small leaf projects

Using Binlog Replay for Performance Analysis

Step-by-step workflow using text log replay:

  1. Replay with performance summary:
    bash
    dotnet msbuild build.binlog -noconlog -fl "-flp:v=diag;logfile=full.log;performancesummary"
  2. Read target/task performance summaries (at the end of full.log):
    bash
    grep "Target Performance Summary\|Task Performance Summary" -A 50 full.log
    This shows all targets and tasks sorted by cumulative time — equivalent to finding expensive targets/tasks.
  3. Find per-project build times:
    bash
    grep "done building project\|Project Performance Summary" full.log
  4. Check parallelism (multi-node scheduling):
    bash
    grep -i "node.*assigned\|RequiresLeadingNewline\|Building with" full.log | head -30
  5. Check analyzer overhead:
    bash
    grep -i "Total analyzer execution time\|analyzer.*elapsed\|CompilerAnalyzerDriver" full.log
  6. Drill into a specific slow target:
    bash
    grep 'Target "CoreCompile"\|Target "ResolveAssemblyReferences"' full.log

Quick Wins Checklist

  • Use /maxcpucount (or -m) for parallel builds
  • Separate restore from build (dotnet restore then dotnet build --no-restore)
  • Enable static graph restore (<RestoreUseStaticGraphEvaluation>true</RestoreUseStaticGraphEvaluation>)
  • Enable hardlinks for Copy (<CreateHardLinksForCopyFilesToOutputDirectoryIfPossible>true</CreateHardLinksForCopyFilesToOutputDirectoryIfPossible>)
  • Disable analyzers conditionally in dev inner loop: <RunAnalyzers Condition="'$(ContinuousIntegrationBuild)' != 'true'">false</RunAnalyzers>
  • Enable reference assemblies (<ProduceReferenceAssembly>true</ProduceReferenceAssembly>)
  • Check for broken incremental builds (see incremental-build skill)
  • Check for bin/obj clashes (see check-bin-obj-clash skill)
  • Use graph build (/graph) for multi-project solutions
  • Use --artifacts-path (.NET 8+) for centralized output layout
  • Enable Dev Drive (ReFS) on Windows dev machines and self-hosted CI

Impact Categorization

When reporting findings, categorize by impact to help prioritize fixes:

  • 🔴 HIGH IMPACT (do first): Items consuming >10% of total build time, or a single target >50% of build time
  • 🟡 MEDIUM IMPACT: Items consuming 2-10% of build time
  • 🟢 QUICK WINS: Easy changes with modest impact (e.g., property flags in Directory.Build.props)

來源與署名

來源:dotnet/skills位於plugins/dotnet-msbuild/skills/build-perf-diagnostics提交0608d89

授權條款: MIT

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

檢舉或申請下架