Build Perf Diagnostics

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 ``

1. Read the performance summary (at the end of full.log):

``bash grep "Target Performance Summary\|Task Performance Summary" -A 50 full.log ``

1. Find expensive targets and tasks: The PerformanceSummary section lists all targets/tasks sorted by cumulative time
2. Check for node utilization: grep for scheduling and node messages

``bash grep -i "node.*assigned\|building with\|scheduler" full.log | head -30 ``

1. 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 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 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 false for RAR-heavy analysis, set true for diagnostic
• Advanced: ` and `
• 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 true 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: false
• Per-configuration: false
• Code-style only: true
• 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 (true), reduce CopyToOutputDirectory items, use true when appropriate, set true, 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 false 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: true 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 ``

1. 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.

1. Find per-project build times:

``bash grep "done building project\|Project Performance Summary" full.log ``

1. Check parallelism (multi-node scheduling):

``bash grep -i "node.*assigned\|RequiresLeadingNewline\|Building with" full.log | head -30 ``

1. Check analyzer overhead:

``bash grep -i "Total analyzer execution time\|analyzer.*elapsed\|CompilerAnalyzerDriver" full.log ``

1. 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 (true)
• [ ] Enable hardlinks for Copy (true)
• [ ] Disable analyzers conditionally in dev inner loop: false
• [ ] Enable reference assemblies (true)
• [ ] 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)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: dotnet
• Source: dotnet/skills
• License: MIT

Install and usage instructions live in the source repository linked above.