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build-parallelism

build-parallelism

github.com/dotnetDevelopment5.8k3.6k installsUpdated 1d ago
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About build-parallelism

A build-diagnostics skill for .NET developers that uses binlogs to identify critical paths and serial dependencies, then suggests targeted MSBuild parallelism improvements.

Key features

  1. 01Check build nodes and project timings
  2. 02Analyze critical paths and dependency chains
  3. 03Find unnecessary project references
  4. 04Analyze build timings with binlog MCP
  5. 05Suggest graph builds and CI parallelism

Use cases

  1. 01Investigate slow builds on multicore machines
  2. 02Identify dependencies that serialize builds
  3. 03Use binlogs to find slow projects and targets

MCP support

Guides use of the binlog MCP tools from Microsoft.AITools.BinlogMcp to inspect project, target, and parallel build timings.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/dotnet/skills --skill build-parallelism

After installing, type/build-parallelismin Claude Code to confirm it loaded.

Details

From the project README

Diagnose a slow parallel build (start here)

Work this checklist in order — it targets the usual root cause (a serial dependency chain that no number of cores can parallelize):

  1. Check how many worker nodes actually built the solution. Capture a binlog with dotnet build /bl:{} (PowerShell: dotnet build '-bl:{}') and inspect the node timeline to see whether more than one node ran. Every dotnet CLI command built on the SDK's MSBuild-forwarding path (build, msbuild, test, pack, publish, etc.) enables /maxcpucount (multiple nodes) by default; -m:1 forces a single node. A direct MSBuild.exe invocation is sequential by default, so pass -m explicitly to enable parallel worker nodes there.
  2. Find the critical path. From the binlog, read per-project timings and the node timeline. If total build time ≈ the sum of the projects on one dependency chain, that chain — not CPU count — is the bottleneck.
  3. Name the chain explicitly, e.g. Core → Api → Web → Tests. A long serial chain stays serial no matter how large -m is, because each project waits on its predecessor.
  4. Look for unnecessary ProjectReference edges that lengthen the chain — a reference that only needs build order (not the output assembly), or one that could be a PackageReference, forces serialization it doesn't need.
  5. Recommend flattening: break false dependencies so independent projects build concurrently, and consider /graph for better scheduling.

MSBuild Parallelism Model

  • /maxcpucount (or -m): number of worker nodes (processes)
  • Every dotnet CLI command (build, msbuild, test, pack, publish, etc.) passes /maxcpucount by default via the SDK's shared MSBuild-forwarding path; -m:1 overrides it with one node
  • A direct MSBuild.exe invocation is sequential by default and requires an explicit -m
  • Recommended: -m without a number = use all logical processors
  • Each node builds one project at a time
  • Projects are scheduled based on dependency graph

Project Dependency Graph

  • MSBuild builds projects in dependency order (topological sort)
  • Critical path: longest chain of dependent projects determines minimum build time
  • Bottleneck: if project A depends on B, C, D and B takes 60s while C and D take 5s, B is the bottleneck
  • Diagnosis: replay binlog to diagnostic log with performancesummary and check Project Performance Summary — shows per-project time; grep for node.*assigned to check scheduling
  • Wide graphs (many independent projects) parallelize well; deep graphs (long chains) don't

Graph Build Mode (/graph)

  • dotnet build /graph or msbuild /graph
  • What it changes: MSBuild constructs the full project dependency graph BEFORE building
  • Benefits: better scheduling, avoids redundant evaluations, enables isolated builds
  • Limitations: all projects must use <ProjectReference> (no programmatic MSBuild task references)
  • When to use: large solutions with many projects, CI builds
  • When NOT to use: projects that dynamically discover references at build time

Optimizing Project References

  • Reduce a <ProjectReference> only after proving it is unnecessary; a slow but valid dependency must stay in the graph
  • Use <ProjectReference ... SkipGetTargetFrameworkProperties="true"> to avoid extra evaluations
  • <ProjectReference ... ReferenceOutputAssembly="false"> for build-order-only dependencies
  • Consider if a ProjectReference should be a PackageReference instead (pre-built NuGet)
  • Use solution filters (.slnf) to build subsets of the solution

BuildInParallel

  • <MSBuild Projects="@(ProjectsToBuild)" BuildInParallel="true" /> in custom targets
  • Without BuildInParallel="true", MSBuild task batches projects sequentially
  • Ensure /maxcpucount > 1 for this to have effect

Multi-threaded MSBuild Tasks

  • Individual tasks can run multi-threaded within a single project build
  • Tasks implementing IMultiThreadableTask can run on multiple threads
  • Tasks must declare thread-safety via [MSBuildMultiThreadableTask]

Analyzing Parallelism with Binlog

Primary: binlog MCP (preferred)

Use the binlog MCP server (Microsoft.AITools.BinlogMcp, exposed under the binlog MCP namespace):

  1. Use expensive_projects tool → find the slowest projects and compare individual vs total build time
  2. Use expensive_targets tool → find bottleneck targets
  3. Use project_target_times tool → drill into a specific project's target-level timing
  4. Ideal: build time should be much less than sum of project times (parallelism)
  5. If build time ≈ sum of project times: too many serial dependencies, or one slow project blocking others
Fallback: text-log replay (when MCP is unavailable)

Step-by-step:

  1. Replay the binlog: dotnet msbuild build.binlog -noconlog -fl "-flp:v=diag;logfile=full.log;performancesummary"
  2. Check Project Performance Summary at the end of full.log
  3. Ideal: build time should be much less than sum of project times (parallelism)
  4. If build time ≈ sum of project times: too many serial dependencies, or one slow project blocking others
  5. grep 'Target Performance Summary' -A 30 full.log → find the bottleneck targets
  6. Consider splitting large projects or optimizing the critical path

CI/CD Parallelism Tips

  • Use -m in CI (many CI runners have multiple cores)
  • Consider splitting solution into build stages for extreme parallelism
  • Use build caching (NuGet lock files, deterministic builds) to avoid rebuilding unchanged projects
  • dotnet build /graph works well with structured CI pipelines

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