Benchmark Laravel Package

Product Decisions This Supports

• Build vs. buy vs. skip for performance tooling: This is a dev-only, MIT-licensed microbenchmark harness. It answers "should we stand up our own benchmarking utility or adopt one?" with a low-cost adopt, freeing engineering time for actual optimization work.
• Implementation A/B decisions: When two candidates exist for the same job — Eloquent vs. query builder, array_map vs. foreach, cache driver X vs. Y, JSON vs. serialized payloads, eager vs. lazy loading — the fluent bench()->compare(foo: ..., bar: ...) API lets an engineer produce a defensible, reproducible comparison (min/max/avg/total, time and memory) in minutes rather than days.
• Performance budgets as a roadmap artifact: toAssert() with toBeAvgTime, toBeTotalTime, toBeMaxMemory thresholds turns "fast enough" from a vibe into a numeric, reviewable spec that can be negotiated with stakeholders and encoded in CI.
• Regression gates in the delivery pipeline: The snapshot/toBeRegressionTime / toBeRegressionMemory feature is the highest-leverage capability here. It converts performance from a periodic audit into a per-PR constraint, which directly supports a roadmap commitment like "no more than N% latency regression per release."
• Prioritization of performance work: Snapshot baselines give you a before/after ledger for hot paths, so you can argue for or against a refactor on measured impact rather than intuition.
• Architecture choices with downstream cost: Deviation measurements (deviations()) provide a cheap noise/volatility signal — useful when deciding whether an optimization is real or measurement variance, which shapes whether a refactor gets scheduled at all.
• Programmatic reporting: toData() returning DTOs means results can feed dashboards, PR comments, or release notes — relevant if you want performance visibility for non-engineers.

When to Consider This Package

Adopt when:

• The stack is PHP 8+/Laravel and you want a --dev-only tool with zero production footprint.
• You need fast, low-ceremony comparisons of two to five code paths inside an existing test suite or artisan-adjacent script.
• You want performance regression enforcement in CI without building snapshotting, tolerance math, and assertion plumbing yourself.
• The team is small and the alternative is "nobody benchmarks anything."
• You value readable console tables for PR screenshots and reviewer communication.
• You are comfortable forking: MIT, small surface area, single maintainer.

Look elsewhere when:

• You need production observability or real traffic profiling — use Laravel Pulse/Telescope, Blackfire, Tideways, Xdebug profiling, or APM.
• You need statistical rigor: confidence intervals, outlier-resistant significance testing, or hypothesis tests. PHPBench is the more mature choice for rigorous, config-driven benchmarking.
• You need load, concurrency, or end-to-end latency testing — k6, JMeter, Locust territory.
• Results must be trusted on shared/noisy CI runners without careful pinning; microbenchmark numbers on cloud CI can be misleading regardless of library.
• Governance requires a single-maintainer dependency to have organizational backing or a secured maintenance commitment.
• You need cross-language or cross-runtime comparison.

Adoption caveats to plan for: 121 stars and zero known dependents is thin social proof; the value is real but the ecosystem signal is weak. Treat the library as a thin, replaceable utility and keep benchmark files isolated so a swap is cheap.

How to Pitch It (Stakeholders)

To executives: It is a free, MIT-licensed developer tool that installs only in development and never ships to production. For roughly an afternoon of setup, we get two things: a fast, standard way for engineers to prove which of two implementations is faster before committing to it, and an automated check that fails a pull request if a code change makes a critical path measurably slower. That converts performance from an occasional fire drill into a routine, low-cost guardrail attached to the work we already do.

To engineering: One dev dependency, a fluent API, and a console table you can paste into a PR. bench()->compare(foo: ..., bar: ...) for ad-hoc comparison; toAssert() for numeric budgets; warmup() and automatic trimming of the top/bottom 10% of iterations (above nine iterations) for cleaner numbers; toBeRegressionTime/Memory with committed .snap baselines to catch regressions in CI. toData() gives DTOs if you want to wire results into reporting. Caveats to state plainly: these are microbenchmarks — they measure the code you give them, not user-perceived latency; CI runner noise can swamp small deltas, so set tolerances generously and re-baseline deliberately; and snapshots must be committed and owned, or the gate becomes a nuisance that people disable.

Risk framing: Single maintainer, modest adoption, but MIT-licensed, dev-only, and small enough that forking is a weekend, not a quarter. The decision is reversible at near-zero cost, which is precisely why it is worth trying before investing in bespoke tooling.