// services

Three engagements. One inner-loop discipline.

Performance tuning, distributed systems engineering, and CI architecture — usually engaged in combination, because the loops they touch are coupled in your codebase whether you treat them that way or not.

// service · 01

Performance tuning

Hot-path refactors, allocator selection, cache and branch tuning, vectorization, kernel-bypass networking. We work at the level the profiler points to — assembly when the data demands it, language idioms when it doesn't.

perf
eBPF · bcc
VTune
Intel PT
jemalloc · mimalloc
io_uring
AF_XDP

case · payments authz

# before — production p99
→ auth/charge: 184ms p99 · 42 req/s/core
# moves
✓ arena alloc for request lifetime (-37%)
✓ SIMD base64 + ed25519 batched verify
✓ remove serialization round-trip
# after
→ auth/charge: 28ms p99 · 310 req/s/core

// service · 02

Distributed systems engineering

Sharding strategy, consistency model selection, backpressure, retry budgets, idempotency keys, partial-failure design. We design systems that degrade gracefully instead of collapsing loudly.

Raft · Paxos variants
CRDTs
queue topology
load shedding
circuit breaking

case · feed fan-out

# symptom: tail spikes during reshard
$ trace --service feed --p99 --by shard
→ shard 73 · 2.4s · queue saturation
# moves
✓ consistent-hash with bounded loads
✓ request hedging w/ 95th-pct trigger
✓ per-shard token-bucket backpressure
→ p99 4.1s → 380ms · zero shed events / wk

// service · 03

CI & build architecture

Hermetic builds, remote execution, test impact analysis, perf-gated pipelines. The goal: a developer can land a small change in under 10 minutes, with full confidence the system is faster than yesterday.

Bazel · Buck2
BuildBuddy · EngFlow
Nix
test sharding
flake detection

case · monorepo CI

# before
→ PR build: 41m · 18% flake rate
# moves
✓ hermetic Bazel + remote cache (1.2 TB hit)
✓ test impact analysis on rdeps graph
✓ perf-gate step blocks p99 regress > 3%
→ PR build: 6m 12s · flake 0.8% · 0 perf regressions / 90d

// case study · deep dive

Order-matching engine, 6.4× throughput in 11 weeks.

A mid-stage trading firm asked us to triple the throughput of their cash-equities matching engine without sacrificing determinism. The previous attempt — a rewrite in a faster language — had stalled after nine months. We kept the language, replaced four data structures, rewrote the allocator strategy, and rebuilt the CI to gate every PR against a recorded production tape.

diagnosis

95% of tail-latency came from three call sites: order insertion (std::map rebalance), the global allocator under burst load, and a serialization step that copied every order twice.

moves

Intrusive red-black tree, per-thread arena allocator with cache-line padding, zero-copy message layout, TSC-based clock, and a fixed-priority pinning strategy across NUMA nodes.

result

p99 1.4ms → 184µs · throughput 6.4× · deterministic replay preserved · CI now rejects any PR that moves p99 by more than 3% on the recorded tape.

// pipeline shape

CI you can actually trust at 03:00.

The pipeline we standardize on across CI engagements. Each stage is independently cacheable, measurable, and reversible. The perf-gate step is the one most teams don't ship — and the one that prevents the worst incidents.

commit

git push

lint

0.4s

build

12s · cached

test

43s · parallel

perf-gate

p99 ≤ 8ms

stage

canary 5%

prod

blue/green

// PR → prod median 6m 12s · perf-gate rejects regressions > 3% on p99 before canary

// design space

Pick the primitive that matches the workload.

Concurrency choices we evaluate during every distributed systems engagement — measured against a representative slice of your real traffic, not microbenchmarks.

scale ↓ · pattern →	Mutex	RWLock	Lock-free	Sharded	Actor
1 core	100× Baseline single-thread	100× No contention	108× CAS overhead	104× Single shard	96× Mailbox overhead
4 cores	140× Lock convoy	220× Reader-heavy wins	380× Cache-line tuned	340× Hash-partitioned	300× Bounded queues
16 cores	165× Contention cliff	280× Reader fairness drops	1,180× NUMA-aware	990× 16 shards · hot-key risk	920× Backpressure tuned
64 cores	170× Pathological	260× Writer starvation	3,680× Hazard pointers	3,100× 64 shards	2,750× Supervisor trees

// Relative throughput (×baseline). Hover a cell to inspect. Source: internal harness · pinned threads · 99p latency budget held.