Written audit covering event loop, queries, queues, and memory. Delivered by someone who ran Node at $1B+ unicorn scale.
- Audit
- Architect
- Scale
monthly retainer
Who this is for
You're an engineering manager whose Node.js backend has become the team's biggest liability. Endpoints are slow but nobody has profiled them. Memory climbs until the process restarts. Leadership is asking whether this needs a rewrite. I work through that question with a structured audit, not a gut call.
The pain today
- The team guesses at performance with no profiling baseline.
- Memory usage climbs until the process restarts — and nobody knows why.
- Slow endpoints have been complained about for months but never measured.
- Leadership wants a written answer: scale it or replace it.
The outcome you get
- A written Node.js audit covering event loop, queries, queues, and memory.
- A prioritized fix list with hours-per-item and business-cost framing.
- A clear scale-vs-rewrite recommendation backed by profiling data.
- Optional implementation follow-up if your team wants to move fast.
What the Node.js audit covers
I profile the running system across six areas. Event-loop lag under load, measured with clinic.js doctor and 0x flame graphs. Query performance, using slow-query logs, Prisma metrics, and EXPLAIN plans for your top 20 queries. Queue health, looking at BullMQ retry rates and dead-letter depth. Memory profile, using heapdump analysis and leak detection against representative traffic — most Node.js memory leaks trace back to unbounded caches, forgotten EventEmitter listeners, or closures holding more than they need. Response-time distribution at p50, p95, and p99. Deploy topology, checking node instances, autoscaling rules, and health-check discipline.
Each finding comes with a severity rating, a business-cost frame (cloud spend, engineer hours, uptime risk), and an hours-to-fix estimate. Nothing abstract.
A written Node.js audit covering event loop, queries, queues, and memory.
The bolttech reference: what Node.js at scale actually looks like
At bolttech, a $1B+ unicorn, I led the Payment Service running NestJS and Node.js across 40+ payment provider integrations, maintaining 99.9% platform uptime on live payment traffic. The architecture decisions that matter at that scale — how to split worker processes from API processes, when a queue is necessary vs. when it just adds latency, how to handle provider retries without compounding downstream failures — are the reference I use when I look at your system.
If your Node.js backend is deciding between scaling and rewriting, that production reference is where my recommendation comes from. Not a framework blog post.
40+: Payment providers integrated.
Three fixes that appear in almost every Node.js audit
First: move synchronous CPU work out of the request handler. Crypto operations, large JSON parsing, and file I/O block the event loop. They belong on worker_threads or a job queue.
Second: add a queue for anything slower than 200ms that does not need to return a value inline. Email delivery, webhook dispatch, search indexing, report generation. BullMQ on Redis is the default choice. This one fix typically clears the majority of reported slowness before any algorithmic change happens.
Third: structured logging plus a Sentry-grade error tracker plus basic Prometheus metrics. You cannot fix what you cannot see. I have run into Node.js backends with years of performance complaints that had no observability beyond console.log. Setting that baseline usually surfaces two or three problems the team did not know existed.
These three together account for the bulk of performance problems I find in mid-size Node.js backends.
When a TypeScript migration is the right call
A performance audit occasionally uncovers that the real problem is not throughput — it is code that is impossible to reason about. Pre-TypeScript codebases older than five or six years, where developers are afraid to touch shared modules because nothing is typed and test coverage is thin, carry a different kind of debt.
I give an honest call here. If the codebase would benefit more from TypeScript adoption than from query tuning, I say so with a migration path. If the fix list is mostly observability and a few query rewrites, I say that instead. The deliverable is an honest audit, not a sales pitch for more work.
Pricing and what you receive
The engagement runs on the Fractional CTO Advisory tier at $5,499 per month, pro-rated to one to four weeks of scope. You receive a written audit report, a prioritized fix list with hours-per-item, one 60-minute debrief call with your engineering leadership, and a two-week follow-up window for questions.
If implementation is the next step, the Applications subscription at $4,999 per month covers ongoing delivery. Many teams run the audit first and hand the fix list to an in-house engineer — that works too.
Recent proof
A comparable engagement, delivered and documented.
Unified payment orchestration across Asia and Europe
Delivered the payment orchestration platform at bolttech, a $1B+ unicorn, with 40+ integrations across multiple regions.
Read the case studyKeep reading
Frequently asked questions
The questions prospects ask before they book.
One to four weeks. A mid-size Node.js backend with reasonable test coverage takes two weeks. A larger or untested codebase — or one with no observability tooling at all — takes four. I give a firm timeline at the start based on a short scoping call and a first look at the repository.
Read-only. I need monitoring access, a week of application logs, and one to two days of p95 traffic samples. I do not need write access to production databases. If your team is sensitive about access, a staging environment under representative load works for about 80% of the audit; I flag what cannot be verified without production data.
Rarely. Most Node.js audits I run end with a targeted refactor plan and an observability baseline — not a rewrite. I recommend a rewrite only for pre-TypeScript codebases older than six years, or for systems where the framework has gone out of support and the upgrade path is effectively a rebuild anyway.
Heapdump comparison under load: I take a snapshot before load, run representative traffic, then take a second snapshot. The diff shows what survived garbage collection and should not have. Most leaks trace to unbounded caches, forgotten EventEmitter listeners, or closures in long-lived request handlers. clinic.js heap is the first tool I reach for.
I have run tests with both and have opinions on where each fits. For a production Node.js service in 2026, I do not recommend migrating unless the team has a specific, measured reason — a concrete benchmark gap or a dependency the runtime resolves. Node 22 plus TypeScript is still the pragmatic default for teams optimizing existing backends.
Yes. I use k6 or Artillery to run load tests against your service and a comparable competitor endpoint, with a written comparison in the report. This is most useful when leadership wants an external benchmark rather than an internal profiling number.