We design and build APIs, queues, workers and data layers together, sized for your real traffic. We also work inside codebases someone else started.
Talk to an engineer, not a salesperson.
BE-01Edge → API → Cache / Queue → Workers → Database
IllustrationThe problem
Slow pages, failed payments and lost orders usually trace back to a few backend decisions made early.
Most systems don't fall over at the layer people expect. Connection pools run out long before the CPU is busy. A cache without stampede control amplifies the spike it was meant to absorb. A queue nobody monitors turns an outage into silent data loss. These are architecture problems, and they cost least to fix before launch.
What we build
At real traffic these are one design decision, not five.
Typed, versioned service boundaries with validation, authentication and rate limiting at the edge. Callers get a stable contract while the system underneath keeps changing.
Slow work moves off the request path into workers, with backpressure and a retry policy. Consumers are idempotent, and a dead-letter queue is one someone actually watches.
Schema, indexes, replicas and partitioning chosen from measured access patterns. Cache keys, expiry and invalidation on write are designed alongside the read path.
Typical first fixes: a pooler in front of PostgreSQL, a shared Redis cache with stampede protection, and indexes checked against real query plans.
Traces, metrics and structured logs that let you diagnose an incident without redeploying. Alerts on error rate and latency, not only on crashes.
Production-shaped load against production-shaped data, before anyone makes a capacity claim.
Evidence
Two clients' reviews, verbatim. Client names withheld.
“Excellent freelancer to work with. The implementation was handled professionally, communication was clear, and the work followed the requested MVP scope properly. The freelancer understood the existing setup quickly…”
“Excellent developer. Anupam delivered a complex production integration with strong attention to architecture, safety, testing, and rollback procedures. He followed the scope carefully, communicated clearly, and provided a reusable solution…”
The internet-facing API holds no signing keys. An isolated worker signs withdrawals. Deposits are re-verified on-chain before credit. Seven withdrawal controls, and token rotation with reuse detection.
Read the buildRatings, reviews and engagement dates come from client contracts delivered through Upwork, checked 24 Sep 2026. '…' marks where a quote was shortened. Client names stay private.
Existing systems
A lot of backend work is adding to a system someone else started. We read before we write: map the existing setup, agree the smallest change that meets the goal, and ship it with a way back.
Rescue
Unstable, slow, or left half-finished by a previous developer. Tell us what's broken. An engineer reviews it and suggests where to start.
Process
Four steps. You get something you can read at the end of each.
We measure or model your real access pattern and read the existing code.
You get
A written brief with the risks we found.
API, cache, queue and data layer designed together.
You get
An architecture doc, the key decisions (ADRs) and a milestone plan with estimates.
Instrumented from the first commit, in reviewable increments.
You get
Regular demos and written updates.
A load test against production-shaped data.
You get
UAT sign-off and handover notes.
Pricing
An architecture review or discovery sprint at a fixed fee, then fixed-price milestones. Ongoing work can run on a dedicated engineer by the month, and small fixes can be hourly.
How much existing code there is to learn, the number of integrations, your traffic and data volume, and how much load testing the launch needs.
Start here
Find where your backend breaks first as traffic grows.
7 indicators. See what to fix first.
Free. Results on screen; no email needed.
Questions
We can tell you where the pressure points are and what will break first. Anyone who guarantees a number without load testing your system against your data is guessing. Start with the scale planner, then a technical review.
When the team and the deployment story justify them. A modular monolith is the right answer more often than it is fashionable, and premature service boundaries are expensive to undo.
Yes. Architecture review, targeted engineering or full ownership of a subsystem are all normal ways to work together.
Mostly Node.js (NestJS or Express) with PostgreSQL, MongoDB or Redis, depending on the workload. If your stack is different, we'll say on the first call whether we're the right fit for it.
Three ways to start
Pick whichever suits you. A person reads every message.
Kolkata, India · GMT plus 5 hours 30