Question 1

Should I start with a monolith or microservices?

Accepted Answer

For most products, a well-structured modular monolith is the right starting point. Microservices add real operational overhead — service discovery, distributed tracing, network failure handling — that only pays off once you have multiple teams or genuinely independent scaling needs. We build monoliths with clean module boundaries so they can be split into services later if and when that's actually warranted.

Question 2

Node.js, Python, or Go — which backend language?

Accepted Answer

Node.js excels at I/O-heavy APIs and shares language with your frontend. Python (FastAPI, Django) is unbeatable for data, ML integration, and rapid development. Go shines for high-throughput, low-latency services where you want compiled performance and easy concurrency. We pick per workload, and a single system can mix them — Go for a hot path, Python for an analytics service.

Question 3

How do you make the backend scale?

Accepted Answer

Scaling starts with stateless services so you can run many copies behind a load balancer, plus a database that won't become the bottleneck. We add caching (Redis), read replicas, connection pooling, and async processing via queues so slow work doesn't block requests. Horizontal scaling beats buying a bigger server, and we design for it from the start.

Question 4

How long does a backend project take?

Accepted Answer

A focused API with auth, a handful of resources, and a database typically takes 4–8 weeks. A complex system with microservices, real-time features, multiple integrations, and high-availability requirements runs several months. The biggest variables are the number of integrations, data-migration complexity, and how strict your uptime and compliance requirements are.

Question 5

How do you keep APIs fast?

Accepted Answer

We set performance budgets and profile against real queries rather than guessing. The usual wins are proper database indexes, eliminating N+1 query patterns, caching hot reads in Redis, paginating large responses, and moving slow work to background jobs. Sub-100ms responses are realistic for most endpoints once the data layer is tuned.

Question 6

How do you handle database migrations safely?

Accepted Answer

We use versioned, reversible migrations run through the CI pipeline, never manual SQL on production. For schema changes on live systems we favor backward-compatible, multi-step migrations — add the column, backfill, switch reads, then drop the old one — so deploys never require downtime. Backups and a tested rollback plan are in place before any migration runs.

Question 7

What about monitoring and reliability?

Accepted Answer

We instrument services with structured logging, metrics (latency, error rate, throughput), and distributed tracing so you can pinpoint a slow request across services. Health checks, alerting on real symptoms, and graceful degradation mean problems get caught before users complain. Observability isn't optional — it's how you keep a system reliable as it grows.

Question 8

Can you work with our existing backend?

Accepted Answer

Yes. We regularly join existing codebases to add features, optimize performance, or modernize incrementally. We start by reviewing the architecture and adding tests around the area we'll change, so improvements are safe rather than risky rewrites. A full rebuild is sometimes the right call, but we'll only recommend it when the evidence supports it.

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