Workload fit
Separate request coordination from CPU-intensive or long-running work.
Server application engineering
Node.js Backend Engineering.
Node.js is effective for I/O-heavy product services when concurrency, resource limits, failure handling, and operational visibility are designed explicitly.
How we use it
We use Node.js for application services that coordinate databases, APIs, events, files, and user-facing workflows. CPU-heavy computation is isolated or delegated instead of being allowed to block request handling.
Architecture decisions
The questions that shape the implementation
Concurrency
Protect dependencies with timeouts, limits, queues, and backpressure.
Failure semantics
Define retries, idempotency, dead letters, and compensation before integrations fail in production.
Service boundaries
Keep a modular application until independent deployment solves a demonstrated problem.
Engineering practice
What disciplined use looks like
Validated request boundaries
Structured errors and logs
Graceful shutdown
Idempotent background processing
Connection and concurrency limits
Health, latency, and dependency monitoring
Failure modes
What we actively design against
Blocking the event loop
Unbounded parallel work
Retries that duplicate side effects
Premature microservices
Module-level clients that fail during builds
Appropriate use cases
Business APIs
Integration services
Background processing
Webhook consumers
Notification systems
Real-time collaboration gateways
Technical questions
Is Node.js suitable for enterprise software?
Yes, when workload characteristics, architecture, security, testing, observability, and operational ownership are appropriate.
Should every Node.js application use microservices?
No. Independent services add deployment and data complexity. We introduce them only when ownership, scaling, isolation, or release needs justify the cost.
Related expertise