Scale / Scalable backend & real-time systems
High-throughput backend and real-time systems engineered from production evidence
We engineer the paths that become expensive or fragile under real demand: WebSocket fan-out, streaming transfers, event processing, shared state, caching, databases and inter-service communication.
Intended outcomes
What this engagement is designed to achieve.
- A capacity model tied to real traffic and business-critical paths
- Predictable latency, throughput and resource use
- Explicit ordering, idempotency and backpressure
- Failure modes that can be observed, contained and recovered
Engineering capabilities
Capabilities applied where the system needs them.
We select technology based on the product, team and operating constraints. The list reflects established areas of delivery, not a mandatory stack.
- Go & Node.js
- REST, gRPC & GraphQL
- WebSocket, SSE & HTTP/2
- Kafka & RabbitMQ
- Redis & caching
- Concurrency & backpressure
- Load testing
- Performance profiling
When to bring us in
When this service is a good fit.
- Traffic growth is exposing backend bottlenecks
- A real-time or streaming feature needs production architecture
- Service boundaries and messaging have become unreliable
- Cloud cost is growing faster than useful throughput
What you receive
Concrete deliverables and a clear path forward.
- Performance profiling and capacity analysis
- Backend and distributed-systems architecture
- Real-time, streaming and messaging implementation
- Database, caching and concurrency optimization
- Load, failure and recovery testing
Questions
Common questions.
Do we need microservices?+
Not automatically. We introduce boundaries only when they improve ownership, scaling, fault isolation or delivery—not because a distributed design looks more advanced.
Can you optimize an existing backend?+
Yes. We work from profiles, query plans, traces, traffic shape and load tests before choosing a rewrite or a technology change.
Direct access to the delivery team