Sciensa

Architecture & Scale

Building for the complexity that comes with growth.

Scale is not only volume. It is what happens to cost, to failure and to the number of teams once the volume arrives.

When growing costs more than growing was worth.

The peak takes everything down, and the peak is predictable

Black Friday and payroll are on the calendar, and they still arrive as a surprise.

Doubling the volume doubled the bill

When cost grows in step with revenue, scaling stops being an advantage.

The database became everyone's bottleneck

Every path goes through the same place, and that place sets the ceiling for the whole system.

One team waits on another to ship

Team scale is scale too, and it jams at the same point the technical one does.

What this discipline decides.

Distributed Systems

Distributing trades one problem for another: the single bottleneck goes, consistency and ordering arrive. Distributing without choosing which trade to make is distributing at random.

Performance

Measuring where time is spent before optimising. Most of the gain usually sits somewhere nobody suspected.

Resilience

Degrading instead of falling over. A resilient system loses function and keeps operating, rather than stopping altogether.

Capacity Planning

Knowing how much the system takes before you need to know, and what each extra step costs.

Observability

Being able to answer a new question about the system's behaviour without shipping a deploy to instrument it.

Growth stops being a risk event.

Peaks absorbed without intervention

The date on the calendar stops requiring someone on call.

Cost that grows slower than volume

The infrastructure curve separates from the transaction curve.

Failure that degrades instead of dropping

One part going down stops meaning the system is down.

Running in production

Apache Kafka
Kubernetes
Apache Spark
Databricks
Go
PostgreSQL

Handling growth is settled before the growth arrives.

Tell us how much you expect to grow and we will show you what needs to change.