Horizontal vs Vertical Scaling
Scale out for stateless, scale up first for stateful.
4 to work through
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intermediate
A service is at capacity. When is vertical scaling the better answer than horizontal, and what is the trap in each direction?
2 min answer -
intermediate Multiple choice
A workspace product's primary database is at its limits. Should it scale vertically, add replicas, or shard? What order and what evidence?
2 min answer -
intermediate
When is vertical scaling the better answer, and what makes horizontal inevitable eventually?
2 min answer -
advanced
A stateful service runs on 16 large nodes, each holding a large in-memory working set. You must move to 200 small nodes under live traffic, for finer failure granularity and better bin-packing. Sequence the migration, and say what changes that nobody plans for.
3 min answer
2 terms in this topic
Scale Cube
A model describing three independent axes of scaling — cloning, functional decomposition, and data partitioning — each addressing a different limit.
conceptUniversal Scalability Law
A model showing that throughput rises with concurrency, flattens due to contention, and then falls due to coherency costs.
Neighbouring topics
Performance & Capacity
General material on performance and capacity engineering.
Latency
Distributions rather than averages, and the floors physics imposes.
Throughput
Work completed per unit time, and why it trades against latency.
Concurrency
Operations in flight, and the limits that are the real capacity ceiling.
Queueing Theory
Why latency explodes as utilisation approaches capacity.
Little's Law
L = λW, and the pool sizes it computes directly.
Bottleneck Analysis
Finding the constraint, and expecting a second one behind it.
Tail Latency
p99 behaviour, amplification across fan-out, and hedged requests.
Load Testing
Realistic data, realistic mix, and a ramp rather than a step.
Stress Testing
Pushing past target to learn what breaks first and how it fails.
Soak Testing
Long runs that surface leaks and slow degradation.
Capacity Modelling
Arithmetic before load tests, and headroom for failure as well as peak.
Caching for Performance
Layer choice, hit ratio as a first-class metric, and cold-cache recovery.
Database Performance
Plans, indexes, contention and the pool in front of the database.
Connection Pooling
The most common hidden ceiling, and the metric nobody collects.
Network Performance Tuning
Keep-alive, compression, payload size and round-trip elimination.
Performance Budgets
Targets enforced in CI so regressions fail the build.
Profiling & Optimisation
Measuring before optimising, and optimising the dominant term.
Peak Event Readiness
Freeze, pre-scale, shed order, warm caches and rehearse.