Capacity Modelling
Arithmetic before load tests, and headroom for failure as well as peak.
6 to work through
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intermediate Multiple choice
Alibaba reported a peak of 583,000 order creations per second during Singles' Day in 2020. Suppose one promoted item accounts for 0.5% of those orders and its stock is held in a single row. Roughly how many updates per second does that row have to absorb?
2 min answer -
intermediate Multiple choice
You run in three availability zones and must survive losing one. What is your maximum normal utilisation and why?
2 min answer -
intermediate Multiple choice
Zoom's CEO wrote on 1 April 2020 that maximum daily meeting participants went from roughly 10 million at the end of December 2019 to more than 200 million in March 2020. For any platform absorbing a 20× demand rise over three months rather than three minutes, which capacity decision does the slower surge force that the fast one does not?
3 min answer -
advanced
A compute platform must plan accelerator capacity where lead times are months, demand is uncertain, and jobs vary from minutes to weeks. How should the capacity model be built?
2 min answer -
advanced
A game hosts a scheduled in-world event for 30 million concurrent players. How should matchmaking, instance allocation, pre-scaling, login queues and degradation be planned, and what is rehearsed?
3 min answer -
advanced
A training cluster has 512 NVIDIA H100-class GPUs in 64 eight-GPU nodes and the scheduler reports 96 GPUs free. Roughly how much collective bandwidth per GPU does a new 64-GPU job get, and what should the capacity report say instead of "96 GPUs free"?
3 min answer
3 terms in this topic
Capacity Lead Time
The delay between deciding capacity is needed and having it available, which determines whether a capacity model can forecast at all or must instead …
practiceCapacity Modelling
Predicting the resources a workload will need, from measured unit costs and a demand forecast, with deliberate headroom.
practiceDemand Forecasting
Projecting future load from historical trends, business plans and known events, and translating it into resource requirements with explicit lead times.
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.
Horizontal vs Vertical Scaling
Scale out for stateless, scale up first for stateful.
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.