3.4b — Capacity Planning & Testing (11)

Capacity planning

Predicting and provisioning the right amount of supply (people, technology, infrastructure) to meet demand, not too little, not too much.

People (capacity consideration)

Staffing is slow to scale: hiring and training takes time; over-staffing means reassignment or layoffs.

Technology (capacity consideration)

Choosing systems that can actually scale up/down, e.g. load-balanced web servers or distributable database tiers.

Infrastructure (capacity consideration)

The physical or cloud buildout needed to support a service: storage, servers, network connectivity.

Rightsizing

Adjusting cloud resource allocation up or down to match actual current demand, avoiding over- or under-provisioning.

Recovery testing

Regular, scoped testing of a disaster recovery plan to confirm the organization can execute it, without impacting production systems.

Tabletop exercise

Walking through the recovery plan verbally with stakeholders, without actually failing anything over. Cheapest test; surfaces planning and coordination gaps.

Failover test

Actually triggering a switch to redundant systems to confirm the failover genuinely works, ideally automatically and invisibly to users.

Simulation (testing)

Testing a specific scenario in a controlled way, e.g. phishing simulation, password reset test, simulated data exfiltration, to see if detection/response works.

Phishing simulation

A simulation testing whether users click malicious links and whether automated systems catch the attempt before it reaches them.

Parallel processing

Multiple CPUs, cores, or machines handling transactions simultaneously; provides both performance and resilience since losing one processor still leaves others working.