Capacity Planning & Scaling Flashcards
7 cards from real SRE practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Capacity Planning & Scaling flashcards as text
Which of the following best describes 'elastic scaling'?
Answer: Automatically provisioning and deprovisioning resources in response to real-time demand
Elastic scaling automatically adjusts resource capacity up or down based on current demand, optimizing both performance and cost.
An SRE is capacity planning for a batch processing system that runs nightly. What is the most cost-effective cloud strategy?
Answer: Use spot/preemptible instances that scale up at night and terminate after completion
Spot or preemptible instances at scale for short-duration batch jobs significantly reduce cost since the workload is fault-tolerant and time-flexible.
What is the purpose of a 'capacity model' in SRE practice?
Answer: Mapping resource consumption to traffic levels to forecast infrastructure needs
A capacity model quantifies the relationship between traffic/usage and resource consumption, enabling accurate infrastructure forecasting as load grows.
When horizontal scaling is applied to a stateless web tier, what happens to the system's theoretical maximum throughput?
Answer: It scales linearly with the number of instances (assuming no shared bottleneck)
Stateless services with no shared state bottleneck scale nearly linearly horizontally because each instance independently handles requests.
A service regularly hits its connection pool limit during peak traffic. Which capacity action directly addresses this bottleneck?
Answer: Increase the database connection pool size or add a connection pooler like PgBouncer
A connection pool limit is a concurrency bottleneck; increasing pool size or adding a connection pooler like PgBouncer multiplexes connections efficiently.
What does Amdahl's Law imply for SRE capacity planning when scaling parallel systems?
Answer: The speedup from parallelization is limited by the sequential (non-parallelizable) fraction of the workload
Amdahl's Law states that sequential portions of a workload cap the maximum speedup achievable through parallelization, setting an upper bound on scaling benefits.
Which SRE practice helps validate that a new capacity plan will actually meet SLOs before rolling it out to production?
Answer: Load testing the new capacity configuration in a staging environment that mirrors production
Load testing in a production-mirror staging environment validates the capacity plan against realistic conditions without risking production availability.