Top 7 Slo Interview Questions
Browse 7 real-world technical and behavioral interview questions about Slo. Review scenarios, edge cases, and architectural best practices.
You are asked to cut cloud spend by thirty percent without hurting reliability. Walk me through the case you would bring.
Agree whether thirty percent means run-rate or this year's cloud spend, absolute or per unit. Then attribute the bill, phase the cuts as quick wins, structural fixes and commitments last, and guard every change with SLO burn and a protected list. Show both the run-rate and the in-year figure.
Reliability work keeps losing to features in planning. How do you change that across the whole organisation?
Stop making reliability compete item by item. Agree SLOs and an error budget policy with product leadership in advance, hold a measured capacity floor for operational work, price incidents in business terms, and require a named executive to sign any decision to overspend the budget.
Your error budget burn alert pages every few hours, but half the time nobody outside the team has noticed anything. How do you tune it without simply making it quieter?
A single threshold on a single window cannot separate a real outage from a brief spike, so it either pages on noise or misses slow burns. Replace it with multi-window multi-burn-rate alerting: a fast rule that pages and a slow rule that files a ticket, each gated by a short window so a spike that already stopped does not keep paging.
The business says the system must be highly available. How do you turn that into a number, and what does that number cost?
Convert the phrase into an error budget over a stated window, derived from what an outage costs the business rather than from a round number of nines. Each additional nine roughly multiplies cost, because it forces redundancy, cross-region failover and operational maturity that the previous nine did not need.
How would you set an SLO for a service, and what is an error budget for?
An SLO defines the reliability users should experience, and the error budget is the allowed gap between that target and perfection. Use burn rate to decide when reliability work must outrank feature delivery.
A stakeholder tells you the system must be scalable. How do you turn that into a requirement you can design and test against?
Rewrite it as a quality-attribute scenario: a named stimulus arriving at a stated rate, hitting a stated system state, with a response measured at a percentile over a defined window. A number with a load figure, a duration and a named sacrifice is designable and testable; a list of maxima is not.
You promise 99.9 percent availability and you call five services that each promise the same. What have you committed to?
Nines only mean something as a downtime budget over a stated window, and dependencies in series multiply: five hard dependencies at three nines each put your own ceiling near 99.4 percent, so the target is met by removing dependencies from the critical path rather than by asking each owner for more nines.