Interview questions in Monitoring & SRE
What defines toil, with an example?
Define toil as manual, repetitive, automatable, tactical, no-enduring-value, scaling-with-growth work; distinguish it from overhead; give a concrete example.
SLI vs SLO vs SLA: how do they relate?
SLI is a measured metric, SLO is the internal target for that metric, SLA is the external contract with consequences.
How do SRE and DevOps relate?
DevOps is a broad culture of breaking down silos; SRE is one prescriptive way to do it with specific practices.
How do you set SLOs for a service from scratch?
Identify critical user journeys, pick SLIs that reflect user happiness, measure current performance, set achievable targets with buffer, iterate.
Error budget exhausted early: what now?
Invoke the error budget policy, shift focus from features to reliability, prioritize stability work, analyze what burned the budget.
How do you find and eliminate toil systematically?
Inventory and measure toil via time tracking or ticket analysis, prioritize by frequency times cost versus automation effort, automate highest-ROI items, measure success…
What makes a blameless postmortem effective?
Cover summary, impact, timeline, root cause, action items; explain blameless means focusing on systemic causes so people report honestly.
Risky launch with a near-empty error budget?
Contain blast radius via canary and feature flags, use progressive rollout tied to budget burn, negotiate explicit risk acceptance, add fast rollback.
SRE vs traditional ops on a recurring alert?
Traditional ops repeatedly handles the alert manually and scales by adding people; SRE treats it as a bug, automates or eliminates the root cause, and scales sublinearly.
Error budget policy across dependent microservices?
Set per-service SLOs but anchor on user-facing journey SLOs, budget for dependency error via the multiplication of availabilities, attribute downstream-caused failures correctly, and use…
Explain the three pillars of observability
Metrics are cheap aggregated time series for detecting and alerting, logs are discrete event records for detail and context, traces follow one request across services to localize latency.
What are the Four Golden Signals?
Name latency, traffic, errors, and saturation; explain each briefly; describe measuring latency as a distribution separating success from failure.
Why use latency percentiles over the average?
Averages hide the tail and are skewed by outliers, so most users can suffer while the mean looks fine; use percentiles; prioritize p99 when tail users are high-value or fan-out…
Structured vs unstructured logging: why it matters
Unstructured logs are free-text lines hard to parse; structured logs are machine-readable key-value or JSON records; structure enables reliable querying…
How does distributed tracing work?
Trace ID ties one request together, span IDs are individual operations, context propagates via headers.
Black-box vs white-box monitoring for legacy apps
Black-box probes from outside, white-box reads internal state; start black-box for fast user-facing signal.
What is high-cardinality data in Prometheus?
Cardinality is the count of unique label combinations; each is a separate series; explosion blows up memory and query cost.
Head-based vs tail-based trace sampling
Head-based decides at trace start cheaply but blindly; tail-based waits for the full trace to keep errors and slow requests.
Symptom-based vs cause-based alerting
Symptom alerts fire on user-visible impact, cause alerts on internal conditions; page on symptoms to cut noise and catch unforeseen failures.
Relationship between SLI, SLO, and SLA
SLI is the measured metric, SLO is the internal target for that metric, SLA is the external contract with consequences.
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