Intermediate interview questions in Monitoring & SRE
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.
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.
Diagnosing a healthy p50 but breaching p99
One percent of requests are slow, hurting power users and fan-out calls; investigate GC, locks, contention, cold caches, retries.
Defining SLOs for a new critical service
Start from user journeys, pick SLIs, involve product, engineering, and business stakeholders, set realistic targets iteratively.
Handling planned maintenance in SLOs and error budgets
Either charge maintenance to the error budget or formally exclude it via a maintenance window; each trades honesty against fairness.
OpenTelemetry API, SDK, and Collector
API defines vendor-neutral instrumentation, SDK implements and exports it, Collector receives, processes, and routes telemetry to backends.
Trace context and propagation across services
Trace context bundles trace ID, span ID, and flags; propagated via headers like W3C traceparent so each service extracts and continues the trace.
Redesigning a high-cardinality request metric
Cardinality is unique label combinations; user_id and raw path are unbounded; redesign by dropping user_id and templating the path.
High cardinality in time-series databases
Each combination is a separate series consuming memory and index; manage by avoiding unbounded labels and bucketing values.
Prometheus histogram versus summary
Histograms expose bucket counts and let you compute aggregatable quantiles at query time; summaries compute fixed quantiles per instance that cannot be combined.
Correlating logs, metrics, and traces
Propagate a trace and span ID through context, stamp it on logs and metric exemplars, then pivot metric to trace to logs.
Designing a cache health dashboard
Hit ratio, latency, memory and evictions, connections and saturation, with stat panels for current state and time-series for trends.
Fixing a noisy non-actionable alert
Review the data to see if it is ever actionable, then tune threshold or duration, re-target at user-facing symptoms, or delete it.
SLO-based alerting and error budgets
Define SLI/SLO, derive an error budget, alert on how fast you burn it using multi-window multi-burn-rate rules so fast burns page and slow burns ticket.
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