Atlassian Observability, SLOs & Reliability interview questions

Metrics quantify impact, traces expose instrumented request paths, and logs describe individual events. Follow a slow checkout across all three while accounting for missing evidence.

Metrics describe the server's experience; synthetics describe the user's. The strong answer designs a few money-path journeys from real geographies, pages only on persistent failure, and budgets for script rot.

Routing rots because orgs change faster than configs. The senior answer treats ownership as data resolved from a catalog at fire time, with drift detection on the routing itself.

Usable runbooks live one click from the alert, front-load symptom-to-action pairs, and stay alive because CI and drills force the issue rather than anyone hoping.

Rotation length decides focus versus fatigue, handoff quality decides whether Tuesday inherits Monday's mess, and follow-the-sun only works when every region holds real authority.

One surface cannot serve the responder and the review. Tier dashboards by the question each audience asks, and make every tile answer in five seconds or link one click deeper.

Assert on the shape of a trace: which spans ran, in what order, with which attributes. Catches the cross-service regressions unit and contract tests structurally miss, at the price of instrumentation discipline.

Comms is a role, not a chore bolted onto the incident commander. Audience-specific cadences, a committed next-update time in every message, and plain language that support can actually repeat.

You have added a dependency with a latency distribution an order of magnitude wider than anything else in your stack, whose failure mode is a plausible wrong answer rather than an error.

Agent per node, gateway per cluster, and one decision that shapes everything else: tail sampling needs every span of a trace in one place, which is why the topology has a tier that looks redundant until you need it.

There is no status code and no caller waiting, so latency and error rate stop meaning what they meant. The signals that replace them are age, lag and completion, and they answer a question the request-response set never had to ask.

Tracing is the only telemetry that answers where the time went across services. The mechanism is context propagation, and the reason teams fail at it is that one uninstrumented hop breaks the chain.

All three can search logs. What differs is who operates the cluster and how the bill is shaped, and the bill is what kills these projects, not the querying.

The arithmetic takes ten seconds and is the part most often skipped. The stall is the signal: it means error budgets are something you have read about rather than used.

Where linear models break: compounding growth, step functions, peak days and saturation cliffs. Forecast per constrained resource, backtest, subtract lead time to get the real order-by date.

Prometheus asks your service for numbers on a schedule rather than waiting to be told. That one design choice explains service discovery, exporters, staleness and why short-lived jobs are the awkward case.

Defining chaos engineering is easy. Far fewer can say what they would break first, and almost none volunteer the abort condition, which is the thing that makes it a programme rather than an incident.