Cloud Monitoring Tools

Closest to 'silent in production until users hit it' (d9). The detection_hints explicitly state automated=no, and the pattern described — only infrastructure metrics with no application metrics, no APM tracing, errors only visible in CloudWatch logs — means gaps in monitoring coverage are invisible until users actually experience problems. No tool automatically flags that you're missing application-level instrumentation.

Closest to 'touches multiple files / significant refactor in one component' (e5). The quick_fix says you need both CloudWatch and Sentry, implying adding structured error tracking, log metric filters, SNS alarms, and log retention policies. This touches infrastructure config, application code instrumentation, and alerting configuration across multiple concerns — more than a one-line patch but not a full architectural rework.

Closest to 'strong gravitational pull' (b7). Monitoring choices apply_to web and cli contexts broadly. A poorly chosen or misconfigured monitoring stack shapes every operational decision — incident response, alerting thresholds, debugging workflows, and SLO definitions all depend on it. The why_it_matters field confirms blind spots and alert fatigue ripple across all ongoing work, making this a load-bearing choice.

Closest to 'serious trap (contradicts how a similar concept works elsewhere)' (t7). The misconception field directly states that developers wrongly believe CloudWatch replaces application monitoring and auto-collects request latency, error rates, and business metrics. This contradicts the behaviour of APM tools like Datadog or New Relic which do provide this automatically, so a developer familiar with those tools will assume CloudWatch does the same — a serious and documented trap.