Intermediate everything in DevOps & Cloud, page 3
Why 'human error' is not a root cause
Human error is a starting symptom; ask why the system allowed it, find missing guardrails.
Conducting a blameless post-mortem in practice
Focus on systems not individuals, assume good intent, use neutral language and facilitation, end with owned action items.
Fast rollback versus targeted fix in an incident
Weigh time-to-recovery and blast radius against rollback side effects; prefer restoring service fast, gated by data like deploy diff and migration risk.
Designing a SEV1-SEV4 severity matrix
Tie levels to user impact, scope, and SLO burn with concrete thresholds; map each to response and escalation.
Designing an escalation policy
Define timeout-based escalation tiers, multiple notification channels, secondary and management layers, coverage across time zones, and severity-based routing.
Anatomy of an effective runbook
Alert meaning and impact, diagnostic steps with dashboard and query links, concrete remediation with rollback, and escalation contacts.
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.
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.
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.
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.
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.
High cardinality in time-series databases
Each combination is a separate series consuming memory and index; manage by avoiding unbounded labels and bucketing values.
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.
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.
OpenTelemetry API, SDK, and Collector
API defines vendor-neutral instrumentation, SDK implements and exports it, Collector receives, processes, and routes telemetry to backends.
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.
Defining SLOs for a new critical service
Start from user journeys, pick SLIs, involve product, engineering, and business stakeholders, set realistic targets iteratively.
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.
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.
How does distributed tracing work?
Trace ID ties one request together, span IDs are individual operations, context propagates via headers.
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