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Observability & Monitoring in Cloud
Seeing inside production systems with metrics, logs, traces, and alerts
Assessment Details
Total Questions
10
Question Type
Mixed Format
Difficulty
Medium
Topics Covered
three-pillarsobservabilityfundamentalsmonitoring-vs-observabilitygolden-signalssreservice-healthstructured-loggingjson-logsbest-practicessliservice-levelmeasurementsloslaerror-budgetreliability-velocityprometheusmetricspull-modelmetric-typescounter-gauge-histogramgrafanavisualizationdashboardsdistributed-tracingtracesspansopentelemetryotelinstrumentationelkelasticsearchlogstashkibanacloudwatchawsmonitoringtrace-propagationw3c-trace-contextjaegertracing-backendcncfred-methodmonitoring-methodologyservice-metricsalert-fatiguealertingon-callpush-pullmetrics-collectionlokilog-aggregationtracinguse-methodresource-monitoringperformancepostmortemblamelessincident-responsepromqlqueryingcardinalityscalingotel-collectortelemetry-pipelinetail-samplingcost-optimizationslo-alertingburn-ratefluentdlog-collectionseverity-levelsincident-classificationresponsexrayaws-tracingmanaged-tracingpercentileslatencyrotationsustainabilityexemplarscorrelationmetrics-tracesrunbookdocumentationcentralized-loggingarchitecturealertmanageralert-routingauto-instrumentationsynthetic-monitoringrumuser-experiencelog-alertingmetric-alertingcomparisonfederationmulti-clusterincident-commandercoordinationthanosprometheus-scalinglong-term-storageservice-mapdependenciesarchitecture-visibilitycorrelation-idrequest-idcross-service-debugginganomaly-detectionml-monitoringwhiteboxblackboxmonitoring-approachesrecording-rulesoptimizationcontractsproduction
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