Evaluate an Application Design and Implementation Considering Observability 350-901 Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   Which pillar of observability is best suited for understanding the path of a single request as it flows through multiple services?

   • ATraces
   • BMetrics
   • CAlerts
   • DLogs
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2. 17foundation · easy

   Which statement correctly describes the three pillars of observability?

   • AThe three pillars are data collection, data storage, and data visualization, which form the observability pipeline.
   • BLogs, metrics, and traces are three distinct data types that together provide insight into system behavior.
   • CThe three pillars are logging, monitoring, and alerting, which are used to manage system operations.
   • DThe three pillars are infrastructure, application, and network telemetry, which cover all system layers.
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4. 18application · medium

   A team is developing a new service. They want to ensure that logs are easy to search and filter, and that they can correlate logs with traces. Which logging approach should they adopt?

   • ALog only errors and warnings to reduce noise.
   • BUse plain text logs with a consistent format.
   • CWrite logs to a local file and rely on the platform to collect them.
   • DUse structured logging with key-value pairs and include a trace ID in each log entry.
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5. 19foundation · easy

   Which metric type is best suited for tracking the number of active user sessions at a given moment?

   • ASummary
   • BGauge
   • CCounter
   • DHistogram
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6. 20expert · hard

   A large e-commerce platform experiences intermittent checkout failures. The team has logs, metrics, and traces. They notice that the error rate spikes, but only for a subset of users. They also see that the checkout service's trace shows a long pause before a call to the payment service. The logs from the payment service show a timeout error. Which approach best helps them correlate these signals to find the root cause?

   • AUse the correlation ID from the trace to filter logs from all services for that specific request, and compare the trace timeline with the log timestamps.
   • BLook at the overall error rate metric and the average trace duration to see if they correlate.
   • CCheck the payment service logs for all errors and assume they are all related to the same issue.
   • DIncrease the log level to DEBUG in all services and reproduce the issue.
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