Cloud Native Observability GCSA Practice Questions (Page 3)

Questions 11–15

1. 11application · medium

   An organization runs services in multiple cloud environments and on-premises. Each team currently uses a different vendor SDK to emit traces and metrics, making it difficult to aggregate data in a single observability platform. The platform team wants to standardize telemetry generation across all services without forcing every team to rewrite their application logic. Which approach should they take?

   • AWrite a custom internal library that wraps each vendor SDK and exposes a unified interface to application teams.
   • BDeploy a sidecar proxy in each pod that converts all application logs into metrics and traces.
   • CRequire each team to continue using their current vendor SDK but configure the observability platform to accept all formats.
   • DAdopt OpenTelemetry as the standard instrumentation layer, using its SDKs and exporters to send data to the existing platform.
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2. 12expert · hard · select all that apply

   A team is designing observability for a new microservices application. They want to follow best practices for structured logging, distributed tracing, and meaningful metrics. Which of the following practices should they adopt? (Select all that apply.)

   • AUse a single global metric for all services to simplify dashboards.
   • BUse consistent key-value pairs in structured logs across all services.
   • CLog all sensitive data in plain text to ensure full visibility.
   • DInstrument every service with distributed tracing and propagate trace context.
   • EDefine metrics that reflect user-facing SLIs, such as request latency and error rate.
   • FInclude a unique request ID in every log entry and propagate it across service calls.
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4. 13foundation · easy

   What is the purpose of instrumenting an application in a cloud native environment?

   • ATo generate telemetry data such as metrics, logs, and traces that can be used for observability.
   • BTo reduce the application's memory footprint.
   • CTo automatically fix bugs in the application code.
   • DTo encrypt all data transmitted between microservices.
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5. 14application · medium

   A team is troubleshooting a slow API endpoint. They have metrics showing the 95th percentile latency is high, but they cannot tell which downstream service is causing the delay. Which telemetry type should they add to identify the bottleneck?

   • AMore detailed metrics for each service's CPU usage.
   • BStructured logs that record the request path.
   • CA new dashboard that aggregates all service metrics.
   • DDistributed traces that show the time spent in each service call.
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6. 15expert · hard

   An organization is moving from a monolithic application to a microservices architecture. The current monitoring system is based on static thresholds and predefined dashboards. The SRE team wants to implement a more observability-driven approach. They have a limited budget and need to justify the investment. Which argument best justifies the shift to cloud native observability?

   • AObservability eliminates the need for monitoring, so the team can reduce costs by removing all dashboards and alerts.
   • BObservability guarantees that all incidents will be automatically resolved without human intervention.
   • CObservability enables the team to debug unknown failure modes by exploring telemetry data, reducing MTTR for incidents that monitoring cannot predict.
   • DObservability is required by all cloud providers, so the organization must adopt it to remain compliant.
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