Evaluate an Application Design and Implementation Considering Observability 350-901 Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   What is the primary purpose of an alerting rule?

   • ATo notify operators when a condition is met
   • BTo automatically fix issues in the application
   • CTo visualize metrics in dashboards
   • DTo store telemetry data for long-term analysis
   Reveal Solution Discussion Select an answer first
2. 2application · medium

   A company runs a microservices-based e-commerce platform. Users report that checkout is slow. The team wants to identify which service in the checkout flow is causing the delay. They already have centralized logging and metrics. What should they add to their observability stack?

   • AMore detailed logging in each service to see the order of operations.
   • BA new dashboard in Grafana that shows all service logs side by side.
   • CAdditional metrics for each service's CPU and memory usage.
   • DDistributed tracing with a tool like Jaeger to trace a checkout request across all services and see where time is spent.
   Reveal Solution Discussion Select an answer first
4. 3application · medium

   A team wants to monitor a Python Flask application. They need to collect metrics like request count and latency, and visualize them on a dashboard. They also want to set up alerts. Which integration approach is most efficient?

   • AWrite a custom script that parses the application logs and sends metrics to Prometheus.
   • BHave the application write metrics to a file and use Prometheus node exporter to read it.
   • CUse the Prometheus client library for Python to expose metrics, and configure Prometheus to scrape them.
   • DUse a third-party APM agent that automatically instruments the app and sends data to a SaaS platform.
   Reveal Solution Discussion Select an answer first
5. 4expert · hard

   A team is troubleshooting a performance issue. They have a trace showing that a request to the order service takes 2 seconds, but the database query inside the trace only takes 100 ms. The logs show that the order service is waiting for a response from the inventory service. The inventory service trace shows a 1.5-second delay. What is the most likely root cause?

   • AThe database query is slow, despite the trace showing 100 ms.
   • BThe order service is waiting for a response from the inventory service, but the inventory service is not the bottleneck.
   • CThe inventory service is slow, as shown by the 1.5-second delay in its trace.
   • DThe network between the order and inventory services is slow.
   Reveal Solution Discussion Select an answer first
6. 5application · medium

   A DevOps team wants to monitor the performance of a REST API. They need to detect when the 95th percentile response time exceeds 500 ms for more than 5 minutes. They plan to use Prometheus and Grafana. What should they do?

   • AExpose a counter metric for total response time and divide by the number of requests in Grafana.
   • BLog every response time and use the log aggregator to calculate the 95th percentile.
   • CExpose a gauge metric that stores the latest response time and configure a Grafana alert on that gauge.
   • DExpose a histogram metric for response times and configure a Prometheus alerting rule that fires when the histogram's 95th percentile exceeds 500 ms for 5 minutes.
   Reveal Solution Discussion Select an answer first