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Question 920
A checkout API fails across two microservices yet trace context is discarded at the message queue boundary. Choose TWO measures that implement and verify an effective Azure DevOps response to this specific situation. (Choose TWO.)
- Declare application insights request correlation and distributed tracing successful solely from a green pipeline status and skip checking its actual control outcome.
- Instrument Application Insights with distributed tracing and propagate operation identifiers across supported services.
- Bypass review and testing for application insights request correlation and distributed tracing whenever the release deadline is urgent, applying the change to production immediately.
- Dismiss the known risk for application insights request correlation and distributed tracing and keep no evidence or accountable owner after deployment.
- Follow a test request through dependency timings, exceptions, and correlated operation IDs in telemetry.
Explanation
Correct Answers
B:Instrument Application Insights with distributed tracing and propagate operation identifiers across supported services. Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions. Investigators may repair the wrong service when requests cannot be traced across boundaries.
E:Follow a test request through dependency timings, exceptions, and correlated operation IDs in telemetry. Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions.
Incorrect Answers
A:Declare application insights request correlation and distributed tracing successful solely from a green pipeline status and skip checking its actual control outcome. It conflicts with the stated operating condition: Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions.
C:Bypass review and testing for application insights request correlation and distributed tracing whenever the release deadline is urgent, applying the change to production immediately. It conflicts with the stated operating condition: Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions.
D:Dismiss the known risk for application insights request correlation and distributed tracing and keep no evidence or accountable owner after deployment. It conflicts with the stated operating condition: Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions.
Question 921
An AKS platform alerts only on VM CPU and misses pods repeatedly restarting because of out-of-memory failures. Which solution should be prioritized to resolve the stated failure?
- Configure Azure Monitor diagnostic settings and workspace routing for critical DevOps workloads and relevant resource metrics.
- Configure Azure VM Insights or suitable agent-based data collection for memory, disk, process, and guest metrics.
- Enable appropriate Azure Monitor Container Insights collection and alerts for nodes, pods, restarts, and utilization.
- Enable relevant Azure Storage, network, and private-endpoint diagnostics with actionable request and dependency metrics.
Explanation
Correct Answer
C:Enable appropriate Azure Monitor Container Insights collection and alerts for nodes, pods, restarts, and utilization. Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction. A cluster can appear healthy at the VM level while customer applications repeatedly fail.
Incorrect Answers
A:Configure Azure Monitor diagnostic settings and workspace routing for critical DevOps workloads and relevant resource metrics.
B:Configure Azure VM Insights or suitable agent-based data collection for memory, disk, process, and guest metrics. That applies to azure vm insights memory disk and process telemetry, not azure container insights for aks node and pod reliability.
D:Enable relevant Azure Storage, network, and private-endpoint diagnostics with actionable request and dependency metrics. That applies to azure storage and network diagnostics for deployment troubleshooting, not azure container insights for aks node and pod reliability.
Question 922
An AKS platform alerts only on VM CPU and misses pods repeatedly restarting because of out-of-memory failures. Which evidence would BEST demonstrate that the fix operates as intended?
- Trigger a benign test event and verify its resource, timestamp, metric, and log record appear in the expected workspace.
- Follow a test request through dependency timings, exceptions, and correlated operation IDs in telemetry.
- Trigger a controlled pod failure in staging and verify restart, node, and container metrics and logs are correlated.
- Create a controlled resource threshold and verify the matching guest metric, alert, and operating-system log event.
Explanation
Correct Answer
C:Trigger a controlled pod failure in staging and verify restart, node, and container metrics and logs are correlated. Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction.
Incorrect Answers
A:Trigger a benign test event and verify its resource, timestamp, metric, and log record appear in the expected workspace. That applies to azure monitor platform metrics and log analytics integration, not azure container insights for aks node and pod reliability.
B:Follow a test request through dependency timings, exceptions, and correlated operation IDs in telemetry. That applies to application insights request correlation and distributed tracing, not azure container insights for aks node and pod reliability.
D:Create a controlled resource threshold and verify the matching guest metric, alert, and operating-system log event.
Question 923
An AKS platform alerts only on VM CPU and misses pods repeatedly restarting because of out-of-memory failures. Which DevOps implementation principle BEST explains the issue?
- Host and guest measurements differ; default platform telemetry may not expose the failing application resource.
- CI reliability is an operational service and must surface broken or stalled workflows to accountable responders.
- Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions.
- Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction.
Explanation
Correct Answer
D:Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction. A cluster can appear healthy at the VM level while customer applications repeatedly fail.
Incorrect Answers
A:Host and guest measurements differ; default platform telemetry may not expose the failing application resource. That applies to azure vm insights memory disk and process telemetry, not controlling principle for azure container insights for aks node and pod reliability.
B:CI reliability is an operational service and must surface broken or stalled workflows to accountable responders. That applies to github actions run health and workflow failure alerts, not controlling principle for azure container insights for aks node and pod reliability.
C:Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions.
Question 924
An AKS platform alerts only on VM CPU and misses pods repeatedly restarting because of out-of-memory failures. What preventive practice should be maintained after the fix?
- Periodically test notification routes and review workflow changes that disable mandatory checks.
- Monitor agent health and keep data-collection rules aligned with current VM image versions.
- Review agent collection health and resource dimensions when clusters and workloads are upgraded.
- Review trace sampling and context propagation when endpoints and async queues change.
Explanation
Correct Answer
C:Review agent collection health and resource dimensions when clusters and workloads are upgraded. A cluster can appear healthy at the VM level while customer applications repeatedly fail.
Incorrect Answers
A:Periodically test notification routes and review workflow changes that disable mandatory checks. This helps sustain a control for github actions run health and workflow failure alerts; it does not directly stop recurrence of azure container insights for aks node and pod reliability described in this case.
B:Monitor agent health and keep data-collection rules aligned with current VM image versions.
D:Review trace sampling and context propagation when endpoints and async queues change. This helps sustain a control for application insights request correlation and distributed tracing; it does not directly stop recurrence of azure container insights for aks node and pod reliability described in this case.
Question 925
An AKS platform alerts only on VM CPU and misses pods repeatedly restarting because of out-of-memory failures. What outcome most clearly explains the business impact?
- Important production failures may be hidden when expected log and metric streams were never enabled.
- Blind spots in service dependencies can cause repeated job retries without identifying root cause.
- A cluster can appear healthy at the VM level while customer applications repeatedly fail.
- Investigators may repair the wrong service when requests cannot be traced across boundaries.
Explanation
Correct Answer
C:A cluster can appear healthy at the VM level while customer applications repeatedly fail. This is the directly relevant business or security consequence of azure container insights for aks node and pod reliability. Root cause: Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction.
Incorrect Answers
A:Important production failures may be hidden when expected log and metric streams were never enabled. That risk is relevant to azure monitor platform metrics and log analytics integration, but the specific unresolved condition here concerns azure container insights for aks node and pod reliability and has a different direct consequence.
B:Blind spots in service dependencies can cause repeated job retries without identifying root cause. That risk is relevant to azure storage and network diagnostics for deployment troubleshooting, but the specific unresolved condition here concerns azure container insights for aks node and pod reliability and has a different direct consequence.
D:Investigators may repair the wrong service when requests cannot be traced across boundaries. That risk is relevant to application insights request correlation and distributed tracing, but the specific unresolved condition here concerns azure container insights for aks node and pod reliability and has a different direct consequence.
Question 926
A containerized service exhausts one node's ephemeral storage but no pod-level metrics or events are available to responders. Which implementation BEST addresses the operational issue?
- Enable relevant Azure Storage, network, and private-endpoint diagnostics with actionable request and dependency metrics.
- Enable appropriate Azure Monitor Container Insights collection and alerts for nodes, pods, restarts, and utilization.
- Configure Azure Monitor diagnostic settings and workspace routing for critical DevOps workloads and relevant resource metrics.
- Configure Azure VM Insights or suitable agent-based data collection for memory, disk, process, and guest metrics.
Explanation
Correct Answer
B:Enable appropriate Azure Monitor Container Insights collection and alerts for nodes, pods, restarts, and utilization. Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction. A cluster can appear healthy at the VM level while customer applications repeatedly fail.
Incorrect Answers
A:Enable relevant Azure Storage, network, and private-endpoint diagnostics with actionable request and dependency metrics. That applies to azure storage and network diagnostics for deployment troubleshooting, not azure container insights for aks node and pod reliability.
C:Configure Azure Monitor diagnostic settings and workspace routing for critical DevOps workloads and relevant resource metrics.
D:Configure Azure VM Insights or suitable agent-based data collection for memory, disk, process, and guest metrics. That applies to azure vm insights memory disk and process telemetry, not azure container insights for aks node and pod reliability.
Question 927
A containerized service exhausts one node's ephemeral storage but no pod-level metrics or events are available to responders. How should the team validate the intended result?
- Create a controlled resource threshold and verify the matching guest metric, alert, and operating-system log event.
- Follow a test request through dependency timings, exceptions, and correlated operation IDs in telemetry.
- Trigger a benign test event and verify its resource, timestamp, metric, and log record appear in the expected workspace.
- Trigger a controlled pod failure in staging and verify restart, node, and container metrics and logs are correlated.
Explanation
Correct Answer
D:Trigger a controlled pod failure in staging and verify restart, node, and container metrics and logs are correlated. Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction.
Incorrect Answers
A:Create a controlled resource threshold and verify the matching guest metric, alert, and operating-system log event.
B:Follow a test request through dependency timings, exceptions, and correlated operation IDs in telemetry. That applies to application insights request correlation and distributed tracing, not azure container insights for aks node and pod reliability.
C:Trigger a benign test event and verify its resource, timestamp, metric, and log record appear in the expected workspace. That applies to azure monitor platform metrics and log analytics integration, not azure container insights for aks node and pod reliability.
Question 928
A containerized service exhausts one node's ephemeral storage but no pod-level metrics or events are available to responders. Which DevOps implementation principle BEST explains the issue?
- Host and guest measurements differ; default platform telemetry may not expose the failing application resource.
- Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction.
- CI reliability is an operational service and must surface broken or stalled workflows to accountable responders.
- Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions.
Explanation
Correct Answer
B:Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction. A cluster can appear healthy at the VM level while customer applications repeatedly fail.
Incorrect Answers
A:Host and guest measurements differ; default platform telemetry may not expose the failing application resource. That applies to azure vm insights memory disk and process telemetry, not controlling principle for azure container insights for aks node and pod reliability.
C:CI reliability is an operational service and must surface broken or stalled workflows to accountable responders. That applies to github actions run health and workflow failure alerts, not controlling principle for azure container insights for aks node and pod reliability.
D:Aggregate request totals cannot identify which distributed dependency is responsible for slow or failing transactions.
Question 929
A containerized service exhausts one node's ephemeral storage but no pod-level metrics or events are available to responders. What preventive practice should be maintained after the fix?
- Review agent collection health and resource dimensions when clusters and workloads are upgraded.
- Periodically test notification routes and review workflow changes that disable mandatory checks.
- Monitor agent health and keep data-collection rules aligned with current VM image versions.
- Review trace sampling and context propagation when endpoints and async queues change.
Explanation
Correct Answer
A:Review agent collection health and resource dimensions when clusters and workloads are upgraded. A cluster can appear healthy at the VM level while customer applications repeatedly fail.
Incorrect Answers
B:Periodically test notification routes and review workflow changes that disable mandatory checks. This helps sustain a control for github actions run health and workflow failure alerts; it does not directly stop recurrence of azure container insights for aks node and pod reliability described in this case.
C:Monitor agent health and keep data-collection rules aligned with current VM image versions.
D:Review trace sampling and context propagation when endpoints and async queues change. This helps sustain a control for application insights request correlation and distributed tracing; it does not directly stop recurrence of azure container insights for aks node and pod reliability described in this case.
Question 930
A containerized service exhausts one node's ephemeral storage but no pod-level metrics or events are available to responders. What outcome most clearly explains the business impact?
- Investigators may repair the wrong service when requests cannot be traced across boundaries.
- Blind spots in service dependencies can cause repeated job retries without identifying root cause.
- A cluster can appear healthy at the VM level while customer applications repeatedly fail.
- Important production failures may be hidden when expected log and metric streams were never enabled.
Explanation
Correct Answer
C:A cluster can appear healthy at the VM level while customer applications repeatedly fail. This is the directly relevant business or security consequence of azure container insights for aks node and pod reliability. Root cause: Kubernetes resource health spans nodes and pods, so VM-only telemetry cannot describe application readiness or eviction.
Incorrect Answers
A:Investigators may repair the wrong service when requests cannot be traced across boundaries. That risk is relevant to application insights request correlation and distributed tracing, but the specific unresolved condition here concerns azure container insights for aks node and pod reliability and has a different direct consequence.
B:Blind spots in service dependencies can cause repeated job retries without identifying root cause. That risk is relevant to azure storage and network diagnostics for deployment troubleshooting, but the specific unresolved condition here concerns azure container insights for aks node and pod reliability and has a different direct consequence.
D:Important production failures may be hidden when expected log and metric streams were never enabled. That risk is relevant to azure monitor platform metrics and log analytics integration, but the specific unresolved condition here concerns azure container insights for aks node and pod reliability and has a different direct consequence.
Designing and Implementing Microsoft DevOps Solutions (AZ-400) Practice Tests
