Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

Container restart failures require detailed observability into pod-level, node-level, and container-level metrics and logs. CloudWatch Container Insights is purpose-built for Kubernetes operational diagnostics and provides granular visibility into CPU, memory, network I/O, disk I/O, container restarts, OOM kills, throttling, pod lifecycle issues, and Kubernetes control plane behaviors.

The CloudWatch Observability add-on deploys Fluent Bit and the CloudWatch Agent directly into the EKS cluster as DaemonSets. These components automatically collect:

Container logs

Pod metrics

Node metrics

Cluster events

OOM errors

CrashLoopBackOff restart cycles

Control plane request anomalies

With this data, the DevOps engineer can easily identify misconfigurations, resource bottlenecks, unhealthy nodes, failing containers, or image pull issues.

Option A (dashboards only) lacks per-container diagnostic data.

Option B (CloudTrail) only logs API calls — not useful for restart debugging.

Option C (CloudTrail Insights) only detects anomalous API usage, not container failures.

Therefore, CloudWatch Container Insights is the correct and AWS-recommended solution for diagnosing container restart failures in EKS.

Configure a CloudWatch alarm on StatusCheckFailed_System and set the EC2 recovery action. Instance recovery automatically recovers the instance on impaired hardware while preserving the instance ID, private IPs, EBS volumes, and metadata.

The condition is deterministic: maximum CPU utilization must be below 2% for the previous 24 one-hour periods. That requires a static threshold, not anomaly detection. Anomaly detection learns a normal band from historical behavior, which is useful for unusual patterns but not for a fixed business definition of “idle.” CloudWatch alarms use “Datapoints to Alarm” as an M-out-of-N evaluation model, so 24 out of 24 means all 24 hourly datapoints must breach the threshold. AWS also documents idle-instance alarm examples based on CPU utilization staying below a threshold for 24 consecutive periods. Option D would alarm if only one hour was below 2%, which is far too sensitive. Options A and C use the wrong threshold type.

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