1Z0-997-25 Question 158
Single answerYou have a containerized microservices application running on Oracle Container Engine for Kubernetes (OKE). You want to collect and analyze logs from all pods across the cluster in Oracle Logging Analytics. Which approach is the most effective and recommended solution to centrally gather and forward container logs for advanced log analysis?
- A
Use the default container stdout streams without additional configuration and enable Application Performance Monitoring to automatically collect all container logs
- B
Deploy the Oracle Cloud Infrastructure (OCI) Logging Fluentd DaemonSet in your OKE cluster and configure a Service Connector to stream logs from OCI Logging to Logging Analytics
- C
Attach an OCI Logging Analytics plugin to each individual pod� Dockerfile and manually push logs to Object Storage for offline analysis
- D
Install a third-party logging agent on each cluster node to push logs directly to Oracle Logging Analytics without using OCI Logging
Show answer and explanation
Correct answer: B
Explanation
The most efficient way to collect and analyze container logs from an OKE cluster is to deploy the OCI Logging Fluentd DaemonSet, which automatically gathers logs from all pods on each node and sends them to OCI Logging. From there, you can use a Service Connector to forward logs to Logging Analytics, enabling centralized log management, real-time querying, and advanced analytics. Refer to Oracle documentation on 'Using Logging with OKE' and 'Logging Analytics' for the recommended best practices for container log ingestion and analysis.
- A. Incorrect.
Incorrect. While Application Performance Monitoring can capture some telemetry data, it does not automatically collect and centralize all container logs via stdout. Additional logging configuration is required to analyze logs across pods.
- B. Correct.
Correct. Deploying the OCI Logging Fluentd DaemonSet is the recommended approach for OKE. The DaemonSet captures container logs at the node level and sends them to OCI Logging. A Service Connector can then route these logs from OCI Logging to Logging Analytics for advanced correlation and analytics.
- C. Incorrect.
Incorrect. Embedding a plugin in each Dockerfile is inefficient and error-prone. Manual pushes to Object Storage do not provide real-time ingestion or the integrated analysis capabilities that Logging Analytics offers when used with OCI Logging and Service Connectors.
- D. Incorrect.
Incorrect. Although third-party logging agents can collect logs, bypassing OCI Logging to send data straight to Logging Analytics forgoes important integration features and can complicate troubleshooting. The Oracle-recommended solution is to leverage OCI Logging before routing logs to Logging Analytics.