1Z0-997-25 Question 157
Single answerYou are designing a new observability solution for a distributed application running across Oracle Container Engine for Kubernetes (OKE) clusters and multiple Compute instances in different compartments. Your main goal is to centralize and correlate logs from all these environments in one place, perform advanced queries, and create dashboards for quick troubleshooting. Which approach should you implement to achieve these requirements with minimal operational overhead?
- A
Configure service connectors to automatically route logs from OCI Logging to Logging Analytics, enabling advanced correlation and dashboards.
- B
Use Object Storage to store raw logs from each microservice, then manually import those logs into a separate analytics tool.
- C
Rely solely on the OCI Monitoring service for system metrics and alerts, ignoring log data collection and correlation.
- D
Install custom logging agents that write logs to local disk for each instance and rely on on-demand SSH access to retrieve log files.
Show answer and explanation
Correct answer: A
Explanation
Using OCI Logging and Logging Analytics together with service connectors is a standard and recommended approach to centralize logs from multiple OCI services. Logging Analytics offers advanced querying, dashboards, and correlation capabilities indispensable for quickly diagnosing issues. For more details, refer to the OCI Logging and Logging Analytics documentation, which outlines best practices for collecting and analyzing logs in distributed architectures.
- A. Correct.
Correct. By setting up OCI Logging for each resource and configuring service connectors to forward logs into Logging Analytics, you obtain centralized log correlation, search, and visualization. This approach reduces operational overhead since Logging Analytics can automatically ingest and analyze logs from multiple sources, offering advanced queries, visual dashboards, and integrated analytics.
- B. Incorrect.
Incorrect. While storing raw logs in Object Storage may provide an archive, it requires significant manual effort to import, parse, and analyze these logs with a separate tool. It lacks the real-time correlation, alerting, and query capabilities offered by Logging Analytics.
- C. Incorrect.
Incorrect. OCI Monitoring is critical for metrics and alarms, but it does not handle detailed log data for correlation or troubleshooting. Exclusively relying on metrics leaves gaps in deeper root-cause analysis that logs can provide.
- D. Incorrect.
Incorrect. Storing logs locally and accessing them via SSH is labor-intensive and error-prone. It does not provide centralized correlation, searching, or alerting. It also complicates scaling and troubleshooting in a distributed environment.