1Z0-997-25 Question 155
Select 2You have a multi-tier application running on Oracle Kubernetes Engine (OKE) that generates large volumes of logs. Most of these logs are debug-level messages, with only a small subset containing critical information that needs prompt attention. You want to minimize costs by storing only essential logs in Oracle Logging Analytics, while still creating alerts for critical issues detected in the logs. Which two steps should you take to achieve this goal?
- A
Create and apply a log filter at the ingestion source to exclude debug-level logs from Oracle Logging Analytics.
- B
Route all logs, including debug-level logs, to Oracle Logging Analytics without any filtering for complete coverage.
- C
Configure a custom metric in OCI Monitoring to track critical log events, and set up an alarm for that metric.
- D
Retain all logs in local file storage on the OKE worker nodes and manually archive them to Object Storage for cost optimization.
Show answer and explanation
Correct answers: A, C
Explanation
In Oracle Cloud Infrastructure (OCI), implementing observability for log-intensive applications often requires balancing cost with the need for fast and accurate alerting. Using Oracle Logging Analytics filtering allows you to ingest only logs above a certain level (e.g., WARN or ERROR), while configuring custom metrics and alarms through OCI Monitoring ensures critical events trigger immediate alerts. Refer to OCI's Logging and Monitoring documentation for best practices on setting up log ingestion filters, creating custom metrics, and configuring alarms for crucial events.
- A. Correct.
Correct. By setting log filters at the source, you can specify which log levels (e.g., WARN, ERROR) are ingested into Oracle Logging Analytics, greatly reducing costs and focusing analysis on critical logs.
- B. Incorrect.
Incorrect. Ingesting all logs (including debug-level) without filtering will lead to higher costs and excessive noise in your observability data, counteracting the goal of minimizing costs.
- C. Correct.
Correct. Creating a custom metric triggered by critical log events provides a lightweight way to monitor and alert on critical situations, ensuring prompt detection of issues without storing unnecessary debug logs.
- D. Incorrect.
Incorrect. Keeping all logs in local storage and only manually archiving them does not provide the continuous, automated visibility and alerting required for observability solutions. You would risk missing critical real-time errors.