Google Professional Cloud DevOps Engineer Question 127
Select 3Google Cloud PlatformYour team has noticed intermittent application performance issues in a production system hosted on Google Kubernetes Engine (GKE). You suspect that the root cause might be related to increasing memory usage in one of the microservices. You want to analyze the logs to confirm this hypothesis. Which of the following steps should you take to efficiently identify memory-related issues in the logs using Google Cloud tools?
- A
Use Cloud Logging to filter logs by resource type 'GKE Container' and search for memory usage patterns or warnings.
- B
Enable Debugger snapshots on the GKE workload to capture memory usage details in real-time.
- C
Create a custom log-based metric in Cloud Logging to track memory usage over time.
- D
Leverage Cloud Monitoring to view memory usage metrics and correlate them with specific log entries.
- E
Export the logs from Cloud Logging to BigQuery for advanced querying and analysis of memory-related issues.
Show answer and explanation
Correct answers: A, C, D
Explanation
To analyze logs for memory-related issues in a GKE production system, it's efficient to use Cloud Logging to filter relevant logs and Cloud Monitoring to correlate memory metrics with logs. Additionally, creating custom log-based metrics helps track memory usage trends over time. Debugger snapshots are not suited for this purpose, and exporting logs to BigQuery, while powerful, is not the most immediate solution.
- A. Correct.
Correct. Filtering logs by resource type 'GKE Container' and searching for memory usage patterns or warnings in Cloud Logging is a direct approach to diagnosing memory-related issues in containerized applications.
- B. Incorrect.
Incorrect. Debugger snapshots are used for inspecting application state at specific code points and are not primarily designed for memory usage analysis.
- C. Correct.
Correct. Creating a custom log-based metric allows you to track memory usage trends over time and provides valuable insights when debugging performance issues.
- D. Correct.
Correct. Cloud Monitoring provides metrics like memory usage, and correlating these metrics with log entries helps in identifying the root cause of performance issues.
- E. Incorrect.
Incorrect. While exporting logs to BigQuery can be useful for advanced querying, it is not the most efficient or immediate approach for analyzing memory-related issues compared to directly using Cloud Logging and Monitoring.