AWS Certified Data Engineer – AssociateData Operations and MonitoringMedium
A data engineering team manages a daily ETL pipeline that processes terabytes of data using AWS Glue. The pipeline has been running successfully for months, but recently, the Glue jobs started failing intermittently with 'Container exited with a non-zero exit code' errors, specifically when processing larger datasets. These failures occur without any code changes and seem to correlate with peak load times. The team needs to diagnose and resolve these intermittent failures efficiently. Which action should they take FIRST?
- AImplement a retry mechanism within the Glue job script using AWS Step Functions.
- BRefactor the Glue job script to use Apache Spark's adaptive query execution (AQE) for better resource management.
- CAnalyze CloudWatch Logs for the Glue job to identify specific error messages or resource constraints.
- DIncrease the number of DPUs (Data Processing Units) allocated to the Glue job.
Show answer & explanationAnswer & explanation
Correct answer: C. Analyze CloudWatch Logs for the Glue job to identify specific error messages or resource constraints.
Analyzing CloudWatch Logs is the first step in troubleshooting Glue job failures. The 'Container exited with a non-zero exit code' is a generic error, and logs will provide specific details about the underlying cause, such as out-of-memory errors, disk space issues, or application-specific exceptions.
Why the other options are wrong
- A. Implementing a retry mechanism addresses symptom (intermittent failure) but not the root cause, and might just lead to repeated failures if the underlying issue persists.
- B. Refactoring the job is a potential solution for performance or resource issues but should only be done after diagnosing the specific problem from logs, as it requires significant development effort.
- D. Increasing DPUs might resolve some resource issues but is a reactive measure without understanding the root cause, potentially leading to unnecessary cost increases.
Glue Job Troubleshooting
The primary step for troubleshooting AWS Glue job failures is to examine CloudWatch Logs for detailed error messages, stack traces, and resource utilization metrics to identify the root cause.
- CloudWatch Logs are central for Glue job diagnostics.
- 'Non-zero exit code' is a generic error needing log analysis.
- Resource constraints (memory, disk) are common causes.
Memory trick: When Glue jobs crash, the logs hold the truth.