AWS Certified Data Engineer Associate DEA-C01 Practice Question
Your team uses a CodePipeline workflow to deploy AWS Glue ETL jobs. A new requirement from operations states that each new job must automatically configure a dedicated CloudWatch Logs group for its driver and executor output. The log group must have a 14-day retention period and a metric filter that counts lines containing the word "ERROR". The solution must minimize manual effort and scale for dozens of new jobs each month. Which approach meets these requirements?
Manually create a single CloudWatch Logs group and metric filter in the console and allow every Glue job to write to the same group.
Modify each Glue job script to call the AWS SDK at runtime to create the log group and metric filter if they do not already exist.
Enable CloudTrail data events for AWS Glue and set a 14-day retention policy on the CloudTrail log group to capture job activity.
Add a CloudFormation stack action to the pipeline that creates an AWSLogsLogGroup resource parameterized with the job name, sets a 14-day retention period, and defines the required metric filter before the Glue job is deployed.
Adding an infrastructure-as-code step to the deployment pipeline ensures that every Glue job is accompanied by the required CloudWatch Logs configuration. A CloudFormation stack can create a log group whose name is passed in as a parameter, set RetentionInDays to 14, and define a metric filter that searches for the "ERROR" pattern. Because the stack is executed automatically by CodePipeline, the process is repeatable and works for any number of jobs without manual intervention.
Creating the log group in the job's Python code causes the resource creation logic to run every execution, introduces IAM overhead, and does not guarantee that the metric filter is in place before logs arrive. Manually creating log groups in the console does not scale to frequent job launches and is prone to human error. Enabling CloudTrail data events only records API activity and does not capture the driver or executor log lines needed by Operations.
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AWS Certified Data Engineer Associate DEA-C01
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