You are migrating a legacy Airflow environment to Cloud Composer. You need to ensure that local Python packages used by custom operators are installed correctly. What is the recommended approach?
You are building a data pipeline using Cloud Workflows that calls a series of Cloud Functions. The output of one function must be passed as an argument to the next function. How should you structure the workflow to achieve this?
Your team runs a Cloud Composer 2 environment. A DAG must run only after a new object lands in a Cloud Storage bucket, and the DAG should not poll the bucket. You want the least operational overhead. What should you do?
Your team uses Workflows to orchestrate a daily ETL job that calls a Cloud Run service. The job occasionally takes longer than expected, and you need to ensure that the workflow automatically retries a failed HTTP call up to 3 times with a 10-second delay between attempts. What should you configure in the Workflows YAML definition?
You are designing a data pipeline using Cloud Composer 2. You need to ensure that your DAG can be triggered automatically based on the arrival of new files in a Cloud Storage bucket. Which TWO of the following methods can be used to trigger the DAG? (Choose two.)
You are designing a Cloud Workflows definition that must call an external HTTP API. The API requires an OAuth 2.0 access token in the Authorization header, and the token is stored in Secret Manager. You want the workflow to retrieve the token securely at runtime without hardcoding credentials. Which step should you include in the workflow?
You are creating a Workflows definition to orchestrate a series of microservices. You need to define the starting point of the workflow. Which field in the Workflows YAML is used to specify the entry point?
Your Cloud Composer 2 environment runs an Airflow DAG that starts a Dataflow streaming job and then needs to wait until that job reports a terminal state before running a downstream cleanup task. You want the DAG to pause without occupying a worker slot while the Dataflow job runs, and to resume as soon as the job finishes. What should you do?
You are writing a Workflows YAML definition that must call a Cloud Function, extract a value from its JSON response, and pass that value as an argument to a subsequent BigQuery insert step. You need to reference the output of the first step in the second step. Which syntax should you use?
You are creating a Cloud Workflows definition to orchestrate a data pipeline. You need to define the starting point of the workflow. Which top-level property must you include in the YAML definition to specify the first step to execute?
You are using Workflows to orchestrate a data processing pipeline. One step invokes a Cloud Function that returns a JSON payload containing a processed record ID. You need to pass this record ID as an argument to a subsequent Cloud Function. How should you reference the output of the first function in the Workflows YAML definition?
You are building a Workflows pipeline that calls a Cloud Function to process an image and then stores the result in Cloud Storage. The Cloud Function returns a JSON object with a 'status' field and a 'fileUrl' field. You need to pass the 'fileUrl' to a subsequent step that uploads the file to a Cloud Storage bucket. How should you reference the output of the Cloud Function in the Workflows YAML definition?
You are deploying a Cloud Composer environment and need to install a custom Python package that your DAGs depend on. The package is not available on PyPI and is provided as a .whl file in a Cloud Storage bucket. What is the recommended way to make this package available to all Airflow workers?
You are designing a Cloud Composer 2 deployment to orchestrate a data pipeline that loads files from Cloud Storage into BigQuery. Your security team requires that the Airflow tasks access Google Cloud services using the environment's own identity rather than user credentials, and that DAG authors can use pre-built operators for GCS and BigQuery. Which two actions should you take to meet these requirements? (Choose two.)
You are using Cloud Composer to orchestrate a data pipeline. A task in your Airflow DAG runs a long-running process that may exceed the default Airflow worker pod timeout. You need to ensure the task can run for up to 2 hours without being killed. What should you do?
You are using Cloud Scheduler to trigger a Workflows execution every hour. You need to authenticate the scheduler job to the Workflows API. Which authentication method should you configure in the Cloud Scheduler job?
You are designing a data pipeline that uses Cloud Composer to orchestrate tasks across multiple Google Cloud services. You need to ensure that the pipeline can be triggered automatically on a schedule and also manually by data analysts. Which TWO methods can be used to trigger a Cloud Composer DAG? (Choose two.)
You are migrating an on-premises Airflow deployment to Cloud Composer 2. Your DAGs use custom operators that depend on a specific Python package version not available on PyPI. You need to ensure these operators work in Cloud Composer without modifying the DAG code. What should you do?
You are designing a data pipeline using Cloud Composer. You need to ensure that a specific task runs only after two upstream tasks, taskA and taskB, have both completed successfully. Which TWO of the following approaches correctly define this dependency in the DAG? (Choose two.)
Your organization uses Cloud Scheduler to start a Workflows execution every hour. The Workflows definition expects no input arguments and simply runs a sequence of API calls. Which HTTP method and target should the Cloud Scheduler job use to invoke the workflow?
You are designing a data pipeline using Cloud Workflows. You need to pass the output of one step as an argument to a subsequent step. Which TWO of the following are valid ways to reference the output of a previous step in a Workflows YAML definition? (Choose two.)
You are migrating a legacy Airflow environment to Cloud Composer. Your DAGs use custom Python operators that depend on a local Python package stored in a `requirements.txt` file. You need to ensure that the package is available to all Airflow workers and the scheduler. What is the recommended approach in Cloud Composer 2?
You are authoring a Workflows definition that must call a Cloud Run service and then branch on the returned HTTP status. Some calls return 404 because the target resource has not been provisioned yet, and you want the workflow to retry only that condition while letting 500 errors fail fast. How should you implement this in the Workflows YAML?
A Cloud Composer 2 environment runs a DAG whose final task must invoke a Workflows execution and wait for its result before the DAG marks success. The Workflows execution can take up to 40 minutes. Which approach correctly waits for completion without blocking a worker slot indefinitely?
You are orchestrating a pipeline with Workflows that invokes several Cloud Functions. You need to pass the output of one function as an argument to the next. What is the correct syntax?
In a Cloud Composer DAG, you need to trigger a BigQuery job that runs as a service account other than the one assigned to the GKE nodes. How should you implement this?
Your organization uses Workflows to orchestrate multi-step API calls. You need to handle transient failures in a specific HTTP request by retrying it up to 5 times with exponential backoff. Which block should you use?
A Cloud Composer DAG is failing because the Airflow database is locking up during high-concurrency periods. What is the most effective way to address this?
You are deploying a Cloud Composer 2 environment and need to ensure that the DAG files are automatically synchronized to all workers. Where should you store these files?
You are troubleshooting a stuck task in Cloud Composer. You want to see the stdout/stderr logs for that specific task attempt. Where can you find them?
You are using Airflow with a Cloud Composer environment. You want to ensure that a specific task runs on a specific day of the week. How do you configure the schedule?
Your team runs a Cloud Composer 2 environment with several DAGs that process data in Cloud Storage. You need to design a DAG that reliably handles transient failures when calling the Cloud Storage API. The DAG should retry failed tasks automatically without manual intervention, but you also want to avoid overwhelming the API during an outage. Which combination of Airflow features should you implement to achieve this?
You are using Cloud Composer to orchestrate a data pipeline. A critical task in your DAG is failing intermittently due to a known transient error in an external API. You want to automatically retry the task up to 5 times with a 2-minute delay between retries. Which Airflow feature should you configure to achieve this?
You are orchestrating a data pipeline in Cloud Composer 2. A task in your DAG downloads a large dataset from Cloud Storage and can take up to 45 minutes to complete, but it occasionally fails and needs to be retried. You want the task to automatically retry up to 3 times with a 5-minute delay between attempts. Which Airflow task parameter should you configure to achieve this?
Your team uses Cloud Composer (Airflow) to run a daily ETL DAG. A task occasionally fails due to transient network errors when calling an external API. You want the task to retry automatically up to 3 times with a 5-minute delay between attempts, and you want the DAG to continue running other tasks even if this task ultimately fails. Which combination of Airflow task parameters should you configure?
You are designing a Cloud Workflows pipeline that calls a series of Cloud Functions. The output of the first function must be passed as an argument to the second function, and the output of the second to the third. You need to define the workflow in YAML. Which Workflows syntax correctly assigns the result of a function call to a variable and then uses that variable in a subsequent call?
Your team runs a Cloud Composer 2 environment where several DAGs import a shared internal Python library. After a library update, tasks begin failing with ModuleNotFoundError across all workers. You need the library to be installed automatically on every worker and scheduler node, including after autoscaling events. What should you do?
You are using Workflows to orchestrate a series of steps that call external HTTP APIs. One API occasionally returns a 503 error, and you want the workflow to retry that specific step with exponential backoff, but not retry on 404 errors. How should you configure the step?
You are using Cloud Scheduler to trigger a Cloud Workflows execution every hour. You need to ensure that the scheduler authenticates to the Workflows API securely. Which two of the following are valid methods for authenticating Cloud Scheduler to Workflows? (Choose two.)
You are using Cloud Composer to orchestrate a daily ETL pipeline. A task that normally completes in 10 minutes occasionally runs for over 2 hours due to unexpected data volume. You want to prevent this task from indefinitely blocking the workflow and ensure it fails after 30 minutes so downstream tasks can be retried or alerted. What should you configure on the task?
Your team runs a Cloud Composer 2 environment that processes financial data. A critical DAG must run exactly once per day at 02:00 UTC, and the Airflow scheduler must not backfill missed runs from the previous week when the DAG is unpaused. You need to configure the DAG so that only future scheduled runs execute. What should you set in the DAG definition?
You are designing a Cloud Composer 2 DAG that must process files as they arrive in a Cloud Storage bucket. You want to minimize latency and avoid unnecessary worker resource consumption. Which TWO approaches should you use? (Choose two.)
You are building a Workflows definition that calls a Cloud Run service and then passes the returned JSON payload to a Cloud Function. The Cloud Run response body is stored in a variable named result. Which syntax correctly passes that value as an argument in the subsequent call step?
You have a Cloud Composer 2 DAG that uses a PythonOperator to run a script that connects to a Cloud SQL database. The script needs a password. You want to avoid hardcoding the password in the DAG or in environment variables. What should you do?
You are using Workflows to orchestrate a data pipeline that includes a step calling a Cloud Function. The Cloud Function returns a JSON payload with a field named 'result'. You need to pass this 'result' value to a subsequent step as an argument. How should you reference the output of the Cloud Function step in the Workflows YAML?
Your Cloud Composer DAG includes a task that runs a long-running data export, and you have observed that the task sometimes exceeds the default Airflow worker pod timeout, causing the task to be killed and retried. You want to increase the allowed execution time for this task without affecting other tasks. What should you do?
A data engineer needs a lightweight, serverless orchestrator on Google Cloud to run a sequence of HTTP calls to internal microservices, retry the calls a few times on failure, and expose the whole sequence as a single REST endpoint. The workflow must not require provisioning any cluster or VM. Which Google Cloud service should be used?
You are using Cloud Scheduler to trigger a Workflows execution every hour. The Workflows definition expects an argument 'projectId' to be passed at runtime. You need to ensure the argument is provided correctly. What should you include in the Cloud Scheduler job configuration?
You are designing a Cloud Composer 2 DAG that must run a task only after a daily file has arrived in a Cloud Storage bucket. You want the DAG to avoid failing prematurely and to avoid consuming a worker slot while waiting. Which two approaches should you use? (Choose two.)
Your Workflows definition calls three Cloud Run services in sequence. The second service occasionally returns HTTP 503 during cold starts, and you want Workflows to retry those specific failures with exponential backoff while treating HTTP 400 responses as permanent failures. How should you configure this?
You maintain a Cloud Composer 2 DAG that processes files as they land in Cloud Storage. Instead of polling, you want the DAG to start processing within seconds of a new object being created, and you want the trigger to be reliable even if the Composer environment is briefly restarting. Which approach should you use?
A Cloud Composer 2 task runs a Python script that performs a long-running data transformation and regularly exceeds the default worker pod timeout, causing tasks to be killed and marked as failed. The transformation cannot be shortened and must complete within a single task. What should you do to allow the task to run to completion?