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EXAMPLE QUESTIONS
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175 Blueprints
Airbyte ingests, dbt transforms, Hightouch activates, Slack confirms, the full reverse-ETL chain in one flow.
Clone a Git repository of PySpark code and run a Spark job with spark-submit, fully orchestrated by Kestra.
Clone a GitHub repository and run a version-controlled Python ETL script in an isolated Docker container.
Download a file from Google Cloud Storage, clean it with Python and pandas, and load the curated result into BigQuery on a schedule.
React to new Postgres rows, land the data in S3 and Databricks, aggregate it with a Databricks job, and validate the result with a Python data quality check.
Run any parameterised SQL query against a Postgres database and store every result row for downstream tasks.
Query a remote Parquet file with DuckDB and export the results straight to an Excel spreadsheet.
Fetch data from a REST API and publish it to a Kafka topic with Kestra.
Clone Python ETL scripts from Git, extract API data in Docker, and load it into Postgres with Kestra.
Extract data from an API with Python, load it into Postgres, and archive a copy to Amazon S3.
Move Apache Pinot query results into BigQuery as a clean, schema-typed CSV load.
Extract multiple Postgres tables in parallel and crunch them into a bestsellers report with Python and Pandas, on a daily schedule.
Fetch trending HackerNews stories, store them in PostgreSQL, generate an AI trend digest with OpenAI, and post a daily briefing to Slack.
Run a GPU-accelerated Python script on Modal's serverless cloud, orchestrated end to end with Kestra.
Auto-load files into BigQuery the moment they land in a Google Cloud Storage bucket, then archive each object so it never re-triggers.
Reprocess an S3 file only when it changed, on a schedule, using Python and boto3.
Publish each row of a CSV file as a message to a RabbitMQ exchange with Kestra.
Read a Google Spreadsheet and load its rows straight into a BigQuery table with automatic schema detection.
Parameterize and run a Jupyter notebook end to end with Papermill inside a Kestra Python task.
Run a Shell script directly on the Kestra host as a child process using the lightweight Process task runner.
Run a ZenML machine learning pipeline from Kestra on a schedule, with logs streamed in real time.
Poll a Google Sheet every 2 minutes and subscribe each lead's email to a Mailchimp audience automatically.
Automatically find stale GitLab issues every week and open a triage tracking issue for your team.
Run four Fivetran connector syncs in parallel, then build your dbt Core models on the freshly loaded data.