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175 Blueprints
Watch a local processing directory for finished output files, archive each one into a dated folder as it lands, and sweep stale .tmp scratch files left behind by interrupted runs.
Download a remote CSV and bulk-load it into MySQL with a declarative, secret-secured ELT pipeline.
Pull a file from a Microsoft Fabric Lakehouse, transform it with Python, and write the result back to OneLake.
Run a Fabric ingestion pipeline, transform data with a Notebook, and validate results in the Warehouse, all from a single Kestra flow.
Event-driven ingestion that lands new S3 files into an Apache Iceberg data lake and merges them with Amazon Athena.
Query a PostgreSQL table and upload the result as a date-partitioned CSV into a Microsoft Fabric Lakehouse on OneLake.
Fetch JSON from a REST API and load it straight into MongoDB as a document, parameterized by a runtime input.
Call a REST API in a Dockerized Python task, save the JSON, and load it straight into a MongoDB collection.
Detect new files in S3 every hour and ingest them into an Apache Iceberg data lake with Git, Python, and Athena.
Detect new CSV files in S3, clean them with Python, and load them into an Apache Iceberg data lake on AWS Glue and Athena.
Download multiple CSV files over HTTP and merge them into a single multi-sheet Excel workbook.
Fetch weather data from an API, reshape it with DuckDB, and load it into InfluxDB as time series points.
Purge expired transients, spam comments, and old post revisions from a MariaDB-backed WordPress database on a schedule, then reclaim disk space with OPTIMIZE TABLE.
Run a scheduled T-SQL query against a Microsoft Fabric Warehouse and store the results in Kestra internal storage.
A realtime Kafka trigger starts one execution per record, branches on the payload, and alerts Slack on anomalies.
Trigger a Microsoft Fabric Data Pipeline, pass runtime parameters, and wait for completion.
Submit a Microsoft Fabric notebook job with parameters and wait for it to complete.
Submit a Microsoft Fabric Spark Job Definition and wait for it to finish.
Download a remote CSV, create the target table with DDL, and bulk load it into Postgres on a single Kestra flow.
Sync every HubSpot CRM object into BigQuery on a daily schedule using CloudQuery.
Automatically create HubSpot contacts from new and updated rows in your Postgres customers table.
Sync multiple Fivetran connectors in parallel, then trigger a dbt Cloud transformation job, all from one Kestra flow.
Capture Postgres row changes with Debezium CDC, then notify Slack and process the new data in Python automatically.
Validate a nested order webhook payload for required fields with JSONata, flatten it into a flat record with computed totals, and only forward it once it passes.