From automating data pipelines to accelerating machine learning model deployment, Kestra streamlines complex workflows across a wide range of industries and domains.
Say goodbye to delays in your pipeline as Kestra initiates workflows based on specific times or events, such as data arrivals or file uploads.
Efficiently manage and deploy machine learning models at scale using Kestra’s orchestration capabilities.
Move, prepare, and clean data, consolidating it into a single data mart for easy access.
Easily connect and integrate with various data sources, ensuring smooth data flow across your systems.
Automatically detect and process changes in data sources with change data capture, keeping your data up-to-date and accurate.
Configure Kestra to distribute reports via email or Slack, keeping your team informed.
Easily collect data from various sources and integrate it into your workflows.
Manage the entire data lifecycle, from ingestion to reporting, with Kestra’s powerful orchestration capabilities.
Extract JSON from a REST API, enrich it, and load it in parallel to Postgres and Amazon S3.
Extract data from a REST API, reshape it with Python and Polars, then run analytical SQL on it with DuckDB, all in one Kestra flow.
Runs parallel endpoint probes, aggregates batch metrics in DuckDB, scores drift in Python, and quarantines bad partitions.
Audit an Apify actor's most recent run status, alert Slack when it failed, timed out, or was aborted, and optionally launch a fresh retry run under a cost cap.
Run an Apify actor under hard cost and run caps, then branch on the returned item count so a degraded scrape pages the on-call instead of silently shipping bad data.
Run an Apify actor on a schedule, fetch its dataset, reshape the records, and bulk-load them into Postgres with cost caps and Slack alerts.
Run an Apify actor, pull its dataset, and publish the scraped results straight into a Notion page.
Search indexed YouTube transcripts and export timestamped passages, source links, and query details for research and video planning.
Audit Argo Workflows for workflows stuck Running far longer than reasonable, then safely terminate them with operator approval and verification.
Probe an Apache Arrow Flight SQL endpoint and alert Slack when it answers over an unencrypted connection in violation of your own TLS policy.
Fetch new arXiv papers for a query, skip duplicates, score relevance with Gemini against your team's interests and post the best to Slack.
Compare a candidate AsyncAPI document with the blessed baseline, alert Slack on removed channels or required fields, and publish the verdict.
Fetch customer feedback, analyze sentiment and categorize topics using OpenAI, aggregate results with DuckDB, and send a summary to Slack.
Audits Apache Avro data contracts, automatically infers schemas from raw streams, verifies bidirectional serialization, and alerts Slack on breaking drift.
Daily AWS Cost Explorer pull that compares yesterday's spend to your budget and alerts Slack on anomalies.
Audit Amazon DynamoDB ThrottledRequests via CloudWatch, detect provisioned capacity starvation, open GitHub issues, and alert Slack.
Watch a CloudWatch backlog metric and fire an EMR Serverless Spark job only when work is pending.
Run a Glue ETL job, validate the output with Athena, then cache the headline KPI in DynamoDB.
Audit an AWS Glue job run's status, alert Slack when it failed or has run far longer than expected, and optionally stop a stuck run with StopJobRun.
List every AWS MSK cluster in a region, alert Slack the moment one enters state FAILED, and classify API reachability separately from cluster health.
Extract JSON from a REST API, enrich it, and load it in parallel to Postgres and Amazon S3.
Extract data from a REST API, reshape it with Python and Polars, then run analytical SQL on it with DuckDB, all in one Kestra flow.
Runs parallel endpoint probes, aggregates batch metrics in DuckDB, scores drift in Python, and quarantines bad partitions.
Audit an Apify actor's most recent run status, alert Slack when it failed, timed out, or was aborted, and optionally launch a fresh retry run under a cost cap.
Run an Apify actor under hard cost and run caps, then branch on the returned item count so a degraded scrape pages the on-call instead of silently shipping bad data.
Run an Apify actor on a schedule, fetch its dataset, reshape the records, and bulk-load them into Postgres with cost caps and Slack alerts.
Built for Enterprises and SMBs, with strong governance, enterprise-grade security, seamless scalability, and dedicated enterprise support backed by SLAs.
