Build, run, and govern across your entire organization.
Agentic AI under the same controls.
Kestra scales because it is designed for cross-team orchestration from day one.
Standardize Terraform, Ansible, CI/CD and operational workflows across hybrid and air-gapped environments.
faster infrastructure delivery
lower legacy tooling cost
Run ingestion, transformations, dbt, Airbyte, Spark and quality checks in one workflow engine.
Faster Pipeline Delivery
Fewer Manual backfills
Agents, RAG pipelines, evaluation, publishing, retraining all orchestrated with governance and observability.
less pipeline maintenance
faster AI delivery cycles
Write workflows in YAML. Version them. Review them. Ship them.
Cloud, data, infra, CI/CD, ITSM, messaging. Plug into your entire stack.
2,600+ plugins
Cron, events, webhooks, messages. One engine to run them all.
Retries, timeouts, SLAs, RBAC, audit logs. SOC 2, Built to run in production.
Run tasks in Python, Bash, Node.js, Go, or containers. No refactoring required.
Empower every team member to collaborate from a single tool—code for developers, UI for everyone else, all in sync.
Copilot for speed, agents for action. Create, iterate, and automate workflows with an AI native platform.
Trigger executions, manage workflows and resources through the API, and roll out updates safely with Git-driven CI/CD pipelines.
Kestra integrates with your existing cloud, data, infrastructure, and SaaS tools.
With 2,600+ plugins, you can orchestrate everything without building custom glue code.
We processed billions of rows and thousands of weekly API pulls in under 3 months. For the first time, our analysts aren't waiting for engineering—they're building the workflows themselves.
Self-host on Docker or Kubernetes. Free Forever
Built for critical environments.
SSO, RBAC, audit logs, multi-tenancy. Isolated workers and dedicated task runners.
Hybrid environments: Cloud, On-Prem, Air-Gapped.
SLA-backed support and a dedicated customer success program.
Managed platform, production-ready, scalable. Fastest time to value.
Jump-start your workflows with a growing library of workflow templates
Fetch the requested vector ids, delete them, fetch again to prove absence, and post a before-and-after audit message to Slack.
Download a JSON export of embeddings, reshape it into Pinecone's vector format with Python, upsert the file in one call, and report the count to Slack.
Detect PostgreSQL lock conflicts and cascading uncommitted blockers via pg_locks, alerting DBAs on Slack before connections exhaust.
Clear every vector in a stale Pinecone namespace with one deleteAll call, verify with a stats readback, and confirm the purge in Discord.
Query a Pinecone index by an existing vector's id, pull the top five neighbors with metadata, and post the match count to Discord for retrieval QA.
Count recent outbound Plivo SMS by final state every hour and alert Slack when messages start failing or going undelivered, with the top error code.
SCD Type 2 customer dimension in Postgres, with quarantine and Slack only on real changes.
Join features to labels as they were known at each label's cutoff with a DuckDB ASOF join, audit the set for future rows and correlation lift, then publish it or block it.
Create a Pinecone serverless index with a fixed dimension, cloud, and region, verify it with a stats readback, and confirm the bootstrap in Slack.
Continuously audit PocketBase backend health, detect SQLite database lock contention and collection drift, and alert on Slack.
A monthly flow lists Pipedrive persons, counts records missing emails or owners in Python, and posts the hygiene metrics to Discord.
Check the exact versions you pin on PyPI, npm and crates.io every day and alert when a maintainer yanks or deprecates one, with the reason and the latest release.
Compare every phpIPAM subnet's VLAN plus VRF assignment against a declared design, correct the drift behind an approval gate, then re-read phpIPAM to prove it landed.
Daily and on-demand PostgreSQL backup pipeline using pg_dump and gzip, streaming to Amazon S3 with size verification and Slack alerting.
A webhook fires on won deals, fetches the full record with deals.Get, celebrates in Slack, and marks the kickoff point for provisioning subflows.
Check Postgres connection usage versus max_connections every 5 minutes and alert Slack before pools exhaust.
Drop a recording into S3 to transcribe it locally with Whisper, draft show notes and chapters with an LLM, approve them, and publish the audio and a validated RSS feed.
Compare a PostgreSQL source and Debezium replica, row by row. Block cutover when the replica has missing, extra, or changed records.
Ingest raw files, run streaming LazyFrame transformations with Polars, validate schema rules, and sink partitioned Parquet with Slack alerts.
After an OS or ICU upgrade, find the PostgreSQL indexes built with the old text sort rules, rebuild them after approval, then refresh the collation version.
Kestra gives you fewer tools to maintain, fewer scripts to debug, fewer dependencies between teams, and one place to see what’s running
across your company.
