01 — ACT
From data exploration to migration
Run Otto in your terminal or directly in Astro. Otto has access to your instance, your warehouses and your deployment history.
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GeezerVison is showing www.astronomer.io — Astronomer: The Best Place to Run Apache Airflow® ORCHESTRATION FOR DATA AND AI.Move data and agentic workflows from prototype to production. BUILT WITH         Featured Content   Booking.com delivers travelers a connected trip with data and AIRead Case Study →  Janus Henderson Investors built self-healing pipelines with Astro & Otto.Read Case Study → The Astro Runtime: Airflow re-engineered for speed and scaleWe rebuilt Airflow's scheduler, executor, runtime, and infrastructure for greater scale, lower latency, and faster recovery. Your DAGs stay the same, while Astro runs low-latency pipelines, AI workflows, and hundreds of thousands of tasks at once.
Coordination Airflow API server1-10 replicas Airflow triggererup to 8 replicas Airflow Dag processor2 replicas with HA Execution— one executor per deployment Airflow Celery executorautoscaled workers Airflow Kubernetes executorone pod per task Platform Astro Scheduler 01 / 05 Event-driven scheduling that stays fastThe Astro Scheduler reacts to new work as it arrives instead of waiting for a polling cycle. Task starts stay fast as trigger volume and concurrency grow. Run event-driven pipelines and AI workflows alongside ETL, ML, and batch workloads—all on one Airflow platform. p95 task start latency: Celery has 23.582 seconds of task lag at 50,000 concurrent tasks; Astro at 100,000 takes 228 milliseconds; and Astro at 300,000 takes 294 milliseconds. p95 task start latency under load Celery @ 50k concurrent tasks23.582s Astro @ 100k concurrent tasks228ms Astro @ 300k concurrent tasks294ms Introducing Otto THE ONLY AGENT BUILT FOR APACHE AIRFLOW.Astronomer’s Airflow expertise, plus your team’s conventions. Otto writes Dags, investigates failures, and plans upgrades grounded in both. Learn More02 — REASON Otto reasons with your contextOtto plans, executes, and verifies its work against public Airflow knowledge, Astronomer's proprietary expertise, and your private memory. 03 — LEARN Every action sharpens the loopEvery fix, pattern, and correction feeds back into your private memory. The more your team uses Otto, the smarter it gets.  Raise the ceiling of data engineering with Airflow you never have to babysitYou write DAGs, Astro runs them reliably at any scale. No Kubernetes expertise required. No ops burden. Just Airflow that works the way it should. $ brew install astro ✓ Successfully installed astro-cli v1.39.0 $ astro dev init --from-template etl Initializing Astro project...
Run `astro dev start` to run Airflow locally $ astro deploy
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