Operationalize and Scale
AI and ML Initiatives with Astro
Accelerate operational AI with a workflow management platform that has the breadth of integrations and scalable compute power essential for delivering next-gen applications.
Build an elastic data foundation for faster development of production-ready AI and ML applications
Astro supports hand-in-hand collaboration between data engineering, data science, and machine learning teams across everything from traditional data pipelines to building AI applications.
Unify development practices
Benefit from a unified AI development environment, offering a consistent framework to streamline the path from prototype to production-ready AI.
Powerful compute capacity
Astro leads the managed-Airflow market with unmatched compute power, enabling scalable AI workloads and efficient, cost-effective operations.
Trusted AI with lineage
Gain clear visibility and transparency in data origins and transformations, enhancing the reliability of AI models and compliance readiness.
Seamless AI integrations
Validated integration with top providers simplifies AI development, allowing teams to focus on creating impactful models and applications without the challenges of interoperability.
Steven Hillion, Astronomer’s SVP of Data and AI, talks about how successful machine learning and AI initiatives come down to repeatable and reliable data processing.
Connect to the most widely-used LLM services and vector databases
Apache Airflow®, combined with a comprehensive list of integrations, offers limitless extensibility and interoperability, enabling unified automation across systems through the power of open-source development.
Astro + OpenAI Easily generate embeddings for data, a foundational step in natural language processing (NLP) with LLM-powered applications. 
Astro + OpenSearch Build solutions for distributed search applications with a flexible, scalable, and open-source framework. 
Astro + Cohere Leverage enterprise-focused LLMs to easily create NLP applications using your data. 
Astro + Weaviate Process high-dimensional vector embeddings using an open-source vector database that offers a rich set of features, exceptional scalability, and reliability. 
Astro + Pinecone Experience a highly customizable vector-based search with an easily scalable, developer-friendly and fully-managed vector database. 
Astro + pgvector Unlock powerful functionalities for working with vectors in a high-dimensional space with this open-source extension for your PostgreSQL database. 
Meet Ask Astro
Ask Astro, an LLM-powered chatbot, harnesses Airflow knowledge from various platforms to deliver Astronomer's extensive expertise on demand and serves as a starting point for operationalizing your applications.
Accelerate your AI workflow development
Discover available modules designed for easy integration with your favorite next generation AI tools.
Certified DAG Use OpenAI LLMs to Embed and Visualize Results
This DAG shows how to use the OpenAI Airflow provider to interact with the OpenAI API.
Airflow Community
Certified DAG Generate Vectors with the Airflow Weaviate Provider
This DAG runs a simple MLOps pipeline to import data, generate vectors, and query the vectors.
Airflow Community
Certified DAG Query Vectors with Pinecone and Airflow
This DAG uses the Pinecone Airflow Provider to import data, generate vectors, then query based on user-provided inputs.
Airflow Community
The world of LLMs is moving fast, so it's important that developers build on flexible platforms that can adapt. Using Apache Airflow® and Weaviate together provides a flexible, open source foundation for building and scaling AI applications.
Bob van Luijt
CEO & Co-Founder
With Astro by Astronomer, we’ve not only streamlined our MLOps but also future-proofed our data operations for unprecedented scale and reliability. Its user-friendly interface, combined with its cost-effectiveness, positions us at the forefront of innovation.
Andrew Ward
VP, Product and Data
The ease of configuration adjustments on Astronomer meant that even if there were potential missteps or heavy reliance on workers, the team could swiftly react and rectify. This confidence in our operations led to a shift in how we’re using Airflow today and allowing us to explore new cases.
Juan Honorato
Chief Technology Officer
Instead of running each model one at a time, Cosmos lets me run everything in parallel where possible, which saves us hours.
Chris Brundage
Data Engineer
Astro emerged as a better fit for our long-term goals, offering the kind of scalable environment and dedicated support we needed. The migration to Astro was streamlined and completed within a two-week sprint, significantly enhancing our data orchestration capabilities.
John Marriott
Manager, Data Platform Team
Using Astro's Apache Airflow® offering on Azure has modernized our data operations. Their best-in-class SLAs, multi-environment deployments, and intuitive dashboards have streamlined our processes, ensuring we can manage our critical pipelines.
Kevin Schmidt
Sr Manager, Data Engineering
The world of LLMs is moving fast, so it's important that developers build on flexible platforms that can adapt. Using Apache Airflow® and Weaviate together provides a flexible, open source foundation for building and scaling AI applications.
Bob van Luijt
CEO & Co-Founder
With Astro by Astronomer, we’ve not only streamlined our MLOps but also future-proofed our data operations for unprecedented scale and reliability. Its user-friendly interface, combined with its cost-effectiveness, positions us at the forefront of innovation.
Andrew Ward
VP, Product and Data
The ease of configuration adjustments on Astronomer meant that even if there were potential missteps or heavy reliance on workers, the team could swiftly react and rectify. This confidence in our operations led to a shift in how we’re using Airflow today and allowing us to explore new cases.
Juan Honorato
Chief Technology Officer
Instead of running each model one at a time, Cosmos lets me run everything in parallel where possible, which saves us hours.
Chris Brundage
Data Engineer
Astro emerged as a better fit for our long-term goals, offering the kind of scalable environment and dedicated support we needed. The migration to Astro was streamlined and completed within a two-week sprint, significantly enhancing our data orchestration capabilities.
John Marriott
Manager, Data Platform Team
Using Astro's Apache Airflow® offering on Azure has modernized our data operations. Their best-in-class SLAs, multi-environment deployments, and intuitive dashboards have streamlined our processes, ensuring we can manage our critical pipelines.
Kevin Schmidt
Sr Manager, Data Engineering
We no longer spend huge chunks of time fixing outages. Our engineering teams can focus on product engineering, our analytic engineers & data scientists can focus on getting stakeholders the analytics they need.
Nick Wilson
Sr. Manager, Platform Team
With Astro, it's incredibly easy to set up new pipelines; I can create 10 new ones a day if needed. This agility has allowed us to scale up to the point where we needed to create specific deployments for larger teams to better manage and measure their usage.
Yohai Vidergor
VP of Global Data
With Astronomer, we've seen our end-to-end nightly execution time drop nearly 20%. Having Astronomer manage orchestration in one central place gives the application and support teams a lot more control and visibility into our running processes.
Kevin Suchy
Solutions Architect
Data Scientist using Astronomer for custom ETLs and ML
I like that it is flexible, well documented, has good support. Its UI is pleasing too. It's fast, allows to schedule lots differents jobs by nature (data engineering, ML models, MLOps, etc). It's overall a fantastic orchestration service.
Great product and collaboration
The experience of using astronomer for the migration of existing DAGs and new developments has been great, and all positive. The team is supportive and very knowledgeable.
Excellent Airflow as a Service Platform
With Astronomer we don't need to worry about the infrastructure, everything is abstracted to us, we just need to click a few times to implement a new deployment (very easy) access the Astronomer UI, and start doing things.
Best way to take the pain out of Airflow
Astronomer is the only feasible managed service currently available for Airflow. It's the first managed service I've used that does not entail a surprising number of performance bugs even when used only as an orchestration engine (which generally deferable functionality has resolved), and the only approach I would recommend if you want to also use it as an execution engine in its own right.
We no longer spend huge chunks of time fixing outages. Our engineering teams can focus on product engineering, our analytic engineers & data scientists can focus on getting stakeholders the analytics they need.
Nick Wilson
Sr. Manager, Platform Team
With Astro, it's incredibly easy to set up new pipelines; I can create 10 new ones a day if needed. This agility has allowed us to scale up to the point where we needed to create specific deployments for larger teams to better manage and measure their usage.
Yohai Vidergor
VP of Global Data
With Astronomer, we've seen our end-to-end nightly execution time drop nearly 20%. Having Astronomer manage orchestration in one central place gives the application and support teams a lot more control and visibility into our running processes.
Kevin Suchy
Solutions Architect
Data Scientist using Astronomer for custom ETLs and ML
I like that it is flexible, well documented, has good support. Its UI is pleasing too. It's fast, allows to schedule lots differents jobs by nature (data engineering, ML models, MLOps, etc). It's overall a fantastic orchestration service.
Great product and collaboration
The experience of using astronomer for the migration of existing DAGs and new developments has been great, and all positive. The team is supportive and very knowledgeable.
Excellent Airflow as a Service Platform
With Astronomer we don't need to worry about the infrastructure, everything is abstracted to us, we just need to click a few times to implement a new deployment (very easy) access the Astronomer UI, and start doing things.
Best way to take the pain out of Airflow
Astronomer is the only feasible managed service currently available for Airflow. It's the first managed service I've used that does not entail a surprising number of performance bugs even when used only as an orchestration engine (which generally deferable functionality has resolved), and the only approach I would recommend if you want to also use it as an execution engine in its own right.
Resources and Insights
