Introducing Astro IDE: Ship Apache Airflow DAGs 10x Faster
Today we're announcing Astro IDE, the first AI-powered IDE purpose-built for Apache Airflow. In this post I'll explain what Astro IDE is, why your data engineering team should take a look at it, and how you can start using it to transform your DAG development workflow.
The Data Engineering Resource Crunch
High-quality data demand is exploding, but data engineering teams can't scale fast enough to meet it. According to Gartner®, 62% of application development teams avoid working with the data group because they perceive it as too slow (Gartner, “Achieve Continuous Delivery With Database DevOps,” Bill Holz, Lyn Robison, August 2025). In addition, according to the 2025 State of Airflow report, 34.2% of data teams cite people-resource shortages as their #1 obstacle to success , as organizations increasingly recognize data as a strategic asset.
Why does this matter? It's because the business depends on these constrained teams more than ever. In the same survey, 90% say Airflow is business-critical, with nearly half running mission-critical workloads on it. That's up from 78% in our 2023 survey, showing how rapidly data orchestration has become essential to business operations.
The resource equation simply doesn't add up: teams are operating under hiring constraints while facing exponentially growing backlogs and mounting pressure to deliver data products faster. General-purpose code assistants and AI coding tools promised to bridge this gap, but they often make things worse—generating buggy Airflow code that requires extensive refactoring by the same engineers who are already stretched thin. These tools don't understand your data environment, Airflow's nuances, version-specific features, or production best practices, creating more work instead of reducing it.
Today, we're solving this bottleneck with a purpose-built solution that understands both your code and your constraints.
Meet Astro AI: Your Context-Aware Programming Partner
Before we dive into Astro IDE, let's talk about what powers it. We've built Astro AI—our intelligent assistant that can generate, refactor, and explain Airflow code by understanding your specific workspace context. Unlike general-purpose coding assistants that work in isolation, Astro AI has read access to your Astro environment, codebase and leverages the patterns, conventions, and metadata you've already established. This contextual awareness, or private data, means every suggestion is tailored to your Airflow environment—not generic boilerplate that ignores how your data organization actually works.
Astro IDE is one of the first interfaces that lets you harness this domain expertise and contextual intelligence directly in your development workflow.
Meet Astro IDE: the only AI-powered IDE built for Apache Airflow
Astro IDE is the first integrated development environment purpose-built for Apache Airflow, combining our domain-trained AI pair-programmer with in-browser testing and one-click deploys. When you grant it the appropriate permissions, Astro IDE analyzes your GitHub repo patterns, and understands your Astro environment configuration—using this context to generate accurate, production-ready DAGs that actually run first time.
Unlike generic code editors that treat Airflow like any other Python framework, Astro IDE speaks your language. It knows when to use TaskFlow API versus traditional operators, understands cross-DAG dependencies, and follows your team's established patterns for connection management and error handling.
The result? Data engineers ship DAGs 10x faster. New hires become productive on day one. And teams finally break through the data engineering bottleneck by amplifying their existing expertise rather than requiring additional resources.
Learn more about getting started with Astro IDE →
Three critical capabilities that supercharge Airflow DAG development
1. AI that actually understands Airflow
Generic AI coding tools don't understand your data or Airflow's nuances. They generate bloated code, outdated operators, and ignore version-specific features—forcing your data engineers to spend hours debugging and refactoring instead of building new capabilities. The result? What should accelerate development actually slows it down.
Astro IDE takes a fundamentally different approach. It uses Astro AI, an intelligent assistant that can generate, refactor, and explain Airflow code based on your specific context. You maintain full control—accepting or rejecting every change Astro AI proposes.
Here's what makes it different: Astro AI has read access to your codebase stored in the IDE and understands broader workspace context, has access to your connections, including project files you've uploaded or built over time, the patterns and naming conventions your team has adopted, and workspace metadata such as assets tracked in Astro Observe's Asset Catalog or tables linked in Snowflake or Databricks.
Whether you're migrating DAGs from Airflow 2 to 3, implementing custom operators, or orchestrating dbt models with Cosmos, Astro IDE produces clean, efficient code that follows your established patterns. This enables higher reliability with better performance and lower resource consumption—critical factors when you're running mission-critical workloads at scale.
"Astro IDE generated code that was high-quality and production-ready from the start. Compared to generic AI tools, Astro IDE was miles ahead, with a deeper understanding of Airflow and the ability to ask the right questions. Even with our most complex DAGs, it was able to explain, transform, and adapt them with ease."
Tim Handley, Chief Product & Technology Officer at Welbee
Learn more about Astro IDE capabilities →
2. Zero-Setup Testing and Deployment in Your Browser
Data engineers spend hours configuring local development setups that emulate but never quite match production. They wrestle with insecure connection management that exposes credentials. They need to run local environments using Docker or Podman so they can test and deploy their Airflow DAGs. They hunt down missing dependencies that work in one environment but fail in another. They battle environment drift where local configurations slowly diverge from what's actually running in production. This entire setup process becomes a massive time sink that adds zero value to your data products.
Astro IDE eliminates the need for a local Airflow setup for testing and deployment entirely. Test DAGs instantly in your browser using ephemeral Astro deployments that match your production environment. See task logs, catch import errors, visualize DAG structure—all without touching Docker or Podman locally. And deploy your Airflow DAGs directly to an Astro deployment or by committing your changes to a branch.
"Astro IDE has made onboarding effortless. New engineers can start building and testing DAGs immediately without the hurdles of configuring local environments."
Javier Jimenez Gil, Data Engineer, SEAT
Learn about in-browser testing →
3. Seamless Path from Development to Production
Context switching kills productivity. Engineers bounce between editors, terminals, Git clients, and deployment tools. Every transition or handoff becomes an opportunity for mistakes to creep in, whether it's a misconfigured environment variable or a deployment to the wrong branch.
Astro IDE integrates your entire workflow into a single, cohesive experience. You can import code directly from GitHub without leaving your browser, collaborate on changes with your team in real-time, and deploy to Astro with one click or push to specific branches for CI/CD pipelines. The AI even writes your commit messages for you, with your approval—ensuring consistent documentation standards while eliminating another small friction point that slows down delivery.
Deploy code from the Astro IDE →
This integrated approach dramatically boosts the productivity of data teams.
"With Astro IDE, development that used to take us an hour now takes just 15 minutes. It’s dramatically accelerating how quickly we can build and test new data pipelines."
Javier Jimenez Gil, Data Engineer, SEAT
Built for Teams That Need to Scale
Astro IDE is already transforming how data teams work. Early adopters from SEAT, Texas Rangers, Welbee, Arch Insurance, SecurityHQ, and DAT Freight & Analytics report:
- 10x faster DAG delivery from concept to production
- 90% reduction in onboarding time for new engineers
- Dramatic improvement in code quality with built-in best practices
Astro IDE particularly shines when you're updating and refactoring existing DAGs to follow current best practices, creating new pipelines with accurate operator recommendations, and understanding unfamiliar codebases during team collaboration. It excels at building custom operators with AI assistance that understands your specific requirements. You'll also find it invaluable for orchestrating dbt models using Cosmos, as well as building event-driven workflows that respond to real-time business events.
Join the Future of Airflow Development
Astro IDE enters public preview on September 17, 2025 with:
- $10 free monthly AI credits per organization
- Additional usage burns down existing Astro credits. $3.75/million tokens for Input messages and $18.75 /million tokens for Output messages
- Full GitHub integration
- Support for Airflow 2.x and 3.x
For Astro Customers: Access Astro IDE directly through your Astro workspace starting September 17. Your $10 in monthly AI usage credits will be automatically available.
New to Astronomer? Start your free Astro trial today and experience how Astro IDE transforms Airflow development. Your trial includes full access to Astro IDE, along with our complete DataOps platform.
New Users: Start Your Free Trial →
Astro IDE is included with your Astro subscription. Ephemeral deployments are priced at standard Small Deployment rates for your plan. See pricing details for more information.
We know you'll have questions about what models we are using, where they are hosted, and what happens to your data – environment, prompts, DAGs. This and more are answered in our Astro IDE Security and Data Privacy whitepaper.
Ready to dive deeper? Check out the Astro IDE documentation for comprehensive setup guides, tutorials, and best practices.
