The text discusses the challenges faced by enterprise data teams using Apache Airflow for orchestrating workflows at scale, highlighting the trade-offs between reliability and performance with existing executors like Celery and Kubernetes. These traditional executors introduce complexities such as task loss during restarts and latency issues, prompting the development of the Astro Executor by Astronomer. Purpose-built for Airflow 3, the Astro Executor addresses these challenges by enhancing efficiency and resilience without compromising on performance, offering a 70% improvement in task concurrency and maintaining zero task failures under stress. It leverages an agent-based architecture that eliminates external broker dependencies, providing enhanced observability, predictable scaling, and direct API communication, which results in better throughput, reliability, and reduced operational costs. The Astro Executor also supports remote execution capabilities, allowing tasks to run in separate environments from the scheduler, which is beneficial for workload isolation, multi-cloud orchestration, and compliance requirements. Available exclusively to Astro customers, the Astro Executor is designed to work seamlessly with existing workflows on Airflow 3 deployments.