Should we use managed Airflow or self-host?

Managed services (AWS MWAA, Cloud Composer, Astronomer) reduce operational burden. Self-hosting gives more control. We help choose based on your team size and requirements.

Can Airflow handle real-time data?

Airflow is designed for batch workflows. For real-time streaming, we combine Airflow with tools like Apache Kafka or use alternative orchestrators.

How do you handle DAG testing?

We implement unit tests for operators, integration tests for DAGs, and CI/CD pipelines for automated DAG validation before deployment.

Orchestrate Data Workflows With Apache Airflow

DAG-based pipelines, custom operators, and enterprise scheduling — Bookuvai builds production-grade Airflow solutions.

Platform: Apache Airflow (Data Orchestration)

Apache Airflow is the industry-standard platform for authoring, scheduling, and monitoring data workflows. Bookuvai builds Airflow DAGs, custom operators, and deployment infrastructure for ETL pipelines, data warehouse management, and ML workflow orchestration.

What We Build

ETL Pipelines: Scheduled data extraction, transformation, and loading DAGs with monitoring and alerting.
Custom Operators: Custom Airflow operators and hooks for proprietary systems, APIs, and data sources.
Infrastructure Setup: Airflow deployment on Kubernetes, AWS MWAA, or GCP Cloud Composer with scaling and monitoring.
Migration: Migrate existing cron jobs, scripts, and legacy pipelines to Airflow with proper error handling.

Integration Capabilities

Provider Packages: Hundreds of pre-built operators for AWS, GCP, Azure, databases, and SaaS tools.
Custom Operators: Build Python-based custom operators for any system with configurable parameters and connections.
Managed Services: Deploy on AWS MWAA, GCP Cloud Composer, or Astronomer for managed Airflow infrastructure.
Monitoring: Task-level monitoring with SLA alerts, failure callbacks, and integration with PagerDuty and Slack.

Typical Projects

Data Warehouse Pipeline: Multi-source ETL pipeline feeding Snowflake/Redshift with incremental loads and data quality checks. (40-80, $80-$160)
Custom Operator Suite: Set of custom operators for proprietary APIs and internal systems with connection management. (20-40, $40-$80)
MWAA/Composer Setup: Managed Airflow setup with CI/CD pipeline, DAG deployment, and monitoring configuration. (15-30, $30-$60)

Frequently Asked Questions

Should we use managed Airflow or self-host?: Managed services (AWS MWAA, Cloud Composer, Astronomer) reduce operational burden. Self-hosting gives more control. We help choose based on your team size and requirements.
Can Airflow handle real-time data?: Airflow is designed for batch workflows. For real-time streaming, we combine Airflow with tools like Apache Kafka or use alternative orchestrators.
How do you handle DAG testing?: We implement unit tests for operators, integration tests for DAGs, and CI/CD pipelines for automated DAG validation before deployment.