Apache Airflow & Apache Kafka
Event-driven workflow automation with Apache Airflow and Kafka
We are the leader in Apache Airflow. TrizenAI designs, builds and operates event-driven workflows on Apache Airflow and Apache Kafka that react to business events in real time, recover from failure and tell you when they need a person.
Why TrizenAI
The leader in Apache Airflow, now event-driven
Scheduled batch jobs leave your business waiting hours for data and decisions. We pair Apache Airflow, the industry standard for workflow orchestration, with Apache Kafka for real-time events, so your workflows start the moment something happens.
Airflow at the core
Airflow 3 migrations, platform engineering and 24/7 operations on Amazon MWAA, Google Cloud Composer, Astronomer and Kubernetes.
Kafka for real-time events
Hardened Apache Kafka clusters with schema registry, data contracts and multi-AZ replication, so events arrive once and in order.
Event-driven scheduling
Airflow assets and event-driven triggers start workflows the moment data lands or a business event fires, instead of waiting on cron.
Operated, not just delivered
Run history, lineage, SLO alerts and on-call support, so failures are caught and fixed before the business notices.
Reference architecture
How Airflow and Kafka work together
- 1
Kafka captures the event
Orders, payments, sensor readings and app activity are published to Kafka topics as they happen.
- 2
Airflow reacts
Event-driven DAGs listen for those events and start the right workflow immediately, with retries and timeouts built in.
- 3
Work is orchestrated end to end
Airflow coordinates the pipelines, services, AI models and human approvals each workflow needs, in the right order.
- 4
Results flow back
Outcomes are written to your warehouse, apps and Kafka topics, with every run logged, observable and replayable.
What event-driven automation does for you
Real-time data pipelines
Stream changes from operational databases through Kafka and land them in the warehouse or lakehouse within minutes.
Order and payment processing
Trigger fulfilment, fraud checks, invoicing and notifications the moment an order or payment event arrives.
AI and ML workflows
Refresh embeddings, retrain models and run batch inference when new data arrives, with every model call auditable.
System integration
Connect ERP, CRM and SaaS platforms through events instead of nightly exports and manual re-keying.
Looking beyond Airflow and Kafka? See our full workflow automation and data orchestration services, including AWS Step Functions and Azure Durable Functions.
How we deliver
- 1
Assess: review your current Airflow, Kafka and scheduling estate and find the workflows worth making event-driven.
- 2
Design: define events, topics, data contracts and DAG patterns, with failure paths designed up front.
- 3
Build: deliver workflows as code through CI/CD, tested and idempotent so every task can be re-run safely.
- 4
Run: operate the platform with monitoring, SLOs and upgrades, or hand it over to your team with runbooks.
FAQs
Why use Apache Airflow and Kafka together?
Kafka moves events reliably and at high volume; Airflow orchestrates the multi-step work those events should trigger. Together they give you real-time reaction with retries, dependencies and a full audit trail.
Can Airflow really be event-driven?
Yes. Airflow assets and event-driven scheduling let DAGs start when data or an external event arrives, rather than on a fixed timetable.
Do you work with managed Airflow services?
Yes. We build and operate Airflow on Amazon MWAA, Google Cloud Composer, Astronomer and self-managed Kubernetes.
We already run Airflow. Where do we start?
With an Airflow health check: we review your DAGs, infrastructure and upgrade path, then identify which workflows gain most from event-driven triggers.
Make your workflows react in real time
Start with an Airflow health check and leave with a clear path to event-driven automation on Airflow and Kafka.
Book an Airflow health check