Self-Managed Deployment of Kafka & Airflow on Linode Kubernetes

The Problem Statement

Managed services like Confluent Kafka and Astronomer (Airflow SaaS) incurred substantial monthly expenses.

Performance bottlenecks occurred during peak traffic, with the need for a more dynamic and scalable setup.

Restrictive customizations created reliance on external vendors for infrastructure changes and updates.

Existing setups lacked robust monitoring and alerting capabilities, impeding real-time insights and metrics analysis.

Migrated from Confluent Kafka to a self-managed Kafka setup on Linode Kubernetes Engine.

Transitioned from Astronomer’s Airflow SaaS to an open-source Airflow deployment on Akamai Cloud.

Utilized tools like Kafka UI, Terraform, Datadog, KEDA, Redis, and GitHub Actions for automation and monitoring.

Implemented continuous deployment pipelines with GitHub Actions and integrated Datadog for real-time monitoring and alerting.

Successfully migrated 200 DAGs to an open-source Airflow setup.

Achieved $10,000 in monthly cost savings.

Ensured high availability (HA) setups for both Kafka and Airflow.

Established a robust observability framework using Datadog, enabling proactive issue resolution and system health monitoring.

Experience Faster Time-to-Market