How to run dlt with Airflow (Or any other Python thing)
Blog post from dltHub
The text discusses various ways to run a Python library called dlt using Apache Airflow, a popular workflow management system. The author presents three methods: using the `PythonOperator`, `PythonVirtualenvOperator`, and `KubernetesPodOperator`. Each method has its advantages and disadvantages, including considerations such as module conflicts, resource contention, and decoupling scheduling from execution. The author concludes that the `KubernetesPodOperator` is a powerful strategy for running Airflow tasks in a Kubernetes cluster, but it requires expertise and infrastructure management. Additionally, external compute services like serverless functions and managed container services can also be used to run dlt pipelines without maintaining underlying infrastructure.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Kubernetes | 23 | 2,064 | 236 | 94 | +7% |
| Serverless | 6 | 1,024 | 191 | 85 | +26% |
| LLM | 1 | 3,669 | 412 | 154 | +40% |
| Secrets Management | 1 | 1,019 | 120 | 64 | +116% |
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