Must have
Installation requirements
- A supported Python environment for the selected Airflow release.
- A metadata database compatible with the selected release.
- An executor and worker arrangement that can run the intended tasks.
Application hosting
Apache Airflow schedules and monitors workflows made of dependent tasks. It suits data pipelines and recurring jobs where the order of work, retries and run history matter. Workflows are defined in Python, and the web interface helps operators follow each run. Airflow coordinates those tasks; it does not remove the compute or service costs of the work they perform.
Requirements last checked against the project's documentation.
A sensible first server for Apache Airflow is 2 vCPU, 8 GB RAM and 40 GB of storage. The cheapest listed plan that fits is OVHcloud VPS-2 (US) at $8.50/month.
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See plansMust have
Recommended
Airflow recommends at least 4 GB of memory, with actual needs depending on deployment. Treat that as a platform starting point, not capacity for every task. Worker concurrency and task memory can dominate the total.
Where to start
Airflow's Docker Compose guide says to give Docker at least 4 GB of memory, ideally 8 GB. The vCPU count and disk are our estimates.
Our shortlist
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Deploy with
The host must provide
Storage
Preserve workflow code, configuration and metadata database backups. Task logs and output datasets need their own storage and retention policy; the metadata database is not a copy of every file produced by a workflow.
Step by step
Choose the Airflow and Python versions together and install with the matching constraints file.
Official instructionsConfigure the metadata database and run the required components separately instead of relying on the local standalone quick start.
Official instructionsChoose the executor, set concurrency and retries, and run a small workflow before scheduling important jobs.
Official instructionsSecurity
Cost
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