Just wondering if there is any approximate number on concurrent tasks a
scheduler can run on say 16 GB RAM and 8 core machine.
If its already been done that would be useful.
We did some benchmarking with local executor and observed that each
TaskInstance was taking ~100MB of memory so we could only run ~130 concurrent
tasks on 16 GB RAM and 8 core machine.
On 2018/04/12 16:32:37, Ry Walker <r...@astronomer.io> wrote:
> Hi Raman -
> First, we’d be happy to help you test this out with Airflow. Or you could
> do it yourself by using http://open.astronomer.io/airflow/ (w/ Docker
> Engine + Docker Compose) to quickly spin up a test environment. Everything
> is hooked to Prometheus/Grafana to monitor how the system reacts to your
> CEO, Astronomer
> On April 12, 2018 at 12:23:46 PM, ramandu...@gmail.com (ramandu...@gmail.com)
> Hi All,
> We have requirement to run 10k(s) of concurrent tasks. We are exploring
> Airflow's Celery Executor for same. Horizontally Scaling of worker nodes
> seem possible but it can only have one active scheduler.
> So will Airflow scheduler be able to handle these many concurrent tasks.
> Is there any benchmarking number around airflow scheduler's scalability.