Re: Airflow - High Availability and Scale Up vs Scale Out
Let us know after trying the beefy box approach about your findings.
On 08/06/2018, 12:24, "Sam Sen" <sxs@xxxxxxxxxxxxxxxx> wrote:
We are facing this now. We have tried the celeryexecutor and it adds more
moving parts. While we have no thrown out this idea, we are going to give
one big beefy box a try.
To handle the HA side of things, we are putting the server in an
auto-scaling group (we use AWS) with a min and Max of 1 server. We deploy
from an AMI that has airflow baked in and we point the DB config to an RDS
using service discovery (consul).
As for the dag code, we can either bake it into the AMI as well or install
it on bootup. We haven't decided what to do for this but either way, we
realize it could take a few minutes to fully recover in the event of a
The other option is to have a standby server if using celery isn't ideal.
With that, I have tried using Hashicorp nomad to handle the services. In my
limited trial, it did what we wanted but we need more time to test.
On Fri, Jun 8, 2018, 4:23 AM Naik Kaxil <k.naik@xxxxxxxxx> wrote:
> Hi guys,
> I have 2 specific questions for the guys using Airflow in production?
> 1. How have you achieved High availability? How does the architecture
> look like? Do you replicate the master node as well?
> 2. Scale Up vs Scale Out?
> 1. What is the preferred approach you take? 1 beefy Airflow VM with
> Worker, Scheduler and Webserver using Local Executor or a cluster with
> multiple workers using Celery Executor.
> I think this thread should help others as well with similar question.
> Kaxil Naik
> Data Reply
> 2nd Floor, Nova South
> 160 Victoria Street, Westminster
> London SW1E 5LB - UK
> phone: +44 (0)20 7730 6000
> [image: Data Reply]
2nd Floor, Nova South
160 Victoria Street, Westminster
London SW1E 5LB - UK
phone: +44 (0)20 7730 6000