+1. And it should be paired with the official image we have work in progress on. I looked a lot at the Astronomer's image while preparing my draft and we can make any adjustments needed to make it works with the helm chart - and I am super happy to collaborate on that.
PR here: https://github.com/apache/airflow/pull/7832 J. On Tue, Mar 24, 2020 at 3:15 PM Kaxil Naik <kaxiln...@gmail.com> wrote: > @Tomasz Urbaszek <tomasz.urbas...@polidea.com> : > Helm Chart Link: https://github.com/astronomer/airflow-chart > > On Tue, Mar 24, 2020 at 2:13 PM Tomasz Urbaszek <turbas...@apache.org> > wrote: > > > An official helm chart is something our community needs! Using your > > chart as the official makes a lot of sens to me because as you > > mentioned - it's battle tested. > > > > One question: what Airflow image do you use? Also, would you mind > > sharing a link to the chart? > > > > Tomek > > > > > > On Tue, Mar 24, 2020 at 2:07 PM Greg Neiheisel > > <g...@astronomer.io.invalid> wrote: > > > > > > Hey everyone, > > > > > > Over the past few years at Astronomer, we’ve created, managed, and > > hardened > > > a production-ready Helm Chart for Airflow ( > > > https://github.com/astronomer/airflow-chart) that is being used by > both > > our > > > SaaS and Enterprise customers. This chart is battle-tested and running > > > hundreds of Airflow deployments of varying sizes and runtime > > environments. > > > It’s been built up to encapsulate the issues that Airflow users run > into > > in > > > the real world. > > > > > > While this chart was originally developed internally for our Astronomer > > > Platform, we’ve recently decoupled the chart from the rest of our > > platform > > > to make it usable by the greater Airflow community. With these changes > in > > > mind, we want to start a conversation about donating this chart to the > > > Airflow community. > > > > > > Some of the main features of the chart are: > > > > > > - It works out of the box. With zero configuration, a user will get > a > > > postgres database, a default user and the KubernetesExecutor ready > to > > run > > > DAGs. > > > - Support for Local, Celery (w/ optional KEDA autoscaling) and > > > Kubernetes executors. > > > > > > Support for optional pgbouncer. We use this to share a configurable > > > connection pool size per deployment. Useful for limiting connections to > > the > > > metadata database. > > > > > > - Airflow migration support. A user can push a newer version of > > Airflow > > > into an existing release and migrations will automatically run > > cleanly. > > > - Prometheus support. Optionally install and configure a > > statsd-exporter > > > to ingest Airflow metrics and expose them to Prometheus > automatically. > > > - Resource control. Optionally control the ResourceQuotas and > > > LimitRanges for each deployment so that no deployment can overload a > > > cluster. > > > - Simple optional Elasticsearch support. > > > - Optional namespace cleanup. Sometimes KubernetesExecutor and > > > KubernetesPodOperator pods fail for reasons other than the actual > > task. > > > This feature helps keep things clean in Kubernetes. > > > - Support for running locally in KIND (Kubernetes in Docker). > > > - Automatically tested across many Kubernetes versions with Helm 2 > > and 3 > > > support. > > > > > > We’ve found that the cleanest and most reliable way to deploy DAGs to > > > Kubernetes and manage them at scale is to package them into the actual > > > docker image, so we have geared this chart towards that method of > > > operation, though adding other methods should be straightforward. > > > > > > We would love thoughts from the community and would love to see this > > chart > > > help others to get up and running on Kubernetes! > > > > > > -- > > > *Greg Neiheisel* / Chief Architect Astronomer.io > > > -- Jarek Potiuk Polidea <https://www.polidea.com/> | Principal Software Engineer M: +48 660 796 129 <+48660796129> [image: Polidea] <https://www.polidea.com/>
