Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Dagster & Geomagical
Search
Noah Kantrowitz
February 09, 2021
Programming
0
160
Dagster & Geomagical
Noah Kantrowitz
February 09, 2021
Tweet
Share
More Decks by Noah Kantrowitz
See All by Noah Kantrowitz
What Python Can Learn From Other Languages
coderanger
0
61
What Python Can Learn From Other Languages (with notes)
coderanger
0
160
Swiss Army Django: Small Footprint ETL (with notes) - DjangoCon US
coderanger
0
220
Swiss Army Django: Small Footprint ETL - DjangoCon US
coderanger
0
59
How to look at space: PyCon AU
coderanger
0
100
Swiss Army Django: Small Footprint ETL
coderanger
0
90
Swiss Army Django: Small Footprint ETL (with notes)
coderanger
0
82
Minimum Viable Kubernetes
coderanger
0
38
Minimum Viable Kubernetes (with notes)
coderanger
0
450
Other Decks in Programming
See All in Programming
オンコール⼊⾨〜ページャーが鳴る前に、あなたが備えられること〜 / Before The Pager Rings
yktakaha4
1
770
システム成長を止めない!本番無停止テーブル移行の全貌
sakawe_ee
1
220
#kanrk08 / 公開版 PicoRubyとマイコンでの自作トレーニング計測装置を用いたワークアウトの理想と現実
bash0c7
1
900
チームのテスト力を総合的に鍛えて品質、スピード、レジリエンスを共立させる/Testing approach that improves quality, speed, and resilience
goyoki
5
1k
AIともっと楽するE2Eテスト
myohei
8
2.9k
猫と暮らす Google Nest Cam生活🐈 / WebRTC with Google Nest Cam
yutailang0119
0
160
“いい感じ“な定量評価を求めて - Four Keysとアウトカムの間の探求 -
nealle
2
11k
Advanced Micro Frontends: Multi Version/ Framework Scenarios @WAD 2025, Berlin
manfredsteyer
PRO
0
370
PipeCDのプラグイン化で目指すところ
warashi
1
290
The Evolution of Enterprise Java with Jakarta EE 11 and Beyond
ivargrimstad
0
180
おやつのお供はお決まりですか?@WWDC25 Recap -Japan-\(region).swift
shingangan
0
140
20250704_教育事業におけるアジャイルなデータ基盤構築
hanon52_
5
910
Featured
See All Featured
The Pragmatic Product Professional
lauravandoore
35
6.7k
How to Ace a Technical Interview
jacobian
278
23k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
229
22k
Code Review Best Practice
trishagee
69
19k
Facilitating Awesome Meetings
lara
54
6.5k
BBQ
matthewcrist
89
9.7k
StorybookのUI Testing Handbookを読んだ
zakiyama
30
5.9k
Typedesign – Prime Four
hannesfritz
42
2.7k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
138
34k
Chrome DevTools: State of the Union 2024 - Debugging React & Beyond
addyosmani
7
740
Principles of Awesome APIs and How to Build Them.
keavy
126
17k
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
47
9.6k
Transcript
Geomagical & Dagster Dagster Community Meeting
Noah Kantrowitz > @kantrn - coderanger.net > Principal Ops @
Geomagical > Part of the IKEA family > Augmented reality with furniture
Our Product
Starting Point > Celery & RabbitMQ > Each operation as
its own daemon > celery.canvas > Custom DAG compiler
Design Goals > Keeping most of the solid structure >
Improved DAG expressiveness > Low fixed overhead, compatible with autoscaling > More detailed tracking and metrics
Dagster > Met all our requirements for structural simplicity >
DAG compiler was a bit limited but growing fast > Highly responsive team Dagster > No execution setup that met our needs
But dagster_celery? > Solid and pipeline code commingled > Single
runtime environment > Hard to build a workflow around at scale
But dagster_k8s? > Fine for infrequent or non-customer facing tasks
> Do not put kube-apiserver in your hot path > No really, I mean it
None
Autoscaling > KEDA watching RabbitMQ > Zero-scale: only Dagit and
gRPC daemons > task_acks_late = True > worker_prefetch_multiplier = 1
Remote Solids > Independent release cycles for each Solid >
Can run multiple versions in parallel > Testing in isolation
Writing A Remote Solid app = SolidCelery('repo-something') @app.task(bind=True) def something(self,
foo: str) -> str: return f'Hello {foo}'
Proxy Solids @celery_solid(queue='repo-something') def something(context, item): output = yield {
'foo': item['bar'], } item['something'] = output yield Output(item)
Workflow > One git repo per Dagster repo > main.py
which holds "default" Pipeline > solids.py which defines proxy Solids > Misc other pipelines for testing and development
CI/CD Briefly, since this is its own rabbit hole >
Buildkite > kustomize edit set image > ArgoCD
Downsides > Slow cold start > No feedback during long
tasks > New and exciting bugs
How It's Going > Happy with overall progress > Still
dropping some tasks at load > Plan to move forward looks good
Future Plans > Async execution support > Events from solid
workers > Pipeline-level webhooks > Predictive auto-scaling? K8s Operator?
Can I Use This? Kinda sorta geomagical/dagster_geomagical
Thank You Questions?