6aabd9a86e
Local caching is now default strategy when building the Production image. You can still change it to pulled - similar to CI builds by providing the right build flag and this is what is used in CI by default. The flags in Breeze are now updated to be more eplanatory and friendly (build-cache-*) and a flag for "disabled" cache option is added as well. Also the Dockerfile and Dockerfile.ci files are not needed any more in the docker context. They used to be needed when we built the Kubernetes image in the container, but since we are now using production image directly - we do not need them any nmore. Combining setting the default strategy to local and removing the Dockerfile from the context has the nice effect that you can iterate much faster on the Production image without triggering rebuilds of half of the docker image as soon as the Dockerfile changes. |
||
|---|---|---|
| .github | ||
| airflow | ||
| backport_packages | ||
| chart | ||
| common | ||
| dags | ||
| dev | ||
| docs | ||
| empty | ||
| hooks | ||
| images | ||
| kubernetes_tests | ||
| license-templates | ||
| licenses | ||
| manifests | ||
| metastore_browser | ||
| requirements | ||
| scripts | ||
| tests | ||
| .asf.yaml | ||
| .bash_completion | ||
| .coveragerc | ||
| .dockerignore | ||
| .editorconfig | ||
| .flake8 | ||
| .gitignore | ||
| .hadolint.yaml | ||
| .mailmap | ||
| .pre-commit-config.yaml | ||
| .rat-excludes | ||
| .readthedocs.yml | ||
| BREEZE.rst | ||
| CHANGELOG.txt | ||
| CI.rst | ||
| CONTRIBUTING.rst | ||
| Dockerfile | ||
| Dockerfile.ci | ||
| IMAGES.rst | ||
| INSTALL | ||
| LICENSE | ||
| LOCAL_VIRTUALENV.rst | ||
| MANIFEST.in | ||
| NOTICE | ||
| README.md | ||
| STATIC_CODE_CHECKS.rst | ||
| TESTING.rst | ||
| UPDATING.md | ||
| breeze | ||
| breeze-complete | ||
| confirm | ||
| pylintrc | ||
| pytest.ini | ||
| setup.cfg | ||
| setup.py | ||
| yamllint-config.yml | ||
README.md
Apache Airflow
Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows.
When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative.
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.
Table of contents
- Requirements
- Getting started
- Installing from PyPI
- Beyond the Horizon
- Principles
- User Interface
- Backport packages
- Contributing
- Who uses Apache Airflow?
- Who Maintains Apache Airflow?
- Can I use the Apache Airflow logo in my presentation?
- Links
Requirements
Apache Airflow is tested with:
Master version (2.0.0dev)
- Python versions: 3.6, 3.7, 3.8
- Postgres DB: 9.6, 10
- MySQL DB: 5.7
- Sqlite - latest stable (it is used mainly for development purpose)
- Kubernetes - 1.16.2, 1.17.0
Stable version (1.10.10)
- Python versions: 2.7, 3.5, 3.6, 3.7
- Postgres DB: 9.6, 10
- MySQL DB: 5.6, 5.7
- Sqlite - latest stable (it is used mainly for development purpose)
- Kubernetes - 1.16.2, 1.17.0
Additional notes on Python version requirements
- Stable version requires at least Python 3.5.3 when using Python 3
- Stable version is currently incompatible with Python 3.8 due to a known compatibility issue with a dependent library
Getting started
Please visit the Airflow Platform documentation (latest stable release) for help with installing Airflow, getting a quick start, or a more complete tutorial.
Documentation of GitHub master (latest development branch): ReadTheDocs Documentation
For further information, please visit the Airflow Wiki.
Official container (Docker) images for Apache Airflow are described in IMAGES.rst.
Installing from PyPI
Airflow is published as apache-airflow package in PyPI. Installing it however might be sometimes tricky
because Airflow is a bit of both a library and application. Libraries usually keep their dependencies open and
applications usually pin them, but we should do neither and both at the same time. We decided to keep
our dependencies as open as possible (in setup.py) so users can install different versions of libraries
if needed. This means that from time to time plain pip install apache-airflow will not work or will
produce unusable Airflow installation.
In order to have repeatable installation, however, starting from Airflow 1.10.10 we also keep a set of
"known-to-be-working" requirement files in the requirements folder. Those "known-to-be-working"
requirements are per major/minor python version (3.6/3.7/3.8). You can use them as constraint files
when installing Airflow from PyPI. Note that you have to specify correct Airflow version and python versions
in the URL.
- Installing just airflow:
pip install apache-airflow==1.10.10 \
--constraint https://raw.githubusercontent.com/apache/airflow/1.10.10/requirements/requirements-python3.7.txt
- Installing with extras (for example postgres,gcp)
pip install apache-airflow[postgres,gcp]==1.10.10 \
--constraint https://raw.githubusercontent.com/apache/airflow/1.10.10/requirements/requirements-python3.7.txt
Beyond the Horizon
Airflow is not a data streaming solution. Tasks do not move data from one to the other (though tasks can exchange metadata!). Airflow is not in the Spark Streaming or Storm space, it is more comparable to Oozie or Azkaban.
Workflows are expected to be mostly static or slowly changing. You can think of the structure of the tasks in your workflow as slightly more dynamic than a database structure would be. Airflow workflows are expected to look similar from a run to the next, this allows for clarity around unit of work and continuity.
Principles
- Dynamic: Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically.
- Extensible: Easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment.
- Elegant: Airflow pipelines are lean and explicit. Parameterizing your scripts is built into the core of Airflow using the powerful Jinja templating engine.
- Scalable: Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers.
User Interface
-
DAGs: Overview of all DAGs in your environment.
-
Tree View: Tree representation of a DAG that spans across time.
-
Graph View: Visualization of a DAG's dependencies and their current status for a specific run.
-
Task Duration: Total time spent on different tasks over time.
-
Gantt View: Duration and overlap of a DAG.
-
Code View: Quick way to view source code of a DAG.
Backport packages
Context: Airflow 2.0 operators, hooks, and secrets
Currently, stable Apache Airflow versions are from the 1.10.* series. We are working on the future, major version of Airflow from the 2.0.* series. It is going to be released in 2020. However, the exact time of release depends on many factors and is not yet confirmed.
We have already a lot of changes in the operators, transfers, hooks, sensors, secrets for many external systems, but they are not used nor tested widely because they are part of the master/2.0 release.
In the Airflow 2.0 - following AIP-21 "change in import paths" all the non-core interfaces to external systems of Apache Airflow have been moved to the "airflow.providers" package.
Thanks to that and automated backport effort we took, the operators from Airflow 2.0 can be used in Airflow 1.10 as separately installable packages, with the constraint that those packages can only be used in python3.6+ environment.
Installing Airflow 2.0 operators in Airflow 1.10
We released backport packages that can be installed for older Airflow versions. Those backport packages are going to be released more frequently that main Airflow 1.10.& releases.
You will not have to upgrade your Airflow version to use those packages. You can find those packages in the PyPI and install them separately for each provider.
Those packages are available now and can be used in the latest Airflow 1.10* version. Most of those packages are also installable and usable in most Airflow 1.10.* releases but there is no extensive testing done beyond the latest released version, so you might expect more problems in earlier Airflow versions.
An easier migration path to 2.0
With backported providers package users can migrate their DAGs to the new providers package incrementally and once they convert to the new operators/sensors/hooks they can seamlessly migrate their environments to Airflow 2.0. The nice thing about providers backport packages is that you can use both old and new classes at the same time - even in the same DAG. So your migration can be gradual and smooth. Note that in Airflow 2.0 old classes raise deprecation warning and redirect to the new classes wherever it is possible. In some rare cases the new operators will not be fully backwards compatible - you will find information about those cases in UPDATING.md where we explained all such cases. Switching early to the Airflow 2.0 operators while still running Airflow 1.10 will make your migration much easier.
More information about the status and releases of the back-ported packages are available at Backported providers package page
Installing backport packages
Note that the backport packages might require extra dependencies. Pip installs the required dependencies
automatically when it installs the backport package, but there are sometimes cross-dependencies between the
backport packages. For example google package has cross-dependency with amazon package to allow
transfers between those two cloud providers. You might need to install those packages in case you use
cross-dependent packages. The easiest way to install them is to use "extras" when installing the package,
for example the below will install both google and amazon backport packages:
pip install apache-airflow-backport-providers-google[amazon]
This is all documented in the PyPI description of the packages as well as in the README.md file available for each provider package. For example for google package you can find the readme in README.md. You will also find there the summary of both - new classes and moved classes as well as requirement information.
Troubleshooting installing backport packages
Backport providers only work when they are installed in the same namespace as the 'apache-airflow' 1.10
package. This is majority of cases when you simply run pip install - it installs all packages
in the same folder (usually in /usr/local/lib/pythonX.Y/site-packages). But when you install
the apache-airflow and apache-airflow-backport-package-* using different methods (for example using
pip install -e . or pip install --user they might be installed in different namespaces.
If that's the case, the provider packages will not be importable (the error in such case is
ModuleNotFoundError: No module named 'airflow.providers').
If you experience the problem, you can easily fix it by creating symbolic link
in your installed "airflow" folder to the "providers" folder where you installed your backport packages.
If you installed it with -e, this link should be created in your airflow
sources, if you installed it with the --user flag it should be from the
~/.local/lib/pythonX.Y/site-packages/airflow/ folder,
Contributing
Want to help build Apache Airflow? Check out our contributing documentation.
Who uses Apache Airflow?
As the Apache Airflow community grows, we'd like to keep track of who is using the platform. Please send a PR with your company name and @githubhandle if you may.
Currently officially using Airflow:
- 4G Capital [@posei]
- 6play [@lemourA, @achaussende, @d-nguyen, @julien-gm]
- 8fit [@nicor88, @frnzska]
- 90 Seconds [@aaronmak]
- 99 [@fbenevides, @gustavoamigo & @mmmaia]
- AdBOOST [AdBOOST]
- Adobe [@mishikaSingh, @ramandumcs, @vardancse]
- Agari [@r39132]
- Agoda [@akki]
- Airbnb [@mistercrunch, @artwr]
- AirDNA
- Airfinity [@sibowyer]
- Airtel [@harishbisht]
- Akamas [@GiovanniPaoloGibilisco, @lucacavazzana]
- Alan [@charles-go]
- allegro.pl [@kretes]
- AloPeyk [@blcksrx, @AloPeyk]
- AltX [@pedromduarte]
- AMPATH[@AMPATH, @fatmali]
- Apigee [@btallman]
- ARGO Labs [@California Data Collaborative]
- ARMEDANGELS [@swiffer]
- Arquivei [@arquivei]
- Arrive
- Asana [@chang, @dima-asana, @jdavidheiser, @ricardoandresrojas]
- Astronomer [@schnie, @ashb, @kaxil, @dimberman, @andriisoldatenko, @ryw, @andrewhharmon]
- Auth0 [@sicarul]
- Automattic [@anandnalya, @bperson, @khrol, @xyu]
- Away [@trunsky]
- Azri Solutions [@userimack]
- Bagelcode
- BalanceHero [@swalloow]
- Banco de Formaturas [@guiligan]
- BandwidthX [@dineshdsharma]
- Basetis
- BBM
- Beamly [@christopheralcock]
- Beeswax
- Bellhops
- BelugaDB [@fabio-nukui & @joao-sallaberry & @lucianoviola & @tmatuki]
- Betterment [@betterment]
- Bexs Bank [@felipefb & @ilarsen]
- BigQuant [@bigquant]
- Birdz by Veolia [@benjamingrenier]
- BlaBlaCar [@puckel & @wmorin]
- Blacklane [@serkef]
- Bloc [@dpaola2]
- Bloomberg [@dimberman]
- Blue Yonder [@blue-yonder]
- BlueApron [@jasonjho & @matthewdavidhauser]
- Bluecore [@JLDLaughlin]
- Bluekiri [@Bluekiri]
- Boda Telecom Suite - CE [@erssebaggala, @bodastage]
- Bodastage Solutions [@erssebaggala, @bodastage]
- Bombora Inc [@jeffkpayne, @pakelley, @dNavalta, @austynh, @TheOriginalAlex]
- Bonial International GmbH
- Bonnier Broadcasting [@wileeam]
- BounceX [@JoshFerge, @hudsonrio, @ronniekritou]
- Braintree [@coopergillan, @curiousjazz77, @raymondberg]
- Branch [@sdebarshi, @dmitrig01]
- Caesars Entertainment
- California Data Collaborative powered by ARGO Labs
- Capital One [@anoopengineer]
- Carbonite [@ajbosco]
- CarLabs [@sganz & @odannyc]
- CAVA [@minh5 & @patchus]
- Celect [@superdosh & @chadcelect]
- Censys [@zakird, @dadrian, & @andrewsardone]
- Change.org [@change, @vijaykramesh]
- Chartboost [@cgelman & @dclubb]
- Checkr [@tongboh]
- Children's Hospital of Philadelphia Division of Genomic Diagnostics [@genomics-geek]
- Cinimex DataLab [@kdubovikov]
- City of San Diego [@MrMaksimize, @andrell81 & @arnaudvedy]
- City of Toronto [@CityofToronto, @radumas]
- ciValue [@chencivalue, @YoavGaudin, @saleem-boshnak]
- Civey [@WesleyBatista]
- Clairvoyant [@shekharv]
- Classmethod, Inc. [@shoito]
- Cleartax [@anks & @codebuff]
- Clover Health [@gwax & @vansivallab]
- Colgate-Palmolive [@fhoda]
- Collectivehealth Inc. [@retornam]
- Compass [@wdhorton]
- ConnectWise [@jacobeturpin]
- ContaAzul [@bern4rdelli, @renanleme & @sabino]
- Cotap [@maraca & @richardchew]
- Craig@Work
- Crealytics
- Credit Karma [@preete-dixit-ck & @harish-gaggar-ck & @greg-finley-ck]
- Creditas [@dcassiano]
- CreditCards.com[@vmAggies & @jay-wallaby]
- Cryptalizer.com
- Custom Ink [@david-dalisay, @dmartin11 & @mpeteuil]
- Cyscale [@ocical]
- Dailymotion [@germaintanguy & @hc]
- Danamica [@testvinder]
- Data Reply [@kaxil]
- DataCamp [@dgrtwo]
- DataFox [@sudowork]
- Dentsu Inc. [@bryan831 & @loozhengyuan]
- Deseret Digital Media [@formigone
- Digital First Media [@duffn & @mschmo & @seanmuth]
- DigitalOcean [@ajbosco]
- Digitas Pixelpark [@feluelle]
- DoorDash
- Dotmodus [@dannylee12]
- Drivy [@AntoineAugusti]
- Easy Taxi [@caique-lima & @diraol]
- EllisDon [@d2kalra & @zbasama]
- Endesa [@drexpp]
- Enigma [@hydrosquall]
- Datamaran [@valexharo]
- Etsy [@mchalek]
- evo.company [@orhideous]
- Experity (formerly DocuTAP) [@cloneluke & @tobyjoliver]
- Fathom Health
- Firestone Inventing [@zihengCat]
- Flipp [@sethwilsonwishabi]
- Format [@format & @jasonicarter]
- FreeNow [@freenowtech]
- FreshBooks [@DinoCow]
- Freshworks [@shaikshakeel]
- FullContact
- Fuller, Inc. [@wutali & @sh-tech]
- Fundera [@andyxhadji]
- G Adventures [@chchtv11, @tgumbley, @tomwross]
- GameWisp [@tjbiii & @theryanwalls]
- Geekie [@wolney]
- GeneCards [@oferze]
- Gentner Lab [@neuromusic]
- Get Simpl [@rootcss]
- GitLab [@tayloramurphy & @m_walker]
- Glassdoor [@syvineckruyk & @sid88in]
- Global Fashion Group [@GFG]
- GoDataDriven [@BasPH, @danielvdende, @ffinfo, @Fokko, @gglanzani, @hgrif, @jrderuiter, @NielsZeilemaker]
- Gojek [@gojek]
- GovTech GDS [@chrissng & @datagovsg]
- Grab [@calvintran]
- Gradeup [@gradeup]
- Grand Rounds [@richddr, @timz1290, @wenever, & @runongirlrunon]
- Greytip [@greytip]
- Groupalia [@jesusfcr]
- Groupon [@stevencasey]
- Growbots[@exploy]
- GrowthSimple
- GSN Games
- Gusto [@frankhsu]
- Handshake [@mhickman]
- Handy [@marcintustin / @mtustin-handy]
- happn [@pcorbel]
- HAVAN [@botbiz]
- HBC Digital [@tmccartan & @dmateusp]
- HBO[@yiwang]
- Healthjump [@miscbits]
- HelloFresh [@tammymendt & @davidsbatista & @iuriinedostup]
- Hipages [@arihantsurana]
- Holimetrix [@thibault-ketterer]
- HomeToGo [@HomeToGo, @AurimasGr]
- Hootsuite
- Hostnfly [@CyrilLeMat & @pierrechopin & @alexisrosuel]
- HotelQuickly [@zinuzoid]
- Huq Industries [@huqindustries, @alepuccetti, @turbomerl]
- Iflix [@ChaturvediSulabh]
- IFTTT [@apurvajoshi]
- iHeartRadio[@yiwang]
- imgix [@dclubb]
- ING
- Instacart 🥕 [@arp1t & @code-sauce & @jasonlew & @j4p3 & @lubert & @mmontagna & @RyanAD &@zzadeh]
- Intercom [@fox & @paulvic]
- Interia
- Investorise [@svenvarkel]
- iS2.co [@iS2co]
- Jampp
- Jeitto [@BrennerPablo & @ds-mauri]
- Jetlore [@bderose]
- JobTeaser [@stefani75 & @knil-sama]
- JULO [@sepam & @tenapril & @verzqy]
- Kalibrr [@charlesverdad]
- Kargo [@chaithra-yenikapati, @akarsh3007 & @dineshanchan]
- Karmic [@hyw]
- King [@nathadfield]
- King Abdullah Petroleum Studies and Research Center(KAPSARC) [@saianupkumarp]
- Kiwi.com [@underyx]
- Kogan.com [@geeknam]
- Korbit [@jensenity]
- KPN B.V. [@biyanisuraj & @gmic]
- Kroton Educacional
- Lemann Foundation [@fernandosjp]
- LeMans Corporation [@alloydwhitlock] & [@tinyrye]
- LendUp [@lendup]
- LetsBonus [@jesusfcr & @OpringaoDoTurno]
- Liberty Global [@LibertyGlobal]
- liligo [@tromika]
- LingoChamp [@haitaoyao]
- Logitravel Group
- Los Angeles Times [@standyro]
- LokSuvidha [@saurabhwahile]
- Lucid [@jbrownlucid & @kkourtchikov]
- Lumos Labs [@rfroetscher & @zzztimbo]
- Lyft [@feng-tao, @milton0825, @astahlman, @youngyjd, @ArgentFalcon]
- M4U [@msantino]
- Madrone [@mbreining & @scotthb]
- Markovian [@al-xv, @skogsbaeck, @waltherg]
- Mercadoni [@demorenoc]
- Mercari [@yu-iskw]
- MFG Labs
- MiNODES [@dice89, @diazcelsa]
- Modernizing Medicine[@kehv1n, @dalupus]
- Movember
- Multiply [@nrhvyc]
- National Bank of Canada [@brilhana]
- Neoway [@neowaylabs]
- Nerdwallet
- New Relic [@marcweil]
- Newzoo [@newzoo-nexus]
- NEXT Trucking [@earthmancash2, @kppullin]
- Nextdoor [@SivaPandeti, @zshapiro & @jthomas123]
- Nine [@TheZepto]
- OdysseyPrime [@davideberdin]
- OfferUp
- OneFineStay [@slangwald]
- Open Knowledge International @vitorbaptista
- Optum - UnitedHealthGroup [@fhoda, @ianstanton, @nilaybhatt,@hiteshrd]
- OrangeBank [@HamzaBoukraa]
- Outcome Health [@mikethoun, @rolandotribo]
- Overstock [@mhousley & @mct0006]
- OVH [@ncrocfer & @anthonyolea]
- Pagar.me [@pagarme]
- Palo Alto Networks [@PaloAltoNetworks]
- Pandora Media [@Acehaidrey & @wolfier]
- Paraná Banco [@lopesdiego12]
- PayFit [@pcorbel]
- PAYMILL [@paymill & @matthiashuschle]
- PayPal [@r39132 & @jhsenjaliya]
- Pecan [@ohadmata]
- Pernod-Ricard [@romain-nio]
- Plaid [@plaid, @AustinBGibbons & @jeeyoungk]
- Playbuzz [@clintonboys & @dbn]
- PMC [@andrewm4894]
- Polidea [@potiuk, @mschickensoup, @mik-laj, @turbaszek, @michalslowikowski00, @olchas]
- Poshmark
- Postmates [@syeoryn]
- Premise [@jmccallum-premise]
- Promofarma [@JavierLopezT]
- Pronto Tools [@zkan & @mesodiar]
- proton.ai [@prmsolutions]
- PubNub [@jzucker2]
- PXYData [@patchus]
- Qplum [@manti]
- Quantopian [@eronarn]
- Qubole [@msumit]
- QuintoAndar [@quintoandar]
- Quizlet [@quizlet]
- Quora
- Qoala [@gnomeria, @qoala-engineering]
- Rakuten
- Raízen [@rudlac & @guifneves]
- Rapido [@ChethanUK]
- REA Group
- Reddit [@reddit]
- Reverb[@reverbdotcom]
- Revolut [@sztanko & @nautilus28]
- Robinhood [@vineet-rh]
- RushOwl [@songyanho]
- Scaleway [@kdeldycke]
- Seasoned [@joshuacano] & [@mmyers] & [@tjward]
- Secret Escapes [@secretescapes]
- Semantics3 [@abishekk92]
- Sense360 [@kamilmroczek]
- Sentry.io [@tiopi]
- ShopBack [@shopback]
- Shopkick [@shopkick]
- Sidecar [@getsidecar]
- SimilarWeb [@similarweb]
- Simply Business [@simplybusiness]
- Skyscanner [@skyscanner]
- SmartNews [@takus]
- SnapTravel
- SocialCops [@vinayak-mehta & @sharky93]
- Société générale [@medmrgh & @s83]
- Spotahome [@spotahome]
- SpotHero [@benjigoldberg]
- Spotify [@znichols]
- Square
- Stackspace
- StoneCo [@lgwacker]
- Strava [@strava, @dhuang & @liamstewart]
- Stripe [@jbalogh]
- Strongmind [@tomchapin & @wongstein]
- Surfline [@jawang35]
- T2 Systems [@unclaimedpants]
- Tails.com [@alanmcruickshank]
- TEK [@telac]
- Telefonica Innovation Alpha [@Alpha-Health]
- Telia Company
- Ternary Data [@mhousley, @JoeReis]
- Tesla [@thoralf-gutierrez]
- The Home Depot[@apekshithr]
- THE ICONIC [@revathijay] [@ilikedata]
- Thinking Machines [@marksteve]
- Thinknear [@d3cay1, @ccson, & @ababian]
- ThoughtWorks [@sann3]
- Thumbtack [@natekupp]
- Tictail
- Tile [@ranjanmanish]
- Tinder [@kbendick]
- Tink [@tink-ab]
- TokenAnalyst [@simonohanlon101, @ankitchiplunkar, @sidshekhar, @sp6pe]
- Tokopedia [@topedmaria]
- Trocafone [@idontdomath & @gseva & @ordonezf & @PalmaLeandro]
- Twine Labs [@ivorpeles]
- Twitter [@aoen]
- Ubisoft [@Walkoss]
- Udacity [@dandikunited, @simon-uc]
- United Airlines [@ilopezfr]
- Upsight
- VeeR VR [@pishilong]
- Veikkaus [@hixus]
- Vente-Exclusive.com [@alexvanboxel]
- Vevo [@csetiawan & @jerrygillespie]
- Vidio
- Ville de Montréal@VilledeMontreal]
- Vnomics [@lpalum]
- Walmart Labs [@bharathpalaksha, @vipul007ravi]
- Waze [@waze]
- WePay [@criccomini & @mtagle]
- WeTransfer [@coredipper & @higee & @azclub]
- Whistle Labs [@ananya77041]
- Wildlifestudios
- WiseBanyan
- Wooga
- WorldRemit [@boittega]
- Wrike [@eliseealex & teoretic6]
- Xero [@yan9yu & adamantnz]
- Xoom
- Yahoo!
- Yieldr [@ggeorgiadis]
- Zapier [@drknexus & @statwonk]
- Zego [@ruimffl, @james-welly, @ken-payne]
- Zendesk
- Zenly [@cerisier & @jbdalido]
- Zerodha [@johnnybravo-xyz]
- Zymergen
- Zynga
Who Maintains Apache Airflow?
Airflow is the work of the community, but the core committers/maintainers are responsible for reviewing and merging PRs as well as steering conversation around new feature requests. If you would like to become a maintainer, please review the Apache Airflow committer requirements.
Can I use the Apache Airflow logo in my presentation?
Yes! Be sure to abide by the Apache Foundation trademark policies and the Apache Airflow Brandbook. The most up to date logos are found in this repo and on the Apache Software Foundation website.