SlideShare a Scribd company logo
Airflow: Deferrable
“Async” Operators
How you can save tons of money!!
Kaxil Naik
Open Source Summit 2022
Who am I?
● Committer & PMC Member of Apache Airflow
● Director of Airflow Engineering @ Astronomer
@kaxil
What is Apache Airflow?
A platform to programmatically author,
schedule, and monitor workflows
Example DAG
Why deferrable operators?
The problem around current operators & sensors
What are they?
And how do they work?
Available async operators
How to find & use the available async operators
Why deferrable operators?
Scheduler
Time
Scheduler
Worker
Scheduler
Time
Scheduler
Submit Spark Job
Typical Operator
Poll Spark cluster Job Completion
Worker
Scheduler
Time
Scheduler
Typical Sensor
Wait for files to arrive in S3 Arrived!
Worker
Scheduler
Time
Scheduler
What a waste!
Wait for files to arrive in S3 Arrived!
Worker
Submit Spark Job Poll Spark cluster Job Completion
Wasted resources
Wasted resources
Operator
Sensor
Time
Polling for Spark Job completion Done!
Multiple
Sensors
Wait for files to arrive in S3 Done!
Polling for Bigquery Job completion Done!
Polling for Spark Job completion Done!
Wait for files to arrive in S3 Done!
Wait for files to arrive in GCS Done!
Imagine the Cost!
Multiple worker slots
Blocked !!
What are deferrable operators?
Scheduler
Time
Scheduler
Worker
Triggerer
Worker
Scheduler
Time
Scheduler
Submit Spark Job
Async Operator
Free slot Job Completion
Worker
Poll Spark cluster
Triggerer
Scheduler
Time
Scheduler
Task 1
Worker Slot (Sync vs Async)
Task 2
Sync
Operator
Async
Operator
Task 1 Task 2 Task 3 Task 2
Task 1 Task 4
Task runs on the Worker, then “defers” itself
Example: Submit an API call and stores job_id in DB
Runs on Triggerer
Async polling until the criteria is met, stores response in DB
Back to the Worker
To show response in the logs and set Task state
Scheduler
Time
Scheduler
Submit Spark Job
Async Operator
Free slot Job Completion
Worker
Poll Spark cluster
Triggerer
Trigger - a
new concept
Trigger is different than Operator
Must be asynchronous & quick
So Triggerer can run thousands of them per CPU core
Should not persistent state
So we can shuffle them around between Triggerers as needed
Must support running multiple copies of itself
For reliability during network partitions
class DateTimeTrigger(BaseTrigger):
def __init__(self, moment: datetime.datetime):
super().__init__()
self.moment = moment
def serialize(self):
return ("mymodule.DateTimeTrigger", {"moment": self.moment})
async def run(self):
while self.moment > timezone.utcnow():
await asyncio.sleep(1)
yield TriggerEvent(self.moment)
class WaitOneHourSensor(BaseSensorOperator):
def execute(self, context):
self.defer(
trigger=TimeDeltaTrigger(timedelta(hours=1)),
method_name="execute_complete",
)
def execute_complete(self, context, event=None):
# We have no more work to do here. Mark as complete.
return
Available Deferrable Operators
Core Airflow & Providers
https://github.com/apache/airflow/
Astronomer Providers
https://github.com/astronomer/astronomer-providers
50+ async operators
Astronomer Providers
https://github.com/astronomer/astronomer-providers
50+ async operators
Built and maintained with ❤ by Astronomer
Apache 2 licensed & Open-source
Drop-in replacements of “sync” Operators
Openlineage support
Astronomer Providers
https://github.com/astronomer/astronomer-providers
Async Operators available for:
● AWS, Google Cloud, Microsoft Azure
● Databricks, Snowflake
● Kubernetes, Apache Livy, Apache Hive
● HTTP, Filesystem
from astronomer.providers.amazon.aws.sensors.s3 import S3KeySensorAsync as S3KeySensor
waiting_for_s3_key = S3KeySensor(
task_id="waiting_for_s3_key"
,
bucket_key="sample_key.txt"
,
wildcard_match
=False,
bucket_name="sample-bucket"
,
)
Caveats when building one
More cost benefits when polling takes longer time
We've seen over a 90% reduction in resources for a 10 min wait
Not everything can be deferred
It must be an external event/system with a unique identifier
Triggerer logs are not visible in the Webserver/UI
Only task logs from workers are displayed on UI
Thank You
@kaxil

More Related Content

What's hot

Battle Of The Microservice Frameworks: Micronaut versus Quarkus edition!
Battle Of The Microservice Frameworks: Micronaut versus Quarkus edition! Battle Of The Microservice Frameworks: Micronaut versus Quarkus edition!
Battle Of The Microservice Frameworks: Micronaut versus Quarkus edition!
Michel Schudel
 
Hyperledger Fabric 1.0 概要
Hyperledger Fabric 1.0 概要Hyperledger Fabric 1.0 概要
Hyperledger Fabric 1.0 概要
Hyperleger Tokyo Meetup
 
GCP HTTPロードバランサ運用例
GCP HTTPロードバランサ運用例GCP HTTPロードバランサ運用例
GCP HTTPロードバランサ運用例
Fumihiko Shiroyama
 
Kafka streams windowing behind the curtain
Kafka streams windowing behind the curtain Kafka streams windowing behind the curtain
Kafka streams windowing behind the curtain
confluent
 
Metaspace
MetaspaceMetaspace
Metaspace
Yasumasa Suenaga
 
Google Cloud Composer
Google Cloud ComposerGoogle Cloud Composer
Google Cloud Composer
Pierre Coste
 
Azure Antenna はじめての Azure Data Lake
Azure Antenna はじめての Azure Data LakeAzure Antenna はじめての Azure Data Lake
Azure Antenna はじめての Azure Data Lake
Hideo Takagi
 
golang profiling の基礎
golang profiling の基礎golang profiling の基礎
golang profiling の基礎
yuichiro nakazawa
 
Apache Camel v3, Camel K and Camel Quarkus
Apache Camel v3, Camel K and Camel QuarkusApache Camel v3, Camel K and Camel Quarkus
Apache Camel v3, Camel K and Camel Quarkus
Claus Ibsen
 
What's New in v2 - AnsibleFest London 2015
What's New in v2 - AnsibleFest London 2015What's New in v2 - AnsibleFest London 2015
What's New in v2 - AnsibleFest London 2015
jimi-c
 
ストリーム処理におけるApache Avroの活用について(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)
ストリーム処理におけるApache Avroの活用について(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)ストリーム処理におけるApache Avroの活用について(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)
ストリーム処理におけるApache Avroの活用について(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)
NTT DATA Technology & Innovation
 
Hadoop入門
Hadoop入門Hadoop入門
Hadoop入門
Preferred Networks
 
Cycloudのストレージ紹介と歴史
Cycloudのストレージ紹介と歴史Cycloudのストレージ紹介と歴史
Cycloudのストレージ紹介と歴史
Hiroki Chinen
 
Elasticsearch の検索精度のチューニング 〜テストを作って高速かつ安全に〜
Elasticsearch の検索精度のチューニング 〜テストを作って高速かつ安全に〜Elasticsearch の検索精度のチューニング 〜テストを作って高速かつ安全に〜
Elasticsearch の検索精度のチューニング 〜テストを作って高速かつ安全に〜
Takahiko Ito
 
Running Apache Spark on Kubernetes: Best Practices and Pitfalls
Running Apache Spark on Kubernetes: Best Practices and PitfallsRunning Apache Spark on Kubernetes: Best Practices and Pitfalls
Running Apache Spark on Kubernetes: Best Practices and Pitfalls
Databricks
 
The Parquet Format and Performance Optimization Opportunities
The Parquet Format and Performance Optimization OpportunitiesThe Parquet Format and Performance Optimization Opportunities
The Parquet Format and Performance Optimization Opportunities
Databricks
 
PostgreSQL16でのロールに関する変更点(第41回PostgreSQLアンカンファレンス@オンライン 発表資料)
PostgreSQL16でのロールに関する変更点(第41回PostgreSQLアンカンファレンス@オンライン 発表資料)PostgreSQL16でのロールに関する変更点(第41回PostgreSQLアンカンファレンス@オンライン 発表資料)
PostgreSQL16でのロールに関する変更点(第41回PostgreSQLアンカンファレンス@オンライン 発表資料)
NTT DATA Technology & Innovation
 
Bloom filter
Bloom filterBloom filter
Bloom filter
Kumazaki Hiroki
 
Katib
KatibKatib
Graal in GraalVM - A New JIT Compiler
Graal in GraalVM - A New JIT CompilerGraal in GraalVM - A New JIT Compiler
Graal in GraalVM - A New JIT Compiler
Koichi Sakata
 

What's hot (20)

Battle Of The Microservice Frameworks: Micronaut versus Quarkus edition!
Battle Of The Microservice Frameworks: Micronaut versus Quarkus edition! Battle Of The Microservice Frameworks: Micronaut versus Quarkus edition!
Battle Of The Microservice Frameworks: Micronaut versus Quarkus edition!
 
Hyperledger Fabric 1.0 概要
Hyperledger Fabric 1.0 概要Hyperledger Fabric 1.0 概要
Hyperledger Fabric 1.0 概要
 
GCP HTTPロードバランサ運用例
GCP HTTPロードバランサ運用例GCP HTTPロードバランサ運用例
GCP HTTPロードバランサ運用例
 
Kafka streams windowing behind the curtain
Kafka streams windowing behind the curtain Kafka streams windowing behind the curtain
Kafka streams windowing behind the curtain
 
Metaspace
MetaspaceMetaspace
Metaspace
 
Google Cloud Composer
Google Cloud ComposerGoogle Cloud Composer
Google Cloud Composer
 
Azure Antenna はじめての Azure Data Lake
Azure Antenna はじめての Azure Data LakeAzure Antenna はじめての Azure Data Lake
Azure Antenna はじめての Azure Data Lake
 
golang profiling の基礎
golang profiling の基礎golang profiling の基礎
golang profiling の基礎
 
Apache Camel v3, Camel K and Camel Quarkus
Apache Camel v3, Camel K and Camel QuarkusApache Camel v3, Camel K and Camel Quarkus
Apache Camel v3, Camel K and Camel Quarkus
 
What's New in v2 - AnsibleFest London 2015
What's New in v2 - AnsibleFest London 2015What's New in v2 - AnsibleFest London 2015
What's New in v2 - AnsibleFest London 2015
 
ストリーム処理におけるApache Avroの活用について(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)
ストリーム処理におけるApache Avroの活用について(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)ストリーム処理におけるApache Avroの活用について(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)
ストリーム処理におけるApache Avroの活用について(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)
 
Hadoop入門
Hadoop入門Hadoop入門
Hadoop入門
 
Cycloudのストレージ紹介と歴史
Cycloudのストレージ紹介と歴史Cycloudのストレージ紹介と歴史
Cycloudのストレージ紹介と歴史
 
Elasticsearch の検索精度のチューニング 〜テストを作って高速かつ安全に〜
Elasticsearch の検索精度のチューニング 〜テストを作って高速かつ安全に〜Elasticsearch の検索精度のチューニング 〜テストを作って高速かつ安全に〜
Elasticsearch の検索精度のチューニング 〜テストを作って高速かつ安全に〜
 
Running Apache Spark on Kubernetes: Best Practices and Pitfalls
Running Apache Spark on Kubernetes: Best Practices and PitfallsRunning Apache Spark on Kubernetes: Best Practices and Pitfalls
Running Apache Spark on Kubernetes: Best Practices and Pitfalls
 
The Parquet Format and Performance Optimization Opportunities
The Parquet Format and Performance Optimization OpportunitiesThe Parquet Format and Performance Optimization Opportunities
The Parquet Format and Performance Optimization Opportunities
 
PostgreSQL16でのロールに関する変更点(第41回PostgreSQLアンカンファレンス@オンライン 発表資料)
PostgreSQL16でのロールに関する変更点(第41回PostgreSQLアンカンファレンス@オンライン 発表資料)PostgreSQL16でのロールに関する変更点(第41回PostgreSQLアンカンファレンス@オンライン 発表資料)
PostgreSQL16でのロールに関する変更点(第41回PostgreSQLアンカンファレンス@オンライン 発表資料)
 
Bloom filter
Bloom filterBloom filter
Bloom filter
 
Katib
KatibKatib
Katib
 
Graal in GraalVM - A New JIT Compiler
Graal in GraalVM - A New JIT CompilerGraal in GraalVM - A New JIT Compiler
Graal in GraalVM - A New JIT Compiler
 

Similar to Airflow: Save Tons of Money by Using Deferrable Operators

Von neumann workers
Von neumann workersVon neumann workers
Von neumann workers
riccardobecker
 
How I learned to time travel, or, data pipelining and scheduling with Airflow
How I learned to time travel, or, data pipelining and scheduling with AirflowHow I learned to time travel, or, data pipelining and scheduling with Airflow
How I learned to time travel, or, data pipelining and scheduling with Airflow
PyData
 
How I learned to time travel, or, data pipelining and scheduling with Airflow
How I learned to time travel, or, data pipelining and scheduling with AirflowHow I learned to time travel, or, data pipelining and scheduling with Airflow
How I learned to time travel, or, data pipelining and scheduling with Airflow
Laura Lorenz
 
Async programming and python
Async programming and pythonAsync programming and python
Async programming and python
Chetan Giridhar
 
Durable functions
Durable functionsDurable functions
Durable functions
Amresh Krishnamurthy
 
Integration-Monday-Stateful-Programming-Models-Serverless-Functions
Integration-Monday-Stateful-Programming-Models-Serverless-FunctionsIntegration-Monday-Stateful-Programming-Models-Serverless-Functions
Integration-Monday-Stateful-Programming-Models-Serverless-Functions
BizTalk360
 
Rhebok, High Performance Rack Handler / Rubykaigi 2015
Rhebok, High Performance Rack Handler / Rubykaigi 2015Rhebok, High Performance Rack Handler / Rubykaigi 2015
Rhebok, High Performance Rack Handler / Rubykaigi 2015
Masahiro Nagano
 
Angular - Improve Runtime performance 2019
Angular - Improve Runtime performance 2019Angular - Improve Runtime performance 2019
Angular - Improve Runtime performance 2019
Eliran Eliassy
 
Apex code Benchmarking
Apex code BenchmarkingApex code Benchmarking
Apex code Benchmarking
Amit Chaudhary
 
On the benchmark of Chainer
On the benchmark of ChainerOn the benchmark of Chainer
On the benchmark of Chainer
Kenta Oono
 
Runtime performance
Runtime performanceRuntime performance
Runtime performance
Eliran Eliassy
 
Stateful patterns in Azure Functions
Stateful patterns in Azure FunctionsStateful patterns in Azure Functions
Stateful patterns in Azure Functions
Massimo Bonanni
 
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
confluent
 
RxJava@Android
RxJava@AndroidRxJava@Android
RxJava@Android
Maxim Volgin
 
Introduction to Python Asyncio
Introduction to Python AsyncioIntroduction to Python Asyncio
Introduction to Python Asyncio
Nathan Van Gheem
 
Async Await for Mobile Apps
Async Await for Mobile AppsAsync Await for Mobile Apps
Async Await for Mobile Apps
Craig Dunn
 
Building Hermetic Systems (without Docker)
Building Hermetic Systems (without Docker)Building Hermetic Systems (without Docker)
Building Hermetic Systems (without Docker)
William Farrell
 
adaidoadaoap9dapdadadjoadjoajdoiajodiaoiao
adaidoadaoap9dapdadadjoadjoajdoiajodiaoiaoadaidoadaoap9dapdadadjoadjoajdoiajodiaoiao
adaidoadaoap9dapdadadjoadjoajdoiajodiaoiao
lyvanlinh519
 
Building Better Data Pipelines using Apache Airflow
Building Better Data Pipelines using Apache AirflowBuilding Better Data Pipelines using Apache Airflow
Building Better Data Pipelines using Apache Airflow
Sid Anand
 
Malo Denielou - No shard left behind: Dynamic work rebalancing in Apache Beam
Malo Denielou - No shard left behind: Dynamic work rebalancing in Apache BeamMalo Denielou - No shard left behind: Dynamic work rebalancing in Apache Beam
Malo Denielou - No shard left behind: Dynamic work rebalancing in Apache Beam
Flink Forward
 

Similar to Airflow: Save Tons of Money by Using Deferrable Operators (20)

Von neumann workers
Von neumann workersVon neumann workers
Von neumann workers
 
How I learned to time travel, or, data pipelining and scheduling with Airflow
How I learned to time travel, or, data pipelining and scheduling with AirflowHow I learned to time travel, or, data pipelining and scheduling with Airflow
How I learned to time travel, or, data pipelining and scheduling with Airflow
 
How I learned to time travel, or, data pipelining and scheduling with Airflow
How I learned to time travel, or, data pipelining and scheduling with AirflowHow I learned to time travel, or, data pipelining and scheduling with Airflow
How I learned to time travel, or, data pipelining and scheduling with Airflow
 
Async programming and python
Async programming and pythonAsync programming and python
Async programming and python
 
Durable functions
Durable functionsDurable functions
Durable functions
 
Integration-Monday-Stateful-Programming-Models-Serverless-Functions
Integration-Monday-Stateful-Programming-Models-Serverless-FunctionsIntegration-Monday-Stateful-Programming-Models-Serverless-Functions
Integration-Monday-Stateful-Programming-Models-Serverless-Functions
 
Rhebok, High Performance Rack Handler / Rubykaigi 2015
Rhebok, High Performance Rack Handler / Rubykaigi 2015Rhebok, High Performance Rack Handler / Rubykaigi 2015
Rhebok, High Performance Rack Handler / Rubykaigi 2015
 
Angular - Improve Runtime performance 2019
Angular - Improve Runtime performance 2019Angular - Improve Runtime performance 2019
Angular - Improve Runtime performance 2019
 
Apex code Benchmarking
Apex code BenchmarkingApex code Benchmarking
Apex code Benchmarking
 
On the benchmark of Chainer
On the benchmark of ChainerOn the benchmark of Chainer
On the benchmark of Chainer
 
Runtime performance
Runtime performanceRuntime performance
Runtime performance
 
Stateful patterns in Azure Functions
Stateful patterns in Azure FunctionsStateful patterns in Azure Functions
Stateful patterns in Azure Functions
 
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
 
RxJava@Android
RxJava@AndroidRxJava@Android
RxJava@Android
 
Introduction to Python Asyncio
Introduction to Python AsyncioIntroduction to Python Asyncio
Introduction to Python Asyncio
 
Async Await for Mobile Apps
Async Await for Mobile AppsAsync Await for Mobile Apps
Async Await for Mobile Apps
 
Building Hermetic Systems (without Docker)
Building Hermetic Systems (without Docker)Building Hermetic Systems (without Docker)
Building Hermetic Systems (without Docker)
 
adaidoadaoap9dapdadadjoadjoajdoiajodiaoiao
adaidoadaoap9dapdadadjoadjoajdoiajodiaoiaoadaidoadaoap9dapdadadjoadjoajdoiajodiaoiao
adaidoadaoap9dapdadadjoadjoajdoiajodiaoiao
 
Building Better Data Pipelines using Apache Airflow
Building Better Data Pipelines using Apache AirflowBuilding Better Data Pipelines using Apache Airflow
Building Better Data Pipelines using Apache Airflow
 
Malo Denielou - No shard left behind: Dynamic work rebalancing in Apache Beam
Malo Denielou - No shard left behind: Dynamic work rebalancing in Apache BeamMalo Denielou - No shard left behind: Dynamic work rebalancing in Apache Beam
Malo Denielou - No shard left behind: Dynamic work rebalancing in Apache Beam
 

More from Kaxil Naik

Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Kaxil Naik
 
Building and deploying LLM applications with Apache Airflow
Building and deploying LLM applications with Apache AirflowBuilding and deploying LLM applications with Apache Airflow
Building and deploying LLM applications with Apache Airflow
Kaxil Naik
 
Introducing airflowctl: A CLI to streamline getting started with Airflow - Ai...
Introducing airflowctl: A CLI to streamline getting started with Airflow - Ai...Introducing airflowctl: A CLI to streamline getting started with Airflow - Ai...
Introducing airflowctl: A CLI to streamline getting started with Airflow - Ai...
Kaxil Naik
 
Why Airflow? & What's new in Airflow 2.3?
Why Airflow? & What's new in Airflow 2.3?Why Airflow? & What's new in Airflow 2.3?
Why Airflow? & What's new in Airflow 2.3?
Kaxil Naik
 
What's new in Airflow 2.3?
What's new in Airflow 2.3?What's new in Airflow 2.3?
What's new in Airflow 2.3?
Kaxil Naik
 
Upgrading to Apache Airflow 2 | Airflow Summit 2021
Upgrading to Apache Airflow 2 | Airflow Summit 2021Upgrading to Apache Airflow 2 | Airflow Summit 2021
Upgrading to Apache Airflow 2 | Airflow Summit 2021
Kaxil Naik
 
Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...
Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...
Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...
Kaxil Naik
 
Upcoming features in Airflow 2
Upcoming features in Airflow 2Upcoming features in Airflow 2
Upcoming features in Airflow 2
Kaxil Naik
 
What's coming in Airflow 2.0? - NYC Apache Airflow Meetup
What's coming in Airflow 2.0? - NYC Apache Airflow MeetupWhat's coming in Airflow 2.0? - NYC Apache Airflow Meetup
What's coming in Airflow 2.0? - NYC Apache Airflow Meetup
Kaxil Naik
 
Airflow Best Practises & Roadmap to Airflow 2.0
Airflow Best Practises & Roadmap to Airflow 2.0Airflow Best Practises & Roadmap to Airflow 2.0
Airflow Best Practises & Roadmap to Airflow 2.0
Kaxil Naik
 
Apache Airflow in the Cloud: Programmatically orchestrating workloads with Py...
Apache Airflow in the Cloud: Programmatically orchestrating workloads with Py...Apache Airflow in the Cloud: Programmatically orchestrating workloads with Py...
Apache Airflow in the Cloud: Programmatically orchestrating workloads with Py...
Kaxil Naik
 

More from Kaxil Naik (11)

Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
 
Building and deploying LLM applications with Apache Airflow
Building and deploying LLM applications with Apache AirflowBuilding and deploying LLM applications with Apache Airflow
Building and deploying LLM applications with Apache Airflow
 
Introducing airflowctl: A CLI to streamline getting started with Airflow - Ai...
Introducing airflowctl: A CLI to streamline getting started with Airflow - Ai...Introducing airflowctl: A CLI to streamline getting started with Airflow - Ai...
Introducing airflowctl: A CLI to streamline getting started with Airflow - Ai...
 
Why Airflow? & What's new in Airflow 2.3?
Why Airflow? & What's new in Airflow 2.3?Why Airflow? & What's new in Airflow 2.3?
Why Airflow? & What's new in Airflow 2.3?
 
What's new in Airflow 2.3?
What's new in Airflow 2.3?What's new in Airflow 2.3?
What's new in Airflow 2.3?
 
Upgrading to Apache Airflow 2 | Airflow Summit 2021
Upgrading to Apache Airflow 2 | Airflow Summit 2021Upgrading to Apache Airflow 2 | Airflow Summit 2021
Upgrading to Apache Airflow 2 | Airflow Summit 2021
 
Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...
Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...
Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...
 
Upcoming features in Airflow 2
Upcoming features in Airflow 2Upcoming features in Airflow 2
Upcoming features in Airflow 2
 
What's coming in Airflow 2.0? - NYC Apache Airflow Meetup
What's coming in Airflow 2.0? - NYC Apache Airflow MeetupWhat's coming in Airflow 2.0? - NYC Apache Airflow Meetup
What's coming in Airflow 2.0? - NYC Apache Airflow Meetup
 
Airflow Best Practises & Roadmap to Airflow 2.0
Airflow Best Practises & Roadmap to Airflow 2.0Airflow Best Practises & Roadmap to Airflow 2.0
Airflow Best Practises & Roadmap to Airflow 2.0
 
Apache Airflow in the Cloud: Programmatically orchestrating workloads with Py...
Apache Airflow in the Cloud: Programmatically orchestrating workloads with Py...Apache Airflow in the Cloud: Programmatically orchestrating workloads with Py...
Apache Airflow in the Cloud: Programmatically orchestrating workloads with Py...
 

Recently uploaded

Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
KatiaHIMEUR1
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
Ana-Maria Mihalceanu
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Speck&Tech
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
SOFTTECHHUB
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Safe Software
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
DianaGray10
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
ControlCase
 
20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website
Pixlogix Infotech
 
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
Edge AI and Vision Alliance
 
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial ApplicationsLarge Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications
Rohit Gautam
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Albert Hoitingh
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
Aftab Hussain
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Matthew Sinclair
 
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
DianaGray10
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
danishmna97
 
“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”
Claudio Di Ciccio
 
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Zilliz
 

Recently uploaded (20)

Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
 
20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website
 
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
 
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial ApplicationsLarge Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
 
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
 
“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”
 
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...
 

Airflow: Save Tons of Money by Using Deferrable Operators