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Introduction to Akka
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Johan Andrén
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The topconf 2013 introduction to actors with Akka
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Slides from Jetbrains/Akka webinar about Akka Actors with Java 8 2016-09-13
Introduction to akka actors with java 8
Introduction to akka actors with java 8
Johan Andrén
The slides of the speech I given during coscup 2011. The topic is "Programming for the Future, Introduction to Actor Model and Akka"
Introduction to Actor Model and Akka
Introduction to Actor Model and Akka
Yung-Lin Ho
Lessons learned through agony and pain, lots of pain.
Building Scalable, Highly Concurrent & Fault Tolerant Systems - Lessons Learned
Building Scalable, Highly Concurrent & Fault Tolerant Systems - Lessons Learned
Jonas Bonér
Akka in Practice: Designing Actor-based Applications
Akka in Practice: Designing Actor-based Applications
NLJUG
This is a brief introduction to Akka.Cluster: - what is Akka.Cluster? - what does it do for me / why should I care? - when do I use it? - how do I use it?
Slides - Intro to Akka.Cluster
Slides - Intro to Akka.Cluster
petabridge
Akka cluster overview at 010dev
Akka cluster overview at 010dev
Roland Kuhn
Akka is the platform for the next generation event-driven, scalable and fault-tolerant architectures on the JVM We believe that writing correct concurrent, fault-tolerant and scalable applications is too hard. Most of the time it's because we are using the wrong tools and the wrong level of abstraction. Akka is here to change that. Using the Actor Model together with Software Transactional Memory we raise the abstraction level and provides a better platform to build correct concurrent and scalable applications. For fault-tolerance we adopt the "Let it crash" / "Embrace failure" model which have been used with great success in the telecom industry to build applications that self-heals, systems that never stop. Actors also provides the abstraction for transparent distribution and the basis for truly scalable and fault-tolerant applications. Akka is Open Source and available under the Apache 2 License.
Akka: Simpler Scalability, Fault-Tolerance, Concurrency & Remoting through Ac...
Akka: Simpler Scalability, Fault-Tolerance, Concurrency & Remoting through Ac...
Jonas Bonér
Learn how to build Reactive Systems with Akka. Examples in both Java 8 and Scala. Abstract: The demands and expectations for applications have changed dramatically in recent years. Applications today are deployed on a wide range of infrastructure; from mobile devices up to thousands of nodes running in the cloud—all powered by multi-core processors. They need to be rich and collaborative, have a real-time feel with millisecond response time and should never stop running. Additionally, modern applications are a mashup of external services that need to be consumed and composed to provide the features at hand. We are seeing a new type of applications emerging to address these new challenges—these are being called Reactive Applications. In this talk we will introduce you to Akka and discuss how it can help you deliver on the four key traits of Reactive; Responsive, Resilient, Elastic and Message-Driven. We will start with the basics of Akka and work our way towards some of its more advanced modules such as Akka Cluster and Akka Persistence—all driven through code and practical examples.
Building Reactive Systems with Akka (in Java 8 or Scala)
Building Reactive Systems with Akka (in Java 8 or Scala)
Jonas Bonér
Recommandé
Slides from Jetbrains/Akka webinar about Akka Actors with Java 8 2016-09-13
Introduction to akka actors with java 8
Introduction to akka actors with java 8
Johan Andrén
The slides of the speech I given during coscup 2011. The topic is "Programming for the Future, Introduction to Actor Model and Akka"
Introduction to Actor Model and Akka
Introduction to Actor Model and Akka
Yung-Lin Ho
Lessons learned through agony and pain, lots of pain.
Building Scalable, Highly Concurrent & Fault Tolerant Systems - Lessons Learned
Building Scalable, Highly Concurrent & Fault Tolerant Systems - Lessons Learned
Jonas Bonér
Akka in Practice: Designing Actor-based Applications
Akka in Practice: Designing Actor-based Applications
NLJUG
This is a brief introduction to Akka.Cluster: - what is Akka.Cluster? - what does it do for me / why should I care? - when do I use it? - how do I use it?
Slides - Intro to Akka.Cluster
Slides - Intro to Akka.Cluster
petabridge
Akka cluster overview at 010dev
Akka cluster overview at 010dev
Roland Kuhn
Akka is the platform for the next generation event-driven, scalable and fault-tolerant architectures on the JVM We believe that writing correct concurrent, fault-tolerant and scalable applications is too hard. Most of the time it's because we are using the wrong tools and the wrong level of abstraction. Akka is here to change that. Using the Actor Model together with Software Transactional Memory we raise the abstraction level and provides a better platform to build correct concurrent and scalable applications. For fault-tolerance we adopt the "Let it crash" / "Embrace failure" model which have been used with great success in the telecom industry to build applications that self-heals, systems that never stop. Actors also provides the abstraction for transparent distribution and the basis for truly scalable and fault-tolerant applications. Akka is Open Source and available under the Apache 2 License.
Akka: Simpler Scalability, Fault-Tolerance, Concurrency & Remoting through Ac...
Akka: Simpler Scalability, Fault-Tolerance, Concurrency & Remoting through Ac...
Jonas Bonér
Learn how to build Reactive Systems with Akka. Examples in both Java 8 and Scala. Abstract: The demands and expectations for applications have changed dramatically in recent years. Applications today are deployed on a wide range of infrastructure; from mobile devices up to thousands of nodes running in the cloud—all powered by multi-core processors. They need to be rich and collaborative, have a real-time feel with millisecond response time and should never stop running. Additionally, modern applications are a mashup of external services that need to be consumed and composed to provide the features at hand. We are seeing a new type of applications emerging to address these new challenges—these are being called Reactive Applications. In this talk we will introduce you to Akka and discuss how it can help you deliver on the four key traits of Reactive; Responsive, Resilient, Elastic and Message-Driven. We will start with the basics of Akka and work our way towards some of its more advanced modules such as Akka Cluster and Akka Persistence—all driven through code and practical examples.
Building Reactive Systems with Akka (in Java 8 or Scala)
Building Reactive Systems with Akka (in Java 8 or Scala)
Jonas Bonér
Slides from Akka typed talk at Øredev 2018 in Malmö, Sweden.
Next generation message driven systems with Akka
Next generation message driven systems with Akka
Johan Andrén
Slides on Akka Cluster, Akka Cluster Tools from jDays 2018, Gothenburg
Buiilding reactive distributed systems with Akka
Buiilding reactive distributed systems with Akka
Johan Andrén
Slides from the Scala italy 2018 talk about the new Akka Typed actor APIs
Next generation actors with Akka
Next generation actors with Akka
Johan Andrén
From Devdays vilnius 2018, introducing Akka Typed with samples in Java
Next generation message driven systems with Akka
Next generation message driven systems with Akka
Johan Andrén
Slides from talk at JeeConf, Kiev 2018-05-19
Reactive stream processing using Akka streams
Reactive stream processing using Akka streams
Johan Andrén
Slides from talk at Devoxx UK 2018-05-11
Networks and types - the future of Akka
Networks and types - the future of Akka
Johan Andrén
Slides from JavaZone 2017 talk about Reactive Streams and Akka Streams
Reactive streams processing using Akka Streams
Reactive streams processing using Akka Streams
Johan Andrén
Slides from Akka Cluster talk at Scala Swarm 2017 in Porto, Portugal
Building reactive distributed systems with Akka
Building reactive distributed systems with Akka
Johan Andrén
Akka streams talk from Umeå Java User Group 2017-06-13
Akka streams - Umeå java usergroup
Akka streams - Umeå java usergroup
Johan Andrén
Slides from my Akka streams talk at Voxxeddays Zürich 2017-02-23
Streaming all the things with akka streams
Streaming all the things with akka streams
Johan Andrén
Slides from talk at JFokus 2017 about Akka Streams, Alpakka and Reactive Streams
Asynchronous stream processing with Akka Streams
Asynchronous stream processing with Akka Streams
Johan Andrén
Akka Streams introduction at the Scala Usergroup Stockholm meetup 2016-10-18
Scala usergroup stockholm - reactive integrations with akka streams
Scala usergroup stockholm - reactive integrations with akka streams
Johan Andrén
Slides from the Akka Streams session on VJUG24 2016-09-27.
VJUG24 - Reactive Integrations with Akka Streams
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Johan Andrén
Slides from my talk about Async with Play framework Scala and Java from the PingConf in Budapest january 2014
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Swedish slides from the breakfast seminar about Scala held at the Mejsla office 2013-11-22
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My Topconf Tallinn 2012 talk on macros and reflection in Scala 2.10.
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Introduction to Akka
1.
An introduction to Actors Akka with Johan
Andrén johan.andren@mejsla.se | @apnylle
2.
Moores law 2,6 billions 1
million 2300 1971 1990 today
3.
Oh, No Problems!
4.
Oh No, Problems! • • • • • • Race
conditions Data corruption Deadlocks Thread contention Livelocks Priority Inversion
5.
Concurrency is HARD • • • • To
write To test To debug To reason about We need a better model!
6.
7.
B C D A F E
8.
event driven systems with ACTORS
9.
10.
State Inbox The only way
to interact from outside Behaviour
11.
• • • • • Single execution flow
model No shared _mutable_ state Lightweight Loose coupling Easy to test
12.
Actor A Actor B
13.
One way communication Actor
A Actor B
14.
React, don’t wait Actor
A Actor B
15.
Load balancing Actor A Actor
B1 router Actor B2
16.
Pipe/Filter Actor A Actor F (filter) Actor
B
17.
Parallellize Actor C1 Actor A Actor
B (chef) Actor C2 Actor C2
18.
• • • No work, no
thread used! Async - never actively wait Loose coupling
19.
JVM B C D A F E
20.
JVM 1 B C JVM 2 D A F E
21.
The same same • • • Two
actors on one core Two actors on separate cores Two actors on separate servers
22.
Error handling in Actor
systems
23.
24.
Traditional model • • • Leaking information
between tiers Impossible to detect simultaneous errors The receiver does not know how to handle the errors!
25.
Error handling with
Actors (parent) Actor A Actor X Actor Z
26.
Error handling with
Actors (parent) Actor A Actor X Actor Z
27.
Error handling with
Actors Actor A Actor X Actor Z
28.
”Supervision” • • • • Compartmentilization What goes back
is explicit Separating error handling and business logic Can detect simultaneous errors
29.
But Wait, there is
more! • • • • • STM Remoting Clustring with no SPoF MQs integration Eventbus Website: akka.io
30.
Try it out! Typesafe
Activator typesafe.com
31.
Recap • • • • Simple but powerful
model Lightweight and fast Loose coupling Resiliency Johan Andrén johan.andren@mejsla.se | @apnylle
32.
Questions? Johan Andrén johan.andren@mejsla.se |
@apnylle
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