This slide shows you how to use Akka cluster in Java.
Source Code: https://github.com/jiayun/akka_samples
If you want to use the links in slide, please download the pdf file.
1. Akka is a toolkit for building concurrent and distributed applications on the JVM based on the actor model.
2. Actors communicate asynchronously by message passing and each actor processes one message at a time in its mailbox.
3. Akka provides features for concurrency, distribution, and fault-tolerance through actors, remoting, and supervision.
Akka is using the Actors together with STM to create a unified runtime and programming model for scaling both UP (multi-core) and OUT (grid/cloud). Akka provides location transparency by abstracting away both these tangents of scalability by turning them into an ops task. This gives the Akka runtime freedom to do adaptive automatic load-balancing, cluster rebalancing, replication & partitioning
This document summarizes advanced Akka features presented by Martin Kanters and Johan Janssen. It covers local and remote actors, scheduling, clustering, routing, cluster singletons, sharding, persistence, Akka HTTP, and finite state machines. The presentation introduces these features and provides examples to illustrate how they can be used with Akka.
This document discusses using Akka and actors for building scalable and concurrent applications in Scala. It introduces actors as fundamental units of computation that communicate asynchronously via message passing. Akka provides tools for creating actor systems and hierarchies. The document uses a monitoring application called Scotchdog as an example, with actors to represent services that are monitored by a watchdog actor. It describes how messages are used to start, stop and check services, and how the watchdog can aggregate status from child actors. The document also briefly mentions using Akka's scheduler and finite state machines to implement more complex actor behaviors.
Java EE 6 CDI Integrates with Spring & JSFJiayun Zhou
This document discusses integrating Java Contexts and Dependency Injection (CDI) with other Java technologies like Spring and JavaServer Faces (JSF). It covers CDI concepts like the Inversion of Control pattern and dependency injection. It also provides examples of using CDI with Spring, integrating CDI and JSF, and using CDI interceptors. The document recommends some libraries for CDI integration and provides sample code links.
A presentation at Twitter's official developer conference, Chirp, about why we use the Scala programming language and how we build services in it. Provides a tour of a number of libraries and tools, both developed at Twitter and otherwise.
Proper distribution of functionalities throughout many machines is very hard, especially when we leave those decisions for later. Akka toolkit gives us many tools for scaling out and we can start using them very early in a development process, enhancing our chances of success. In this introductory talk, I want to go through a very simple example and show snippets of single-noded and sharded implementations.
This document provides an overview of Celery, an open-source distributed task queue written in Python. It discusses what Celery is used for, its core architecture including brokers, tasks, workers, and monitoring. It also covers key Celery concepts like signatures, tasks workflows using groups, chains, chords, maps and more. The document explains how to define and call tasks, and configure workers with options like autoreloading, autoscaling, rate limits, and user components. Monitoring is also covered, highlighting the Flower web monitor for task progress and statistics.
This document provides an overview of Akka in Scala, including terminology related to concurrency and parallelism, the actor model, life cycle of an actor, communication between actors, and a basic "Hello World" demo. Key points covered include:
- Definitions of concurrency, parallelism, synchronous/asynchronous, blocking/non-blocking, and race conditions.
- The actor model as a new paradigm for concurrent programming where actors communicate asynchronously via message passing.
- An actor has its own state and behavior, and processes one message at a time.
- Akka is an implementation of the actor model for JVM languages that provides fault tolerance, location transparency, and scalability.
- Act
This document discusses building an "Internet of Trains" project using LEGO trains controlled over WiFi. It describes connecting Raspberry Pis to LEGO trains using infrared transmitters and switches. An Android/web application allows controlling the trains remotely. Challenges included coordinating the distributed system, which the authors addressed using Scala and Akka actors for remote communication between devices. Performance tests showed remote actors had faster response times than HTTP for this real-time control application.
This document discusses using Celery and RabbitMQ to handle asynchronous and distributed tasks in Python. It provides an overview of Celery and RabbitMQ and how they can be used together. Examples are given of defining and running tasks, including periodic tasks, task sets, routing, retries, and interacting with results. The benefits of using Celery for slow, memory-intensive, or externally-dependent tasks are highlighted.
The dark side of Akka and the remedy - bp.scala meetupkrivachy
The document discusses the problems with using Akka actors and proposes solutions using FSM and futures instead of actors for some cases. It describes issues with actors like lack of type safety, mutable state leading to complex code, and difficult debugging. FSMs are presented as a better solution by enforcing state transitions and logging. Futures are also suggested for cases without need for location transparency or real-time data flow that actors provide. The conclusion is that Akka requires a new mindset and can cause headaches if overused, so it's best to only use actors when truly needed.
2014-02-20 | Akka Concurrency (Vienna Scala User Group)Dominik Gruber
The document summarizes a presentation about the book "Akka Concurrency" by Derek Wyatt. It provides an overview of the book's content including chapters on actors, testing, routing messages, dataflow concurrency and examples of stateful actors and using the finite state machine pattern. It also notes that while the book provides an exhaustive overview of Akka, it is based on an older version of Akka and does not cover newer features like clustering and persistence.
A short introduction (with many examples) to the Scala programming language and also an introduction to using the Play! Framework for modern, safe, efffcient and reactive web applications.
This document discusses Akka futures and remote actors. It covers how to use futures to retrieve results asynchronously from actors or directly. It also describes how to enable remote capabilities in an Akka project, how to create remote actors, and how to look up remote actors. Functional composition of futures using map, filter, and for comprehensions is also covered.
Asynchronous web apps with the Play Framework 2.0Oscar Renalias
This document discusses Play's asynchronous capabilities for building scalable and responsive web applications. It begins by explaining the traditional blocking request processing model and Play's asynchronous non-blocking model. It then covers asynchronous requests using Futures and Promises in Play. Examples are provided for making actions asynchronous using asynchronous responses. The document also discusses reactive IO in Play using Enumerators and Iteratees for non-blocking streaming of data. Real world use cases for asynchronous programming include asynchronous web services, streaming files and data, and websockets.
This document provides an overview of the Web Server Gateway Interface (WSGI) specification and its components. WSGI defines the interface between web servers and web applications to allow them to evolve independently. It outlines the operations and responses expected between servers and applications. WSGI allows for easy integration of middleware components into applications and servers. Common Python web servers, frameworks, and middleware examples are also described to demonstrate how WSGI enables components to work together.
The fundamentals and advance application of Node will be covered. We will explore the design choices that make Node.js unique, how this changes the way applications are built and how systems of applications work most effectively in this model. You will learn how to create modular code that’s robust, expressive and clear. Understand when to use callbacks, event emitters and streams.
Akka and the Zen of Reactive System DesignLightbend
In order to be successful with asynchronous programming, when coming from synchronous execution models you need to change your mindset and look at things from a slightly different perspective. In order to use Akka at it's best, you will have to change the way you think about application design (loosen coupling in space and time between components), and re-think what you've maybe learned in the past.
In this talk we uncover a number of rules that serve as a guide in designing concurrent distributed applications, how those apply to Akka, and how they can help you in daily app development.
Aimed at developers through architects, Akka team happy hAkker, Konrad Malawski, bends your parameters with regards to application design and asynchronous execution models.
Over the past few years, web-applications have started to play an increasingly important role in our lives. We expect them to be always available and the data to be always fresh. This shift into the realm of real-time data processing is now transitioning to physical devices, and Gartner predicts that the Internet of Things will grow to an installed base of 26 billion units by 2020.
Reactive web-applications are an answer to the new requirements of high-availability and resource efficiency brought by this rapid evolution. On the JVM, a set of new languages and tools has emerged that enable the development of entirely asynchronous request and data handling pipelines. At the same time, container-less application frameworks are gaining increasing popularity over traditional deployment mechanisms.
This talk is going to give you an introduction into one of the most trending reactive web-application stack on the JVM, involving the Scala programming language, the concurrency toolkit Akka and the web-application framework Play. It will show you how functional programming techniques enable asynchronous programming, and how those technologies help to build robust and resilient web-applications.
WSGI is a specification for connecting HTTP servers to web applications through a common interface. It defines an application as a callable object that receives environment variables from the server and returns a response. WSGI also supports middleware as callable objects that can process requests and responses between the server and application.
This presentation deals with a complex approach to application testing in back end and front end parts, tests writing and common mistakes. It also includes a short overview of libraries and frameworks for creation of tests, as well as practical examples of code.
Presentation by Pavlo Iuriichuk, Lead Software Engineer, GlobalLogic, Kyiv), delivered at an open techtalk on December 11, 2014.
More details - http://globallogic.com.ua/report-web-testing-techtalk-2014
Celery is an open source asynchronous task queue/job queue based on distributed message passing. It allows tasks to be executed concurrently, in the background across multiple servers. Common use cases include running long tasks like API calls or image processing without blocking the main process, load balancing tasks across servers, and concurrent execution of batch jobs. Celery uses message brokers like RabbitMQ to asynchronously queue and schedule tasks. Tasks are defined as Python functions which get executed by worker processes. The workflow involves defining tasks, adding tasks to the queue from views or management commands, and having workers process the tasks.
Celery is a really good framework for doing background task processing in Python (and other languages). While it is ridiculously easy to use celery, doing complex task flow has been a challenge in celery. (w.r.t task trees/graphs/dependecies etc.)
This talk introduces the audience to these challenges in celery and also explains how these can be fixed programmatically and by using latest features in Celery (3+)
Slides from http://www.meetup.com/Reactive-Systems-Hamburg/events/232887060
Barys and Simon talked about Akka Cluster. Cluster Sharding allows to transparently distribute work in an Akka cluster with automatic balancing, migration of workers and automatic restart in case of errors. Cluster PubSub offers the publish/subscribe pattern. Akka Distributed Data offers eventually consistent data structures across the cluster, that allow for keeping the cluster's state.
They talked about the Akka Modules and explained how they interplay. Finally, they shared what Risk.Ident have learned running a reactive application based on Akka Cluster in production for almost a year.
This document provides an overview of Akka in Scala, including terminology related to concurrency and parallelism, the actor model, life cycle of an actor, communication between actors, and a basic "Hello World" demo. Key points covered include:
- Definitions of concurrency, parallelism, synchronous/asynchronous, blocking/non-blocking, and race conditions.
- The actor model as a new paradigm for concurrent programming where actors communicate asynchronously via message passing.
- An actor has its own state and behavior, and processes one message at a time.
- Akka is an implementation of the actor model for JVM languages that provides fault tolerance, location transparency, and scalability.
- Act
This document discusses building an "Internet of Trains" project using LEGO trains controlled over WiFi. It describes connecting Raspberry Pis to LEGO trains using infrared transmitters and switches. An Android/web application allows controlling the trains remotely. Challenges included coordinating the distributed system, which the authors addressed using Scala and Akka actors for remote communication between devices. Performance tests showed remote actors had faster response times than HTTP for this real-time control application.
This document discusses using Celery and RabbitMQ to handle asynchronous and distributed tasks in Python. It provides an overview of Celery and RabbitMQ and how they can be used together. Examples are given of defining and running tasks, including periodic tasks, task sets, routing, retries, and interacting with results. The benefits of using Celery for slow, memory-intensive, or externally-dependent tasks are highlighted.
The dark side of Akka and the remedy - bp.scala meetupkrivachy
The document discusses the problems with using Akka actors and proposes solutions using FSM and futures instead of actors for some cases. It describes issues with actors like lack of type safety, mutable state leading to complex code, and difficult debugging. FSMs are presented as a better solution by enforcing state transitions and logging. Futures are also suggested for cases without need for location transparency or real-time data flow that actors provide. The conclusion is that Akka requires a new mindset and can cause headaches if overused, so it's best to only use actors when truly needed.
2014-02-20 | Akka Concurrency (Vienna Scala User Group)Dominik Gruber
The document summarizes a presentation about the book "Akka Concurrency" by Derek Wyatt. It provides an overview of the book's content including chapters on actors, testing, routing messages, dataflow concurrency and examples of stateful actors and using the finite state machine pattern. It also notes that while the book provides an exhaustive overview of Akka, it is based on an older version of Akka and does not cover newer features like clustering and persistence.
A short introduction (with many examples) to the Scala programming language and also an introduction to using the Play! Framework for modern, safe, efffcient and reactive web applications.
This document discusses Akka futures and remote actors. It covers how to use futures to retrieve results asynchronously from actors or directly. It also describes how to enable remote capabilities in an Akka project, how to create remote actors, and how to look up remote actors. Functional composition of futures using map, filter, and for comprehensions is also covered.
Asynchronous web apps with the Play Framework 2.0Oscar Renalias
This document discusses Play's asynchronous capabilities for building scalable and responsive web applications. It begins by explaining the traditional blocking request processing model and Play's asynchronous non-blocking model. It then covers asynchronous requests using Futures and Promises in Play. Examples are provided for making actions asynchronous using asynchronous responses. The document also discusses reactive IO in Play using Enumerators and Iteratees for non-blocking streaming of data. Real world use cases for asynchronous programming include asynchronous web services, streaming files and data, and websockets.
This document provides an overview of the Web Server Gateway Interface (WSGI) specification and its components. WSGI defines the interface between web servers and web applications to allow them to evolve independently. It outlines the operations and responses expected between servers and applications. WSGI allows for easy integration of middleware components into applications and servers. Common Python web servers, frameworks, and middleware examples are also described to demonstrate how WSGI enables components to work together.
The fundamentals and advance application of Node will be covered. We will explore the design choices that make Node.js unique, how this changes the way applications are built and how systems of applications work most effectively in this model. You will learn how to create modular code that’s robust, expressive and clear. Understand when to use callbacks, event emitters and streams.
Akka and the Zen of Reactive System DesignLightbend
In order to be successful with asynchronous programming, when coming from synchronous execution models you need to change your mindset and look at things from a slightly different perspective. In order to use Akka at it's best, you will have to change the way you think about application design (loosen coupling in space and time between components), and re-think what you've maybe learned in the past.
In this talk we uncover a number of rules that serve as a guide in designing concurrent distributed applications, how those apply to Akka, and how they can help you in daily app development.
Aimed at developers through architects, Akka team happy hAkker, Konrad Malawski, bends your parameters with regards to application design and asynchronous execution models.
Over the past few years, web-applications have started to play an increasingly important role in our lives. We expect them to be always available and the data to be always fresh. This shift into the realm of real-time data processing is now transitioning to physical devices, and Gartner predicts that the Internet of Things will grow to an installed base of 26 billion units by 2020.
Reactive web-applications are an answer to the new requirements of high-availability and resource efficiency brought by this rapid evolution. On the JVM, a set of new languages and tools has emerged that enable the development of entirely asynchronous request and data handling pipelines. At the same time, container-less application frameworks are gaining increasing popularity over traditional deployment mechanisms.
This talk is going to give you an introduction into one of the most trending reactive web-application stack on the JVM, involving the Scala programming language, the concurrency toolkit Akka and the web-application framework Play. It will show you how functional programming techniques enable asynchronous programming, and how those technologies help to build robust and resilient web-applications.
WSGI is a specification for connecting HTTP servers to web applications through a common interface. It defines an application as a callable object that receives environment variables from the server and returns a response. WSGI also supports middleware as callable objects that can process requests and responses between the server and application.
This presentation deals with a complex approach to application testing in back end and front end parts, tests writing and common mistakes. It also includes a short overview of libraries and frameworks for creation of tests, as well as practical examples of code.
Presentation by Pavlo Iuriichuk, Lead Software Engineer, GlobalLogic, Kyiv), delivered at an open techtalk on December 11, 2014.
More details - http://globallogic.com.ua/report-web-testing-techtalk-2014
Celery is an open source asynchronous task queue/job queue based on distributed message passing. It allows tasks to be executed concurrently, in the background across multiple servers. Common use cases include running long tasks like API calls or image processing without blocking the main process, load balancing tasks across servers, and concurrent execution of batch jobs. Celery uses message brokers like RabbitMQ to asynchronously queue and schedule tasks. Tasks are defined as Python functions which get executed by worker processes. The workflow involves defining tasks, adding tasks to the queue from views or management commands, and having workers process the tasks.
Celery is a really good framework for doing background task processing in Python (and other languages). While it is ridiculously easy to use celery, doing complex task flow has been a challenge in celery. (w.r.t task trees/graphs/dependecies etc.)
This talk introduces the audience to these challenges in celery and also explains how these can be fixed programmatically and by using latest features in Celery (3+)
Slides from http://www.meetup.com/Reactive-Systems-Hamburg/events/232887060
Barys and Simon talked about Akka Cluster. Cluster Sharding allows to transparently distribute work in an Akka cluster with automatic balancing, migration of workers and automatic restart in case of errors. Cluster PubSub offers the publish/subscribe pattern. Akka Distributed Data offers eventually consistent data structures across the cluster, that allow for keeping the cluster's state.
They talked about the Akka Modules and explained how they interplay. Finally, they shared what Risk.Ident have learned running a reactive application based on Akka Cluster in production for almost a year.
This document provides an introduction to Akka.Cluster, including defining what a cluster is, the benefits of clustering, how to enable clustering in an application, and examples of using clusters. It describes how clusters are formed and maintain themselves, including initial node discovery, leader election, and ring formation. Location transparency is discussed, where the physical location of actors does not impact functionality.
The document describes how to define and create an actor using Akka. It defines a Greeting message class and GreetingActor class that extends UntypedActor. The GreetingActor behavior logs a greeting message when it receives a Greeting. An ActorSystem is created, and a greeter ActorRef is obtained by passing the GreetingActor class and a name to the system's actorOf method.
This document provides an introduction to Akka actors. It discusses how actors provide a model for building concurrent and distributed applications by avoiding shared mutable state and instead using message passing. Actors communicate asynchronously by message passing and handle errors through a supervision hierarchy. The document outlines several features of the actor model including load balancing, parallelization, and error handling.
The actor model provides simple concurrency, resiliency, and elasticity through processing messages sequentially between actors that have no shared state. Actors receive and respond to messages to define their behavior, and can create other actors within the actor system. Key aspects include that actors are not threads, messages are processed sequentially, multiple actors can work concurrently, and exception handling is done through hierarchical supervisor strategies.
This document provides an overview of Akka and Akka Cluster, frameworks for building distributed and fault-tolerant applications using actors. It discusses concurrency paradigms like message passing actors, Akka's implementation of the actor model, clustering with Akka Cluster, and using CRDTs for distributed shared state. It also previews demos of building a web crawler application and clustering it across nodes with Akka Cluster.
Akka Cluster allows distributing actors across multiple JVMs with no single point of failure. The document discusses challenges faced with unreachable members and journal lifecycles when operating an Akka Cluster application at scale for 10 months. For unreachables, triggering a scale-in to mark nodes as down and automating restarts addressed the issue. Journals stored in Redis required cleanup to avoid inconsistencies, as deleting messages did not remove the highest sequence number. Straying from event sourcing's complete event history model weakened ecosystem support.
The document introduces Akka, an open-source toolkit for building distributed, concurrent applications on the JVM. It provides a programming model called the actor model that makes it easier to build scalable and fault-tolerant systems. Actors process messages asynchronously and avoid shared state, providing a simpler approach to concurrency than traditional threads and locks. Akka allows actors to be distributed across a network, enabling applications to scale out elastically.
Akka persistence == event sourcing in 30 minutesKonrad Malawski
Akka 2.3 introduces akka-persistence, a wonderful way of implementing event-sourced applications. Let's give it a shot and see how DDD and Akka are a match made in heaven :-)
The document discusses various concurrency models including shared state concurrency, message passing concurrency using actors, and software transactional memory. Shared state concurrency uses locking to synchronize access to shared resources but is prone to issues like race conditions and deadlocks. Message passing concurrency avoids these issues by isolating actors and having them communicate asynchronously through message passing without shared state. The actor model is implemented in several JVM languages including Scala, Groovy, and Java libraries. Software transactional memory provides an alternative to locking by allowing transactions to access shared memory in an isolated and atomic manner.
Next generation message driven systems with AkkaJohan Andrén
The document provides an overview and examples of Akka Typed, the next generation of Akka focused on type safety. It introduces key Akka Typed concepts like actors, behaviors, and messages. It then provides two sample programs to demonstrate basic actor messaging in Akka Typed: a "hello world" example and an example that shows how an actor's behavior can change dynamically based on messages received. The samples are shown in both Java and Scala to illustrate the language agnostic nature of Akka Typed.
JavaScript is evolving with the addition of modules, platform consistency, and harmony features. Modules allow JavaScript code to be organized and avoid naming collisions. CommonJS and AMD module formats are used widely. Platform consistency is improved through polyfills that mimic future APIs for older browsers. Harmony brings language-level modules and features like destructuring assignment, default parameters, and promises to JavaScript. Traceur compiles Harmony code to existing JavaScript.
While most bugs reveal their cause within their stack trace, Java’s OutOfMemoryError is less talkative and therefore regarded as being difficult to debug by a majority of developers. With the right techniques and tools, memory leaks in Java programs can however be tackled like any other programming error. This talks discusses how a JVM stores data, categorizes different types of memory leaks that can occur in a Java program and presents techniques for fixing such errors. Furthermore, we will have a closer look at lambda expressions and their considerable potential of introducing memory leaks when they are used incautiously.
The document discusses the future of server-side JavaScript. It covers various Node.js frameworks and libraries that support both synchronous and asynchronous programming styles. CommonJS aims to provide interoperability across platforms by implementing synchronous proposals using fibers. Examples demonstrate how CommonJS allows for synchronous-like code while maintaining asynchronous behavior under the hood. Benchmarks show it has comparable performance to Node.js. The author advocates for toolkits over frameworks and continuing development of common standards and packages.
In a world where users have ever higher expectations from the apps they use, having data always available, even when the device is offline, has become increasingly important.
In this talk you will learn how thinking "offline first" not only makes your app architecture better but also result in cleaner code and happier users.
I will introduce Realm, a new database for easy persistence, and demonstrate how it enables truly reactive UI's by fitting seamlessly into the standard network stack of Retrofit and RxJava.
Finally we will take a look at the new Realm Mobile Platform, which provides real-time synchronization between devices, enabling features previously out of reach for many development teams.
How and why i roll my own node.js frameworkBen Lin
1) The document discusses the author's experience building their own node.js web framework, including their background with other technologies like Ruby on Rails.
2) It describes the key features of their framework, such as MVC structure, middleware support, asset packaging, and command line tools.
3) The author explains that they rolled their own framework to learn more about how frameworks work, have more control over the technology stack, and because node.js performance is better than Ruby on Rails. They emphasize that building the framework was a fun learning experience.
This document describes how to virtualize Java applications in Java by hosting multiple "pseudo JVMs" within a single JVM. This allows deploying distributed applications for testing purposes. Key points covered include:
- Using custom classloaders and system properties to isolate "pseudo JVMs" and simulate distributed environments.
- Frameworks like GridKit that enable starting whole application topologies within JUnit tests for behaviors testing.
- Techniques for testing features like serialization, data routing, and cross-version compatibility.
- Later extensions to deploy virtual nodes across real servers using SSH for performance and deployment testing of distributed systems.
Play Framework and Ruby on Rails are web application frameworks that help developers build web applications. Both frameworks provide tools and libraries for common tasks like routing, database access, templates and more. Some key similarities include using MVC patterns, supporting SQL/NoSQL databases via libraries, and including tools for unit testing and deployment. Some differences are Play uses Scala and Java while Rails uses Ruby, and they have different project structures and ways of handling assets, templates and dependencies. Both aim to help developers build web applications faster with their features and ecosystem of supporting libraries.
The document summarizes Dmitry Soshnikov's presentation on ECMAScript 6 features at the HelsinkiJS meetup on December 12, 2011. Key features discussed include default function parameters, modules system, quasi-literals for string templates, array comprehensions, maps and weak maps, destructuring assignment, rest operator for function arguments, proxy objects for meta programming, and struct types.
This is my presentation from TechBeats #3 hosted by Applause about Server-Side Swift framework called Vapor.
Swift is a great language and possibility of using it also in backend is a huge benefit for any iOS developer out there. Using Vapor is a seamless experience. With this framework creating advance APIs by iOS developer is as easy as writing simple iOS app.
https://www.meetup.com/TechBeats-hosted-by-Applause/events/254910023/
Threads, Queues, and More: Async Programming in iOSTechWell
To keep your iOS app running butter-smooth at 60 frames per second, Apple recommends doing as many tasks as possible asynchronously or “off the main thread.” Joe Keeley introduces you to some basic concepts of asynchronous programming in iOS. He discusses what threads and queues are, how they are related, and the special significance of the main queue to iOS. Look at what options are available in the iOS SDK to work asynchronously, including NSOperationQueues and Grand Central Dispatch. Take an in depth look at how to implement some common use cases for those options in Swift. Joe pays special attention to networking, one of the most common asynchronous use cases. Spend some time discussing common asynchronous programming pitfalls—and how to avoid them. Leave this session ready to try out asynchronous programming in your iOS app.
Play 2.0 is a web framework for Java and Scala that is designed to be productive, asynchronous, and reactive. Some key features include being full stack, high-productive, asynchronous and reactive, stateless, HTTP-centric, typesafe, scalable, and open source. Play 2.0 aims to be fun and fast to develop with by enabling features like hot code reloading, browser error reporting, and easy deployment to platforms like Heroku. It also focuses on being asynchronous and reactive through support for WebSockets, Comet, HTTP streaming responses, and composable streams.
Clojure is a Lisp dialect that runs on the Java Virtual Machine (JVM) and provides excellent concurrency support and tight integration with Java. It retains the advantages of Lisp such as being simple, expressive, and flexible while also allowing access to existing Java code and libraries. Clojure makes concurrency easy through features like transactional memory and agents. It can be used to create both Java and Clojure libraries and extends the Java platform.
Fast Web Applications Development with Ruby on Rails on OracleRaimonds Simanovskis
This document provides an overview of Ruby on Rails and how it can be used to develop fast web applications with an Oracle database backend. It discusses key Rails concepts like MVC architecture and Active Record. It also demonstrates how to connect Rails to Oracle using gems like ruby-oci8, activerecord-oracle_enhanced-adapter, and ruby-plsql to access Oracle data types, stored procedures, and full-text search capabilities. The document concludes with deployment options and pointers to related sessions.
The document discusses reactive application patterns and principles. It describes how Akka actors can be used to build message-driven, resilient, elastic, and responsive applications. It provides an example of using Play, Akka Cluster Sharding to build a reactive user management system that is horizontally scalable and always available.
The document provides an overview of Groovy and Java code examples for performing common tasks like printing "Hello World", reading files, making web requests, using strings, importing packages, and using Swing/SwingBuilder for GUIs. It also shows examples of using Groovy with Java libraries for Excel files, Ant, and JSON. Additional sections cover parallel processing with GPars, contract programming with GContracts, method chaining, Grails basics, and Gaelyk controllers and views.
apidays LIVE Australia 2020 - Building distributed systems on the shoulders o...apidays
apidays LIVE Australia 2020 - Building Business Ecosystems
Building distributed systems on the shoulders of giants
Dasith Wijesiriwardena, Telstra Purple (Readify)
10 Excellent Ways to Secure Spring Boot Applications - Okta Webinar 2020Matt Raible
Spring Boot is an efficient way to build Java applications with the Spring Framework. If you’re developing apps that handle sensitive data, you should make sure they’re secure.
This session will cover HTTPS, dependency checking, CSRF, using a CSP to prevent XSS, OIDC, password hashing, and much more!
You’ll learn how to add these features to a real application, using the Java language you know and love.
* Blog post: https://developer.okta.com/blog/2018/07/30/10-ways-to-secure-spring-boot
* Cheat sheet: https://snyk.io/blog/spring-boot-security-best-practices/
* OIDC demo: http://bit.ly/spring-oidc-demo
Hacking JavaFX with Groovy, Clojure, Scala, and Visage: Stephen Chinjaxconf
JavaFX 2 is the next version of a revolutionary rich client platform for developing immersive desktop applications. One of the new features in JavaFX 2 is a set of pure Java APIs that can be used from any JVM language, opening up tremendous possibilities. This presentation demonstrates the potential of using JavaFX 2 together with alternative languages such as Groovy, Clojure, and Scala. It also will showcase the successor to JavaFX Script, Visage, a DSL with features specifically targeted at helping create clean UIs.
This document discusses creating a custom Spring Initializr for teams. It begins with background on Heroku and Spring Initializr. It then discusses using the initializr-generator to configure a custom Initializr and deploying it. The talk concludes with a question and answer section and thanks the audience. The custom Initializr allows teams to generate Spring Boot projects with their preferred dependencies and configurations.
This document provides an overview of Spring Boot and some of its key features. It discusses the origins and modules of Spring, how Spring Boot simplifies configuration and dependency management. It then covers examples of building Spring Boot applications that connect to a SQL database, use RabbitMQ for messaging, and schedule and run asynchronous tasks.
The document discusses Spring and Hibernate frameworks. It provides an overview of Hibernate's object-relational mapping capabilities and how it can be used to map Java objects to database tables. It also describes Spring's inversion of control and dependency injection features. The document outlines how Spring and Hibernate can be integrated together for data access in applications. It provides examples of configuration, transaction management, and security integration between the two frameworks.
The document provides style guidelines for Python code, including recommendations for semicolons, line length, indentation, whitespace, comments, imports, exceptions, naming conventions, and other stylistic elements. It derives many of the guidelines from Google's and PEP 8's Python style guides, with the goal of writing clear, readable, and consistent Python code.
This document provides an overview of key Python concepts including:
- Identifiers name variables, types, functions, packages etc.
- Data types include numbers, strings, lists, tuples, dictionaries, sets and more.
- Control flow statements like if/else and for loops are used without braces.
- Functions are defined using the def keyword and can return values.
- Modules provide useful functionality like datetime and can be imported.
- Python supports OOP with classes, inheritance and methods.
- Common libraries are included for tasks like web development, databases and more.
The document discusses refactoring and improving existing code. It describes how the Eclipse IDE has been refactored and improved over multiple versions from 1.0 to 3.7. It also discusses common code smells like duplicated code, long methods, large classes, and long parameter lists that indicate needs for refactoring. Various refactoring techniques are presented, such as extracting methods, extracting classes, replacing parameters with method calls, and introducing parameter objects. The importance of unit testing during refactoring is also emphasized.
Andrew Marnell: Transforming Business Strategy Through Data-Driven InsightsAndrew Marnell
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𝙄𝙨 𝘼𝙄 𝙟𝙪𝙨𝙩 𝙝𝙮𝙥𝙚? 𝙊𝙧 𝙞𝙨 𝙞𝙩 𝙩𝙝𝙚 𝙜𝙖𝙢𝙚 𝙘𝙝𝙖𝙣𝙜𝙚𝙧 𝙮𝙤𝙪𝙧 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙣𝙚𝙚𝙙𝙨?
Everyone’s talking about AI but is anyone really using it to create real value?
Most companies want to leverage AI. Few know 𝗵𝗼𝘄.
✅ What exactly should you ask to find real AI opportunities?
✅ Which AI techniques actually fit your business?
✅ Is your data even ready for AI?
If you’re not sure, you’re not alone. This is a condensed version of the slides I presented at a Linkedin webinar for Tecnovy on 28.04.2025.
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Procurement Insights integrated Historic Procurement Industry Archives, serves as a powerful complement — not a competitor — to other procurement industry firms. It fills critical gaps in depth, agility, and contextual insight that most traditional analyst and association models overlook.
Learn more about this value- driven proprietary service offering here.
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This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
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-Artificial Intelligence Market Overview
-Strategies for AI Adoption in 2025
-Anticipated drivers of AI adoption and transformative technologies
-Benefits of AI and Big data for your business
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-AI and data privacy: Strategies for securing data privacy in AI models, etc.
Download your free copy nowand implement the key findings to improve your business.
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Precision in data labeling = Precision on the production floor.
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
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-AI and data privacy: Key findings
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HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/
HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client.
Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience.
In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including
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Designing Low-Latency Systems with Rust and ScyllaDB: An Architectural Deep DiveScyllaDB
Want to learn practical tips for designing systems that can scale efficiently without compromising speed?
Join us for a workshop where we’ll address these challenges head-on and explore how to architect low-latency systems using Rust. During this free interactive workshop oriented for developers, engineers, and architects, we’ll cover how Rust’s unique language features and the Tokio async runtime enable high-performance application development.
As you explore key principles of designing low-latency systems with Rust, you will learn how to:
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Toradex brings robust Linux support to SMARC (Smart Mobility Architecture), ensuring high performance and long-term reliability for embedded applications. Here’s how:
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• Secure and Reliable – With Secure Boot, over-the-air (OTA) updates, and LTS kernel support, Toradex ensures industrial-grade security and longevity.
• Containerized Workflows for AI & IoT – Support for Docker, ROS, and real-time Linux enables scalable AI, ML, and IoT applications.
• Strong Ecosystem & Developer Support – Toradex offers comprehensive documentation, developer tools, and dedicated support, accelerating time-to-market.
With Toradex’s Linux support for SMARC, developers get a scalable, secure, and high-performance solution for industrial, medical, and AI-driven applications.
Do you have a specific project or application in mind where you're considering SMARC? We can help with Free Compatibility Check and help you with quick time-to-market
For more information: https://www.toradex.com/computer-on-modules/smarc-arm-family
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc
Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency.
This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data.
Attendees will learn:
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- How businesses assess third-party vendors and their consent management operations
- Where business preparedness needs improvement
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24. Local Main
public static void main(String[] args) throws
Exception {
ActorSystem _system =
ActorSystem.create("LocalNodeApp",ConfigFactory
.load().getConfig("LocalSys"));
ActorRef localActor =
_system.actorOf(Props.create(LocalActor.class));
localActor.tell("Hello", null);
Thread.sleep(5000);
_system.shutdown();
}
25. Local Actor
ActorRef remoteActor;
@Override
public void preStart() {
//Get a reference to the remote actor
remoteActor = getContext().actorFor(
"akka.tcp://[email protected]:2552/user/remoteActor"
);
}
@Override
public void onReceive(Object message) throws Exception {
Future<Object> future = Patterns.ask(remoteActor,
message.toString(),
timeout);
String result = (String) Await.result(future,
timeout.duration());
log.info("Message received from Server -> {}", result);
}
27. Remote Main
public static void main(String[] args) {
final ActorSystem system =
ActorSystem.create("RemoteNodeApp", ConfigFactory
.load().getConfig("RemoteSys"));
system.actorOf(Props.create(RemoteActor.class),
"remoteActor");
Runtime.getRuntime().addShutdownHook(new Thread()
{
@Override
public void run() {
system.shutdown();
}
});
}
28. Remote Actor
@Override
public void onReceive(Object message) throws
Exception {
if (message instanceof String) {
// Get reference to the message sender and
reply back
log.info("Message received -> {}", message);
getSender().tell(message + " got something",
null);
}
}
36. Backend Main
public static void main(String[] args) {
// Override the configuration of the port when specified as
program argument
final String hostname = args.length > 0 ? args[0] : "127.0.0.1";
final String port = args.length > 1 ? args[1] : "0";
final Config config =
ConfigFactory.parseString("akka.remote.netty.tcp.hostname=" +
hostname).
withFallback(ConfigFactory.parseString("akka.remote.netty.tcp.port="
+ port)).
withFallback(ConfigFactory.parseString("akka.cluster.roles =
[backend]")).
withFallback(ConfigFactory.load());
ActorSystem system = ActorSystem.create("ClusterSystem", config);
system.actorOf(Props.create(TransformationBackend.class),
"backend");
}
37. Backend Actor - 1
Cluster cluster = Cluster.get(getContext().system());
//subscribe to cluster changes, MemberUp
@Override
public void preStart() {
cluster.subscribe(getSelf(), MemberUp.class);
}
//re-subscribe when restart
@Override
public void postStop() {
cluster.unsubscribe(getSelf());
}
void register(Member member) {
if (member.hasRole("frontend"))
getContext().actorSelection(member.address() +
"/user/frontend").tell(
BACKEND_REGISTRATION, getSelf());
}
38. Backend Actor - 2
@Override
public void onReceive(Object message) {
if (message instanceof TransformationJob) {
TransformationJob job = (TransformationJob) message;
getSender().tell(new
TransformationResult(job.getText().toUpperCase()),
getSelf());
} else if (message instanceof CurrentClusterState) {
CurrentClusterState state = (CurrentClusterState) message;
for (Member member : state.getMembers()) {
if (member.status().equals(MemberStatus.up())) {
register(member);
}
}
} else if (message instanceof MemberUp) {
MemberUp mUp = (MemberUp) message;
register(mUp.member());
} else {
unhandled(message);
}
}
39. Frontend Main - 1
final String hostname = args.length > 0 ? args[0] :
"127.0.0.1";
final String port = args.length > 1 ? args[1] : "0";
final Config config =
ConfigFactory.parseString("akka.remote.netty.tcp.host
name=" + hostname).
withFallback(ConfigFactory.parseString("akka.remote.n
etty.tcp.port=" + port)).
withFallback(ConfigFactory.parseString("akka.cluster.
roles = [frontend]")).
withFallback(ConfigFactory.load());
ActorSystem system =
ActorSystem.create("ClusterSystem", config);
40. Frontend Main - 2
final ActorRef frontend = system.actorOf(
Props.create(TransformationFrontend.class),
"frontend");
…
system.scheduler().schedule(interval, interval, new
Runnable() {
public void run() {
Patterns.ask(frontend,
new TransformationJob("hello-" +
counter.incrementAndGet()),
timeout).onSuccess(new OnSuccess<Object>()
{
public void onSuccess(Object result) {
System.out.println(result);
}
}, ec);
}
}, ec);
41. Frontend Actor - 1
List<ActorRef> backends = new ArrayList<ActorRef>();
int jobCounter = 0;
@Override
public void onReceive(Object message) {
if ((message instanceof TransformationJob) &&
backends.isEmpty()) {
TransformationJob job = (TransformationJob)
message;
getSender().tell(
new JobFailed("Service unavailable, try again
later", job),
getSender());
57. Frontend Main
final int upToN = 200;
final Config config = ConfigFactory.parseString(
"akka.cluster.roles = [frontend]").withFallback(
ConfigFactory.load("factorial"));
final ActorSystem system =
ActorSystem.create("ClusterSystem", config);
new
ZookeeperClusterSeed((ExtendedActorSystem)system).join();
Cluster.get(system).registerOnMemberUp(new Runnable() {
@Override
public void run() {
system.actorOf(Props.create(FactorialFrontend.class, upToN,
true),
"factorialFrontend");
}
});
58. Frontend Actor
ActorRef backend =
getContext().actorOf(FromConfig.getInstance().props(),
"factorialBackendRouter");
…
void sendJobs() {
log.info("Starting batch of factorials up to
[{}]", upToN);
for (int n = 1; n <= upToN; n++) {
backend.tell(n, getSelf());
}
}