This document introduces Akka, an open-source toolkit for building highly concurrent, distributed, and fault-tolerant event-driven applications on the JVM. It provides a single unified programming model based on actors that simplifies concurrency, scalability, and fault tolerance. Akka supports both Scala and Java APIs and can be deployed on single nodes or in a distributed, clustered environment in the cloud.
The document provides guidance on how to create and distribute Perl modules. It discusses what Perl modules are, why they are useful, and how to structure, write, test, and package a module for distribution. Key steps include using the h2xs tool to generate module scaffolding, writing the module code in the .pm file with best practices like strict and warnings, testing the module, and creating a compressed archive for distribution.
The document discusses the Android Debug Bridge (adb) tool which allows you to manage emulator and device instances. Adb includes a client, server, and daemon components. The client runs commands on your computer, the server manages communication between the client and device daemon. Adb allows you to install apps, forward ports, copy files, issue shell commands, and more. It provides a way to test and debug Android applications.
A presentation that tries to introduce some functional programming's core concepts in a more digestible way. It tries to stay away from all the complicated lingo and math, so the average developer can start his adventures through the dangerous but beautiful realms of functional programming.
This document provides an overview of the Symfony components created by Fabien Potencier. It describes that the components are standalone libraries for PHP 5.3 that have no dependencies between them. The components include Event Dispatcher, Output Escaper, YAML, Routing, Console, Dependency Injection Container, Request Handler, and Templating. The document discusses how to download and install the components via Git, SVN, or nightly builds. It also covers autoloading classes using the UniversalClassLoader and describes some of the individual components in more detail like Console, Routing, and Testing.
Streams are used in C++ for input/output (I/O) operations. The stream is the central concept of the iostream classes, which handle input from and output to external entities. There are different stream classes for different I/O needs, such as ostream for output streams, ifstream for input streams, and fstream for simultaneous input and output streams. Iterators and algorithms in the Standard Template Library (STL) allow containers like vectors to be used with I/O streams to read from and write to files.
Robot Framework is a generic test automation framework for acceptance testing and acceptance test-driven development (ATDD). It supports keyword-driven testing and can be extended with Python or Java. RF supports various test data formats, different test styles, flexible test organization, variables, custom keywords, test libraries, and more. It also has an active community and development.
The document provides an overview of the GIFT-VT tools framework. It describes the different levels and types of tools, the classes and inheritance used to implement tools, modules and services, how tools are executed by the server by loading the shared library and calling functions, and examples of tool configuration files and Makefiles.
A slightly deeper dive into StagefrightAlexy Joseph
This document provides an overview of Stagefright, the primary multimedia framework available on Android. It describes Stagefright's architecture and components, how it handles file playback, recording, and streaming. It also discusses hardware accelerated rendering, tweaking and optimizing Stagefright, and references additional resources. The document is presented by Alexy Mathew Joseph from Pathpartner and focuses on explaining how Stagefright works under the hood.
The document provides guidance on how to create and distribute Perl modules. It discusses what Perl modules are, why they are useful, and how to structure, write, test, and package a module for distribution. Key steps include using the h2xs tool to generate module scaffolding, writing the module code in the .pm file with best practices like strict and warnings, testing the module, and creating a compressed archive for distribution.
The document discusses the Android Debug Bridge (adb) tool which allows you to manage emulator and device instances. Adb includes a client, server, and daemon components. The client runs commands on your computer, the server manages communication between the client and device daemon. Adb allows you to install apps, forward ports, copy files, issue shell commands, and more. It provides a way to test and debug Android applications.
A presentation that tries to introduce some functional programming's core concepts in a more digestible way. It tries to stay away from all the complicated lingo and math, so the average developer can start his adventures through the dangerous but beautiful realms of functional programming.
This document provides an overview of the Symfony components created by Fabien Potencier. It describes that the components are standalone libraries for PHP 5.3 that have no dependencies between them. The components include Event Dispatcher, Output Escaper, YAML, Routing, Console, Dependency Injection Container, Request Handler, and Templating. The document discusses how to download and install the components via Git, SVN, or nightly builds. It also covers autoloading classes using the UniversalClassLoader and describes some of the individual components in more detail like Console, Routing, and Testing.
Streams are used in C++ for input/output (I/O) operations. The stream is the central concept of the iostream classes, which handle input from and output to external entities. There are different stream classes for different I/O needs, such as ostream for output streams, ifstream for input streams, and fstream for simultaneous input and output streams. Iterators and algorithms in the Standard Template Library (STL) allow containers like vectors to be used with I/O streams to read from and write to files.
Robot Framework is a generic test automation framework for acceptance testing and acceptance test-driven development (ATDD). It supports keyword-driven testing and can be extended with Python or Java. RF supports various test data formats, different test styles, flexible test organization, variables, custom keywords, test libraries, and more. It also has an active community and development.
The document provides an overview of the GIFT-VT tools framework. It describes the different levels and types of tools, the classes and inheritance used to implement tools, modules and services, how tools are executed by the server by loading the shared library and calling functions, and examples of tool configuration files and Makefiles.
A slightly deeper dive into StagefrightAlexy Joseph
This document provides an overview of Stagefright, the primary multimedia framework available on Android. It describes Stagefright's architecture and components, how it handles file playback, recording, and streaming. It also discusses hardware accelerated rendering, tweaking and optimizing Stagefright, and references additional resources. The document is presented by Alexy Mathew Joseph from Pathpartner and focuses on explaining how Stagefright works under the hood.
Akka 2.0 allows actors to be distributed across multiple nodes in a cluster in a transparent manner. It introduces new concepts like actor addresses and deployment configurations. The clustering functionality leverages ZooKeeper for distributed coordination and stores serialized actor factories. This allows actors to be dynamically created, migrated, and replicated across nodes for fault tolerance and load balancing. Composable futures also allow combining results from multiple asynchronous messages.
Introduction to Akka, as presented on May 3 2012 at the Belgian Java User Group (BeJUG). For more details see: http://www.bejug.org/confluenceBeJUG/display/BeJUG/ForkJoin+and+Akka
Demo code can be found at: http://bit.ly/bejug-akka
The document provides an introduction to Akka, a toolkit for building highly concurrent, distributed, and resilient message-driven applications using the actor model on the JVM, describing how Akka implements the actor model with additional features and modules for clustering, remoting, streams, and more.
Василий Ременюк «Курс молодого подрывника» e-Legion
В своем докладе, на примере фреймвормка для нагрузочного тестирования многопользовательской онлайн-игры, Василий рассказал, как, следуя 4-ем простым советам, создать эффективную, асинхронную систему, используя модель актеров и Akka 2.0, уложиться в отведенные сроки, и, при этом, регулярно спать по-ночам больше 4 часов.
Václav Pech is the lead of GPars, a concurrency library for Groovy. He discusses how languages are becoming increasingly concurrent to take advantage of multi-core processors. GPars supports various concurrency constructs including asynchronous functions, actors, dataflow programming, and parallel collections. It aims to provide concurrency without complexity through a unified API that hides low-level concurrency details.
The document provides an overview of Akka actors and clustering. Some key points:
- Akka actors are reactive components that receive messages asynchronously via mailboxes. Each actor has a behavior and mutable state.
- Actors can be created and organized in hierarchies. Messages are sent between actors using paths like actor references.
- Clustering allows actors to be deployed across multiple nodes. The cluster uses gossip protocols and vector clocks to maintain membership and detect failures.
- Cluster features include failure detection, cluster-aware routers for load balancing, and deathwatch notifications when nodes fail. This enables fault tolerance and distribution of actor applications.
Akka is a toolkit for building highly concurrent, distributed, and fault-tolerant applications on the JVM. It provides actors as the fundamental unit of concurrency. Actors receive messages asynchronously and process them one at a time by applying behaviors. Akka uses a supervision hierarchy where actors monitor child actors and handle failures through configurable strategies like restart or stop. This provides clean separation of processing and error handling compared to traditional approaches.
"Walk in a distributed systems park with Orleans" Евгений БобровFwdays
Долгое время разработка производительных, масштабируемых, надежных и экономически эффективных распределенных систем, была прерогативой узкого круга специалистов. Переезд в «облако», сам по себе, проблему не решил. Обещанная провайдерами дешевая линейная масштабируемость, по-прежнему, недостижимая мечта для всех, сидящих «на игле» реляционных баз данных и монолитных архитектур.
С выходом Microsoft Orleans, разработчики, наконец-то, получили максимально простую и удобную платформу для создания масштабируемых и отказоустойчивых распределенных систем, предназначенных для запуска в «облаке» или в приватном дата-центре.
В докладе будут рассмотрены основные концепции и прецеденты использования платформы, такие как: Internet Of Things (IoT), распределенная обработка потоков данных, масштабирование РСУБД и любых других ограниченных ресурсов, отказоустойчивая координация длительно выполняющихся бизнес-процессов.
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.
Con-FESS 2015 - Having Fun With JavassistAnton Arhipov
This document discusses using Javassist, a bytecode manipulation library, for tasks like adding logging to existing code without modifying the source code. It provides examples of using Javassist to inject logging into a method and creating a Java agent to manipulate bytecode. The document also summarizes how Javassist works under the hood to modify class files and how frameworks like JRebel use it to reload configurations without restarts.
Monitoring And Tuning Glass Fish In The Wild Community One 2009SteveMillidge
The document provides an overview of tools for monitoring and troubleshooting GlassFish application servers, including command line tools like jps, jstat, jmap, jstack, asadmin, graphical tools like the GlassFish Admin Console and VisualVM, and more advanced tools like Memory Analyzer, Oracle JRockit, the Attach API, instrumentation, and BTrace. It describes example uses like identifying memory leaks, monitoring thread activity, and dynamically injecting tracing scripts into a running JVM.
The document provides an overview of tools for monitoring and troubleshooting GlassFish application servers, including command line tools like jps, jstat, jmap, jstack, asadmin, graphical tools like the GlassFish Admin Console and VisualVM, and more advanced tools like Memory Analyzer, Oracle JRockit, the Attach API, instrumentation, and BTrace. It describes examples of using these tools to detect memory leaks, rogue threads, and perform other diagnostic and debugging tasks on a running GlassFish server.
Scala is a multi-paradigm programming language that runs on the Java Virtual Machine. It is both object-oriented and functional, with support for immutable data and concise syntax. Scala has gained popularity due to its advantages like type safety, concurrency support, and interoperability with Java. However, some of Scala's advanced features can be difficult to read and use for beginners, and tooling support is not as robust as Java. Overall, Scala represents a promising approach that prioritizes simplicity over ease of use.
Akka provides tools for building concurrent, scalable and fault-tolerant systems using the actor model. The key tools provided by Akka include actors for concurrency, agents for shared state, dispatchers for work distribution, and supervision hierarchies for fault handling. Akka actors simplify concurrency through message passing and isolation, and provide tools for scaling and distributing actors across nodes for increased throughput and fault tolerance.
This document provides a history of JavaScript and ECMAScript specifications from 1995 to the present. It discusses the standardization process and key people and organizations involved like B. Eich, TC39, and ECMA. Major versions and proposed features are summarized, including ES6/ES2015 additions like arrow functions, block scoping with let/const, classes, modules, iterators/generators, and proxies.
The document outlines the topics covered in an advanced Java programming course, including object-oriented programming concepts, Java programming fundamentals, GUI programming, networking, and server-side programming. It also provides examples of Java code demonstrating basic syntax, methods, classes, strings, and math functions.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Akka 2.0 allows actors to be distributed across multiple nodes in a cluster in a transparent manner. It introduces new concepts like actor addresses and deployment configurations. The clustering functionality leverages ZooKeeper for distributed coordination and stores serialized actor factories. This allows actors to be dynamically created, migrated, and replicated across nodes for fault tolerance and load balancing. Composable futures also allow combining results from multiple asynchronous messages.
Introduction to Akka, as presented on May 3 2012 at the Belgian Java User Group (BeJUG). For more details see: http://www.bejug.org/confluenceBeJUG/display/BeJUG/ForkJoin+and+Akka
Demo code can be found at: http://bit.ly/bejug-akka
The document provides an introduction to Akka, a toolkit for building highly concurrent, distributed, and resilient message-driven applications using the actor model on the JVM, describing how Akka implements the actor model with additional features and modules for clustering, remoting, streams, and more.
Василий Ременюк «Курс молодого подрывника» e-Legion
В своем докладе, на примере фреймвормка для нагрузочного тестирования многопользовательской онлайн-игры, Василий рассказал, как, следуя 4-ем простым советам, создать эффективную, асинхронную систему, используя модель актеров и Akka 2.0, уложиться в отведенные сроки, и, при этом, регулярно спать по-ночам больше 4 часов.
Václav Pech is the lead of GPars, a concurrency library for Groovy. He discusses how languages are becoming increasingly concurrent to take advantage of multi-core processors. GPars supports various concurrency constructs including asynchronous functions, actors, dataflow programming, and parallel collections. It aims to provide concurrency without complexity through a unified API that hides low-level concurrency details.
The document provides an overview of Akka actors and clustering. Some key points:
- Akka actors are reactive components that receive messages asynchronously via mailboxes. Each actor has a behavior and mutable state.
- Actors can be created and organized in hierarchies. Messages are sent between actors using paths like actor references.
- Clustering allows actors to be deployed across multiple nodes. The cluster uses gossip protocols and vector clocks to maintain membership and detect failures.
- Cluster features include failure detection, cluster-aware routers for load balancing, and deathwatch notifications when nodes fail. This enables fault tolerance and distribution of actor applications.
Akka is a toolkit for building highly concurrent, distributed, and fault-tolerant applications on the JVM. It provides actors as the fundamental unit of concurrency. Actors receive messages asynchronously and process them one at a time by applying behaviors. Akka uses a supervision hierarchy where actors monitor child actors and handle failures through configurable strategies like restart or stop. This provides clean separation of processing and error handling compared to traditional approaches.
"Walk in a distributed systems park with Orleans" Евгений БобровFwdays
Долгое время разработка производительных, масштабируемых, надежных и экономически эффективных распределенных систем, была прерогативой узкого круга специалистов. Переезд в «облако», сам по себе, проблему не решил. Обещанная провайдерами дешевая линейная масштабируемость, по-прежнему, недостижимая мечта для всех, сидящих «на игле» реляционных баз данных и монолитных архитектур.
С выходом Microsoft Orleans, разработчики, наконец-то, получили максимально простую и удобную платформу для создания масштабируемых и отказоустойчивых распределенных систем, предназначенных для запуска в «облаке» или в приватном дата-центре.
В докладе будут рассмотрены основные концепции и прецеденты использования платформы, такие как: Internet Of Things (IoT), распределенная обработка потоков данных, масштабирование РСУБД и любых других ограниченных ресурсов, отказоустойчивая координация длительно выполняющихся бизнес-процессов.
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.
Con-FESS 2015 - Having Fun With JavassistAnton Arhipov
This document discusses using Javassist, a bytecode manipulation library, for tasks like adding logging to existing code without modifying the source code. It provides examples of using Javassist to inject logging into a method and creating a Java agent to manipulate bytecode. The document also summarizes how Javassist works under the hood to modify class files and how frameworks like JRebel use it to reload configurations without restarts.
Monitoring And Tuning Glass Fish In The Wild Community One 2009SteveMillidge
The document provides an overview of tools for monitoring and troubleshooting GlassFish application servers, including command line tools like jps, jstat, jmap, jstack, asadmin, graphical tools like the GlassFish Admin Console and VisualVM, and more advanced tools like Memory Analyzer, Oracle JRockit, the Attach API, instrumentation, and BTrace. It describes example uses like identifying memory leaks, monitoring thread activity, and dynamically injecting tracing scripts into a running JVM.
The document provides an overview of tools for monitoring and troubleshooting GlassFish application servers, including command line tools like jps, jstat, jmap, jstack, asadmin, graphical tools like the GlassFish Admin Console and VisualVM, and more advanced tools like Memory Analyzer, Oracle JRockit, the Attach API, instrumentation, and BTrace. It describes examples of using these tools to detect memory leaks, rogue threads, and perform other diagnostic and debugging tasks on a running GlassFish server.
Scala is a multi-paradigm programming language that runs on the Java Virtual Machine. It is both object-oriented and functional, with support for immutable data and concise syntax. Scala has gained popularity due to its advantages like type safety, concurrency support, and interoperability with Java. However, some of Scala's advanced features can be difficult to read and use for beginners, and tooling support is not as robust as Java. Overall, Scala represents a promising approach that prioritizes simplicity over ease of use.
Akka provides tools for building concurrent, scalable and fault-tolerant systems using the actor model. The key tools provided by Akka include actors for concurrency, agents for shared state, dispatchers for work distribution, and supervision hierarchies for fault handling. Akka actors simplify concurrency through message passing and isolation, and provide tools for scaling and distributing actors across nodes for increased throughput and fault tolerance.
This document provides a history of JavaScript and ECMAScript specifications from 1995 to the present. It discusses the standardization process and key people and organizations involved like B. Eich, TC39, and ECMA. Major versions and proposed features are summarized, including ES6/ES2015 additions like arrow functions, block scoping with let/const, classes, modules, iterators/generators, and proxies.
The document outlines the topics covered in an advanced Java programming course, including object-oriented programming concepts, Java programming fundamentals, GUI programming, networking, and server-side programming. It also provides examples of Java code demonstrating basic syntax, methods, classes, strings, and math functions.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
What is an RPA CoE? Session 1 – CoE VisionDianaGray10
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframePrecisely
Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
Ever-changing customer expectations demand more modern digital experiences, and the bank needed to find a solution that could provide real-time data to its customer channels with low latency and operating costs. Join this session to learn how Citizens is leveraging Precisely to replicate mainframe data to its customer channels and deliver on their “modern digital bank” experiences.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
1. Above the Clouds:
Introducing Akka
Vojin Jovanovic, EPFL
Philipp Haller, Typesafe
Based on material provided by the Akka team at Typesafe
2. The problem
It is way too hard to build:
1. correct highly concurrent systems
2. truly scalable systems
3. fault-tolerant systems that self-heal
...using “state-of-the-art” tools
8. WHERE IS AKKA USED?
SOME EXAMPLES:
FINANCE TELECOM
• Stock trend Analysis & Simulation
• Streaming media network gateways
• Event-driven messaging systems
SIMULATION
BETTING & GAMING • 3D simulation engines
• Massive multiplayer online gaming
E-COMMERCE
• High throughput and transactional
• Social media community sites
betting
10. ACTOR CONCURRENCY
• Actors = lightweight isolated processes
• No shared state
• Asynchronous message passing (non-blocking)
• Sequential message processing (one message at a
time)
• Actor mailbox: queue of not-yet-processed messages
19. Actors
case object Tick
class Counter extends Actor {
var counter = 0
def receive = {
case Tick =>
counter += 1
println(counter)
}
}
Scala API
20. Actors
class Counter extends UntypedActor {
int counter = 0;
void onReceive(Object msg) {
if (msg.equals(“Tick”)) {
counter += 1;
System.out.println(counter);
}
}
}
Java API
21. ACTOR SYSTEMS
• Actors are created in the context of an actor system
• Actor system = unit for managing shared facilities:
scheduling services, configuration, logging etc.
• Several actor systems with different configurations
may co-exist within the same JVM instance (there is
no global state within Akka itself)
• There may be millions of actors within a single actor
system
22. Create Application
val conf = ConfigFactory.load(“application”)
val system = ActorSystem(“my-app”, conf)
Scala API
23. Create Application
Config conf =
ConfigFactory.load(“application”);
ActorSystem system =
ActorSystem.create(“my-app”, conf);
Java API
24. Create Actors
val counter = system.actorOf(Props[Counter])
counter is an ActorRef
Creates a top-level actor
Scala API
30. Send: ?
import akka.patterns.ask
// returns a future
val future = actor ? message
future onSuccess {
case x => println(x)
}
returns a Future
Scala API
31. Reply
class SomeActor extends Actor {
def receive = {
case User(name) =>
// reply to sender
sender ! (“Hi ” + name)
}
}
Scala API
32. Reply
class SomeActor extends UntypedActor {
void onReceive(Object msg) {
if (msg instanceof User) {
User user = (User) msg;
// reply to sender
getSender().tell(“Hi ” + user.name);
}
}
}
Java API
33. ...or use ask
import akka.patterns.ask
// returns a future
val future = actor ask message
future onSuccess {
case x => println(x)
}
Scala API
34. ...or use ask
import static akka.patterns.Patterns.ask;
Future<Object> future = ask(actor, message, timeout);
future.onSuccess(new OnSuccess<Object>() {
public void onSuccess(String result) {
System.out.println(result);
}
});
Java API
35. Future
val f = Promise[String]()
f onComplete { ... }
onSuccess { ... }
onFailure { ... }
f foreach { ... }
f map { ... }
f flatMap { ... }
f filter { ... }
f zip otherF
f fallbackTo otherF
Await.result(f, 5 seconds)
Scala API
36. Future
firstCompletedOf
fold
reduce
find
traverse
sequence
Combinators for collections of Futures
59. Parental automatic supervision
// from within an actor
val child = context.actorOf(Props[MyActor], “my-actor”)
transparent and automatic fault handling by design
Scala API
60. Parental automatic supervision
// from within an actor
ActorRef child = getContext().actorOf(
new Props(MyActor.class), “my-actor”);
transparent and automatic fault handling by design
Java API
67. Name resolution
Guardian System Actor
Foo Bar
A
A C
E C
B
B
D
68. Name resolution
Guardian System Actor
/Foo
Foo Bar
A
A C
E C
B
B
D
69. Name resolution
Guardian System Actor
/Foo
Foo Bar
/Foo/A
A
A C
E C
B
B
D
70. Name resolution
Guardian System Actor
/Foo
Foo Bar
/Foo/A
A
A C
/Foo/A/B
E C
B
B
D
71. Name resolution
Guardian System Actor
/Foo
Foo Bar
/Foo/A
A
A C
/Foo/A/B
E C
B
B
D
/Foo/A/D
72. Supervision
class MySupervisor extends Actor {
def supervisorStrategy = OneForOneStrategy({
case _: ActorKilledException => Stop
case _: ArithmeticException => Resume
case _: Exception => Restart
case _ => Escalate
},
maxNrOfRetries = None,
withinTimeRange = None)
def receive = {
case NewUser(name) =>
... = context.actorOf[User](name)
}
} Scala API
73. Supervision
class MySupervisor extends Actor {
def supervisorStrategy = AllForOneStrategy
OneForOneStrategy({
case _: ActorKilledException => Stop
case _: ArithmeticException => Resume
case _: Exception => Restart
case _ => Escalate
},
maxNrOfRetries = None,
withinTimeRange = None)
def receive = {
case NewUser(name) =>
... = context.actorOf[User](name)
}
} Scala API
74. Manage failure
class FaultTolerantService extends Actor {
...
override def preRestart(
reason: Throwable, message: Option[Any]) = {
... // clean up before restart
}
override def postRestart(reason: Throwable) = {
... // init after restart
}
}
Scala API
75. watch/unwatch
val buddy: ActorRef = ...
val watcher = system.actorOf(Props(
new Actor {
context.watch(buddy)
def receive = {
case t: Terminated => ...
}
}
))
Scala API
76. ...and much much more
TestKit FSM
HTTP/REST
EventBus Pub/Sub
Durable Mailboxes Camel
IO
Microkernel SLF4J
AMQP
ZeroMQ Dataflow
Transactors
Agents Spring
77. get it and learn more
http://akka.io
http://typesafe.com