This presentation shows introduction to performance testing open source tool Gatling.
I am working on this tool from more than a year now and loved it's load testing features.
It uncovered many performance issues in our web based software service application.
I made and presented these slides to 20 QA people audience in our organization to show basics of Gatling tool. It also covers main facilities of Gatling for effective performance testing.
Thanks,
er.viral.jain@gmail.com
Gatling can be used to load test REST APIs by writing Scala simulation scripts. The scripts define test scenarios by chaining together the steps of invoking APIs concurrently. Feeders can inject runtime values. Tests are run by executing the Scala scripts from sbt or triggered from Jenkins. Gatling generates test reports in the target directory with results like response times and errors.
Reason meets OCaml
- Reason is a syntax extension to OCaml that compiles to efficient JavaScript. It has a rock solid type system and access to the OCaml ecosystem.
- ReasonReact provides React bindings for Reason. Components are defined in a similar way to TypeScript but use Reason's type system and compiler.
- Examples show how stateless and stateful components are defined in ReasonReact compared to TypeScript. ReasonReact uses OCaml's type system and reducer pattern while TypeScript uses interfaces and state.
- Interoperability with JavaScript is supported through modules, raw JavaScript blocks, and using the platform. Reason aims to leverage the strengths of both OCaml and React.
Performance Test Automation With GatlingKnoldus Inc.
Gatling is a lightweight dsl written in scala by which you can treat your performance test as a production code means you can easily write a readable code to test the performance of an application it s a framework based on Scala, Akka and Netty.
The document discusses dynamic programming in .NET 4. It covers the benefits of dynamic languages like easier refactoring. The Dynamic Language Runtime (DLR) allows dynamic features in static languages and sharing libraries. Dynamic objects implement their own binding and the DLR optimizes them. While dynamic coding avoids type declarations, it lacks compiler checking and IntelliSense support. The document also compares dynamic programming to using the object and var types.
The document provides details about the person's most recent role as a QA Analyst and Lead for a client project. Their responsibilities included creating test plans and cases from requirements, automating test scripts using tools like QTP, modifying scripts to include verification points and page load checks, configuring scripts to run in different environments, parameterizing test data, logging failures to report issues, attending meetings, and tracking bug fixes.
The document provides an overview of Apache Airflow, an open-source workflow management platform for data pipelines. It describes how Airflow allows users to programmatically author, schedule and monitor workflows or data pipelines via a GUI. It also outlines key Airflow concepts like DAGs (directed acyclic graphs), tasks, operators, sensors, XComs (cross-communication), connections, variables and executors that allow parallel task execution.
This presentation shows introduction to performance testing open source tool Gatling.
I am working on this tool from more than a year now and loved it's load testing features.
It uncovered many performance issues in our web based software service application.
I made and presented these slides to 20 QA people audience in our organization to show basics of Gatling tool. It also covers main facilities of Gatling for effective performance testing.
Thanks,
er.viral.jain@gmail.com
Gatling can be used to load test REST APIs by writing Scala simulation scripts. The scripts define test scenarios by chaining together the steps of invoking APIs concurrently. Feeders can inject runtime values. Tests are run by executing the Scala scripts from sbt or triggered from Jenkins. Gatling generates test reports in the target directory with results like response times and errors.
Reason meets OCaml
- Reason is a syntax extension to OCaml that compiles to efficient JavaScript. It has a rock solid type system and access to the OCaml ecosystem.
- ReasonReact provides React bindings for Reason. Components are defined in a similar way to TypeScript but use Reason's type system and compiler.
- Examples show how stateless and stateful components are defined in ReasonReact compared to TypeScript. ReasonReact uses OCaml's type system and reducer pattern while TypeScript uses interfaces and state.
- Interoperability with JavaScript is supported through modules, raw JavaScript blocks, and using the platform. Reason aims to leverage the strengths of both OCaml and React.
Performance Test Automation With GatlingKnoldus Inc.
Gatling is a lightweight dsl written in scala by which you can treat your performance test as a production code means you can easily write a readable code to test the performance of an application it s a framework based on Scala, Akka and Netty.
The document discusses dynamic programming in .NET 4. It covers the benefits of dynamic languages like easier refactoring. The Dynamic Language Runtime (DLR) allows dynamic features in static languages and sharing libraries. Dynamic objects implement their own binding and the DLR optimizes them. While dynamic coding avoids type declarations, it lacks compiler checking and IntelliSense support. The document also compares dynamic programming to using the object and var types.
The document provides details about the person's most recent role as a QA Analyst and Lead for a client project. Their responsibilities included creating test plans and cases from requirements, automating test scripts using tools like QTP, modifying scripts to include verification points and page load checks, configuring scripts to run in different environments, parameterizing test data, logging failures to report issues, attending meetings, and tracking bug fixes.
The document provides an overview of Apache Airflow, an open-source workflow management platform for data pipelines. It describes how Airflow allows users to programmatically author, schedule and monitor workflows or data pipelines via a GUI. It also outlines key Airflow concepts like DAGs (directed acyclic graphs), tasks, operators, sensors, XComs (cross-communication), connections, variables and executors that allow parallel task execution.
Gatling is a load testing tool that addresses issues with other tools like JMeter. It uses an asynchronous and non-blocking model based on the actor model to more accurately simulate loads. Gatling's DSL and Scala support allow for highly customizable scenarios and checks. It integrates with tools like Maven and Graphite and more features are in development like clustering and websockets support. A demo showed Gatling outperforming JMeter for high load testing of web applications.
With Cloud Functions you write simple, functions that doing one unit of execution.
Cloud Functions can be written using JavaScript, Python 3, or Go
and you simply deploy a function bound to the event you want and you are all done.
In our case we will leavrage from Cloud Function to manage our K8s clusters based on work times in order to save budget.
Concourse is a CI/CD tool that uses containers to provide repeatable builds. It models pipelines as a series of jobs that are connected through their inputs and outputs. Resources are checked for new versions and pulled into tasks where the work is done. Custom resources and caches can be created with containers to extend Concourse. Complex pipelines can be built with techniques like parallelization, aggregation, artifact storage, and grouping of jobs.
Kubernetes provides a powerful framework and great tooling to control hundreds of heterogenous workloads on thousands of machines. In a production environment, however, the collection of metrics to automatically detect and act on issues in such a cluster is essential. Prometheus was created to meet such needs: highly dynamic scheduling, automatic service discovery, and reliable operations.
Gatling, one of the most popular stress test OSS frameworks, is powered by Akka and Scala. In this talk I share insight gained while working with and customizing Gatling to exercise Protobuf-based backed services. I also show how to use Gatling for web applications.
ReactiveCocoa is a framework that uses functional reactive programming (FRP) to handle asynchronous data flows and events in a declarative way. It provides RACStream and RACSignal components to represent push-driven and pull-driven streams of data. RACSignal can be used to observe and chain together events like KVO observations. RACSequence represents pull-driven collections and adds higher-order functions. The document demonstrates using ReactiveCocoa and MVVM to build a reactive BMI calculator app, separating presentation logic from the view controller for easier testing and UI changes.
Gatling 2 is planned for 2014 and will include significant refactoring and new features. Some key changes include:
1. A new expression API that uses Validation to handle errors and support different data types.
2. Improvements to the session API to make data access safer.
3. A new templating API that supports string interpolation and external EL templates for simple use cases.
4. Enhancements to checks like regex to support capturing multiple groups and different data types.
5. Support for fetching embedded resources in parallel to better simulate browser behavior during load tests.
The document discusses a Kubeflow Pipelines component for Kubeflow Serving (KFServing) that allows usage of KFServing within Kubeflow Pipelines. The component uses the KFServing Python package and API to deploy InferenceServices and perform canary rollouts. A sample pipeline is shown that uses the component to deploy a TensorFlow model. The document also analyzes the component and discusses passing InferenceService YAML as the most flexible way to deploy models with full customizability.
Powering machine learning workflows with Apache Airflow and PythonTatiana Al-Chueyr
This document provides an overview of using Apache Airflow to power machine learning workflows with Python. It discusses Airflow concepts like DAGs, operators, relationships and visualizations. It also covers installing Airflow, common issues experienced like debugging and versioning, and using Airflow for machine learning tasks like model building and hyperparameter tuning. Examples of Airflow pipelines for data ingestion and machine learning are demonstrated. The presenter's background and the BBC Datalab team are briefly introduced.
Reactive programming is a general programming term focused on reacting to changes, such as data values or events. It can and often is done imperatively. A callback, delegate is an approach to reactive programming done imperatively.
Load Testing with Taurus using Jenkins and AWSGuy Salton
How to use Taurus, an open source automation framework to easily create and run open source load testing tools from CI and scale your tests with BlazeMeter
This document provides an overview of Spring Batch, including its typical architecture, key terminology, and how jobs flow through the framework. Spring Batch is designed for lightweight batch processing and works with a scheduler like Quartz. It allows for different types of processing like normal, concurrent, parallel, and partitioning. The document defines terminology like job hierarchy, step hierarchy, job parameters, and the difference between job execution context and step execution context. It also provides pointers on chunk processing, restarting jobs, using SPEL to access job parameters, and how to write custom item readers and writers.
The document describes Lineflow, an internal tool developed by LINE corp to improve engineering efficiency. It aims to automate LINE's software development process through a command line interface. Key points:
- Lineflow was built with Golang to define commands as a domain-specific language that reflects LINE's development workflow. It tracks command history to suggest next steps.
- This helped save engineers time by automating repetitive manual tasks like copying code between branches. It is estimated to save 41 engineer-hours per day.
- Developing internal tools requires dedicated resources and evangelism to gain adoption, but it lays the foundation for further improvements and integration with other tools.
Dr. Piyush Harsh discusses using Docker to streamline the testing environment for Cyclops, an open-source rating, charging, and billing microservices framework. Key benefits of Docker include predictable, standardized environment setup and faster response times compared to virtual machine-based deployments. Some challenges included port conflicts and ensuring service start order, but these were easy to address. A demo of Cyclops integrating with external components for a telecom network virtualization use case is also mentioned.
The document discusses the observer pattern and key-value observing (KVO) in Swift. It provides an overview of the observer pattern, explaining that it is event-driven, easy to write, and decouples objects. It then explains that KVO is a way to observe changes to an object's properties using Objective-C runtime, and outlines how to add, remove, and handle callbacks for observers in Swift. Finally, it notes that in Swift 4 KVO uses closures instead of callback functions and no longer requires removing observers.
Event Driven Architecture and Apache Kafka were discussed. Key points:
- Event driven systems allow for asynchronous and decoupled communication between services using message queues.
- Apache Kafka is a distributed streaming platform that allows for publishing and subscribing to streams of records across a cluster of servers. It provides reliability through replication and allows for horizontal scaling.
- Kafka provides advantages over traditional queues like decoupling, scalability, and fault tolerance. It also allows for publishing of data and consumption of data independently, unlike traditional APIs.
This document provides an overview of building an Apache Apex application, including key concepts like DAGs, operators, and ports. It also includes an example "word count" application and demonstrates how to define the application and operators, and build Apache Apex from source code. The document outlines the sample application workflow and includes information on resources for learning more about Apache Apex.
Orchestrating workflows Apache Airflow on GCP & AWSDerrick Qin
Working in a cloud or on-premises environment, we all somehow move data from A to B on-demand or on schedule. It is essential to have a tool that can automate recurring workflows. This can be anything from an ETL(Extract, Transform, and Load) job for a regular analytics report all the way to automatically re-training a machine learning model.
In this talk, we will introduce Apache Airflow and how it can help orchestrate your workflows. We will cover key concepts, features, and use cases of Apache Airflow, as well as how you can enjoy Apache Airflow on GCP and AWS by demo-ing a few practical workflows.
This document discusses using BaseX, an XML database, for web applications. It describes GraphXQ, which uses RESTXQ and Graphviz to visualize graphs. It also describes CellarXQ, an Angular.js single page application that uses BaseX and OAuth for user authentication and data storage. Finally, it shows how to create a chatbot using BaseX, Node.js and Socket.io that passes messages to an XQuery script for processing.
The document provides an overview of advance Java topics including collections, multithreading, networking, AWT, Swing, JDBC, JSP, and applets. It discusses key aspects of each topic such as the collection framework providing interfaces and classes for storing and manipulating groups of data, multithreading allowing programs to perform multiple tasks simultaneously, and JDBC enabling connection between Java applications and databases. Code examples are also included to demonstrate concepts like a basic Swing program and a simple applet.
Gatling is a load testing tool that addresses issues with other tools like JMeter. It uses an asynchronous and non-blocking model based on the actor model to more accurately simulate loads. Gatling's DSL and Scala support allow for highly customizable scenarios and checks. It integrates with tools like Maven and Graphite and more features are in development like clustering and websockets support. A demo showed Gatling outperforming JMeter for high load testing of web applications.
With Cloud Functions you write simple, functions that doing one unit of execution.
Cloud Functions can be written using JavaScript, Python 3, or Go
and you simply deploy a function bound to the event you want and you are all done.
In our case we will leavrage from Cloud Function to manage our K8s clusters based on work times in order to save budget.
Concourse is a CI/CD tool that uses containers to provide repeatable builds. It models pipelines as a series of jobs that are connected through their inputs and outputs. Resources are checked for new versions and pulled into tasks where the work is done. Custom resources and caches can be created with containers to extend Concourse. Complex pipelines can be built with techniques like parallelization, aggregation, artifact storage, and grouping of jobs.
Kubernetes provides a powerful framework and great tooling to control hundreds of heterogenous workloads on thousands of machines. In a production environment, however, the collection of metrics to automatically detect and act on issues in such a cluster is essential. Prometheus was created to meet such needs: highly dynamic scheduling, automatic service discovery, and reliable operations.
Gatling, one of the most popular stress test OSS frameworks, is powered by Akka and Scala. In this talk I share insight gained while working with and customizing Gatling to exercise Protobuf-based backed services. I also show how to use Gatling for web applications.
ReactiveCocoa is a framework that uses functional reactive programming (FRP) to handle asynchronous data flows and events in a declarative way. It provides RACStream and RACSignal components to represent push-driven and pull-driven streams of data. RACSignal can be used to observe and chain together events like KVO observations. RACSequence represents pull-driven collections and adds higher-order functions. The document demonstrates using ReactiveCocoa and MVVM to build a reactive BMI calculator app, separating presentation logic from the view controller for easier testing and UI changes.
Gatling 2 is planned for 2014 and will include significant refactoring and new features. Some key changes include:
1. A new expression API that uses Validation to handle errors and support different data types.
2. Improvements to the session API to make data access safer.
3. A new templating API that supports string interpolation and external EL templates for simple use cases.
4. Enhancements to checks like regex to support capturing multiple groups and different data types.
5. Support for fetching embedded resources in parallel to better simulate browser behavior during load tests.
The document discusses a Kubeflow Pipelines component for Kubeflow Serving (KFServing) that allows usage of KFServing within Kubeflow Pipelines. The component uses the KFServing Python package and API to deploy InferenceServices and perform canary rollouts. A sample pipeline is shown that uses the component to deploy a TensorFlow model. The document also analyzes the component and discusses passing InferenceService YAML as the most flexible way to deploy models with full customizability.
Powering machine learning workflows with Apache Airflow and PythonTatiana Al-Chueyr
This document provides an overview of using Apache Airflow to power machine learning workflows with Python. It discusses Airflow concepts like DAGs, operators, relationships and visualizations. It also covers installing Airflow, common issues experienced like debugging and versioning, and using Airflow for machine learning tasks like model building and hyperparameter tuning. Examples of Airflow pipelines for data ingestion and machine learning are demonstrated. The presenter's background and the BBC Datalab team are briefly introduced.
Reactive programming is a general programming term focused on reacting to changes, such as data values or events. It can and often is done imperatively. A callback, delegate is an approach to reactive programming done imperatively.
Load Testing with Taurus using Jenkins and AWSGuy Salton
How to use Taurus, an open source automation framework to easily create and run open source load testing tools from CI and scale your tests with BlazeMeter
This document provides an overview of Spring Batch, including its typical architecture, key terminology, and how jobs flow through the framework. Spring Batch is designed for lightweight batch processing and works with a scheduler like Quartz. It allows for different types of processing like normal, concurrent, parallel, and partitioning. The document defines terminology like job hierarchy, step hierarchy, job parameters, and the difference between job execution context and step execution context. It also provides pointers on chunk processing, restarting jobs, using SPEL to access job parameters, and how to write custom item readers and writers.
The document describes Lineflow, an internal tool developed by LINE corp to improve engineering efficiency. It aims to automate LINE's software development process through a command line interface. Key points:
- Lineflow was built with Golang to define commands as a domain-specific language that reflects LINE's development workflow. It tracks command history to suggest next steps.
- This helped save engineers time by automating repetitive manual tasks like copying code between branches. It is estimated to save 41 engineer-hours per day.
- Developing internal tools requires dedicated resources and evangelism to gain adoption, but it lays the foundation for further improvements and integration with other tools.
Dr. Piyush Harsh discusses using Docker to streamline the testing environment for Cyclops, an open-source rating, charging, and billing microservices framework. Key benefits of Docker include predictable, standardized environment setup and faster response times compared to virtual machine-based deployments. Some challenges included port conflicts and ensuring service start order, but these were easy to address. A demo of Cyclops integrating with external components for a telecom network virtualization use case is also mentioned.
The document discusses the observer pattern and key-value observing (KVO) in Swift. It provides an overview of the observer pattern, explaining that it is event-driven, easy to write, and decouples objects. It then explains that KVO is a way to observe changes to an object's properties using Objective-C runtime, and outlines how to add, remove, and handle callbacks for observers in Swift. Finally, it notes that in Swift 4 KVO uses closures instead of callback functions and no longer requires removing observers.
Event Driven Architecture and Apache Kafka were discussed. Key points:
- Event driven systems allow for asynchronous and decoupled communication between services using message queues.
- Apache Kafka is a distributed streaming platform that allows for publishing and subscribing to streams of records across a cluster of servers. It provides reliability through replication and allows for horizontal scaling.
- Kafka provides advantages over traditional queues like decoupling, scalability, and fault tolerance. It also allows for publishing of data and consumption of data independently, unlike traditional APIs.
This document provides an overview of building an Apache Apex application, including key concepts like DAGs, operators, and ports. It also includes an example "word count" application and demonstrates how to define the application and operators, and build Apache Apex from source code. The document outlines the sample application workflow and includes information on resources for learning more about Apache Apex.
Orchestrating workflows Apache Airflow on GCP & AWSDerrick Qin
Working in a cloud or on-premises environment, we all somehow move data from A to B on-demand or on schedule. It is essential to have a tool that can automate recurring workflows. This can be anything from an ETL(Extract, Transform, and Load) job for a regular analytics report all the way to automatically re-training a machine learning model.
In this talk, we will introduce Apache Airflow and how it can help orchestrate your workflows. We will cover key concepts, features, and use cases of Apache Airflow, as well as how you can enjoy Apache Airflow on GCP and AWS by demo-ing a few practical workflows.
This document discusses using BaseX, an XML database, for web applications. It describes GraphXQ, which uses RESTXQ and Graphviz to visualize graphs. It also describes CellarXQ, an Angular.js single page application that uses BaseX and OAuth for user authentication and data storage. Finally, it shows how to create a chatbot using BaseX, Node.js and Socket.io that passes messages to an XQuery script for processing.
The document provides an overview of advance Java topics including collections, multithreading, networking, AWT, Swing, JDBC, JSP, and applets. It discusses key aspects of each topic such as the collection framework providing interfaces and classes for storing and manipulating groups of data, multithreading allowing programs to perform multiple tasks simultaneously, and JDBC enabling connection between Java applications and databases. Code examples are also included to demonstrate concepts like a basic Swing program and a simple applet.
This document provides an overview of microservices and how to develop them using Spring. It discusses the challenges of distributed systems and how Spring Boot and Spring Cloud Netflix address areas like configuration, service registration, load balancing, fault tolerance, and monitoring. Examples are provided for building microservices with Spring Boot, integrating configuration with Spring Cloud Config, registering services with Eureka, load balancing with Ribbon and Feign, handling faults with Hystrix, and monitoring with Hystrix Dashboard. Reactive programming with RxJava is also introduced as an approach for concurrent API integration.
Java ScriptingJava Scripting: One VM, Many Languageselliando dias
The document discusses using scripting languages with the Java platform. It provides an overview of scripting languages and their uses. It explains how the Java virtual machine can run many languages and leverage their advantages while providing scalability. Examples are given of integrating scripts with Java applications and invoking script functions from Java. Future directions like JSR 292 for dynamic invocation are also covered.
Building Server Applications Using ObjectiveC And GNUstepguest9efd1a1
- Server applications written in Objective-C and GNUstep can take advantage of the GNUstep base libraries and Foundation framework to provide high-level object-oriented design and functionality while maintaining high performance comparable to C.
- The GNUstep base libraries provide common classes for tasks like strings, collections, threading, notifications, and I/O that allow server code to be organized using object-oriented patterns.
- Objective-C is well-suited for server applications because it is a strict superset of C, allowing seamless integration of C code and libraries, while also providing object-oriented features for high-level organization of server code.
Building Server Applications Using Objective C And Gn Ustepwangii
- Server applications written in Objective-C and GNUstep-base can take advantage of the high-level object-oriented features of Objective-C while maintaining the performance and flexibility of C.
- GNUstep-base provides the Foundation library, which includes classes for tasks like threading, networking, data storage and more that are useful for server applications.
- Objective-C allows mixing C code for performance critical parts while organizing the overall application structure using object-oriented patterns supported by the GNUstep-base libraries.
This document provides a summary of Ankit Chohan's professional experience and technical skills. He has over 3 years of experience as a senior Java developer working on projects involving data integration, continuous integration/delivery, and financial systems. His technical skills include Java/J2EE, SQL, XML, web services, Jenkins, Ant, and various databases and application servers.
The document provides an introduction to the Java programming language. It discusses that Java was created by Sun Microsystems to allow web pages to include interactive Java code. It is a simple, object-oriented, portable language that uses bytecode and a virtual machine to achieve platform independence. The document outlines Java's core features such as being distributed, multithreaded, robust, secure, and high performance. It also summarizes Java's basic data types, classes, objects, and how to write both applications and applets.
The document summarizes Roberto Casadei's presentation on scafi, a Scala-based framework for aggregate programming and distributed computational fields. Scafi includes (1) an internal DSL for the field calculus, integrated with Scala's type system, (2) an actor-based distributed platform using Akka for fault tolerance, communication, and synchronization, and (3) support for code mobility through message deserialization. The presentation evaluates scafi's achievement of key goals like field calculus support and distributed platform flexibility, while identifying opportunities for further improvement, testing, and applications.
Kubernetes is exploding in popularity right now and has all the buzz and cargo-culting that Docker enjoyed just a few years ago. But what even is Kubernetes? How do I run my PHP apps in it? Should I run my PHP apps in it ?
JavaScript and jQuery for SharePoint DevelopersRob Windsor
If you’re a SharePoint developer you either are doing JavaScript development now or you will be doing JavaScript development in the near future. There has been an increased focus on client-side development with each of the recent versions of SharePoint and now, with the introduction of the SharePoint 2013 App model, understanding client-side development is a must. In this session, we`ll look at JavaScript development from a SharePoint perspective. In addition to effective use of JavaScript and jQuery in your applications, we`ll look where you can deploy JavaScript files and how to reference those files in your pages and web parts.
This document discusses using various technologies on Google App Engine including JIQL, GaeVFS, RESTlets, scheduled tasks, JRuby on Rails, task queues, XMPP, and Clojure. JIQL emulates a relational database on App Engine's Bigtable datastore. GaeVFS provides a virtual filesystem on Bigtable. RESTlets make RESTful web services easy to implement in Java on App Engine. Scheduled tasks allow for background processing via cron jobs. JRuby on Rails provides a way to run Ruby on Rails applications on App Engine. Task queues allow for asynchronous background processing. XMPP enables instant messaging and peer-to-peer applications. Clojure can also be used
OSGi Overview provides information on OSGi, its benefits, and how it works. Key points include:
- OSGi allows developing modular Java programs through bundles that declare dependencies. Each bundle dynamically loads classes.
- In Liferay, bundles become portlets, services, or extensions. The blade CLI helps create these.
- Portlets can be implemented as MVC portlets or use configuration and portlet provider templates.
- Services can be created with Service Builder or wrapped. OSGi services can also be registered.
- Liferay modules can be extended through fragments to customize JSPs, properties, add filters or events.
This document provides an overview of Java 8 including:
- Java 8 has approximately 9 million developers and Oracle supports versions 6-8.
- New features include default methods, lambda expressions, streams, and parallel processing capabilities.
- JavaScript integration allows JavaScript code to be run from Java, enabling database and other connections from JavaScript.
- Potential issues with Java 8 include more complex debugging due to lambda expressions and increased abstraction.
The document discusses the history of build tools and outlines a roadmap for sbt 1.0 focused on stability and modularization. It introduces sbt-server as a way to centralize build tasks and allow multiple clients to interact with the build. Key points of the sbt-server design include running tasks in a centralized queue, handling reconnects, using a versioned protocol for communication, and supporting background jobs and input. The document also discusses bringing existing sbt plugins onto sbt-server without breaking functionality.
(1) c sharp introduction_basics_dot_netNico Ludwig
This document provides an introduction to parsing an update log using different programming languages, including C#, Visual Basic, C++/CLI, F#, and others. It describes the problem of parsing a software update log file to retrieve the latest updates for different applications. It then shows sample code solutions in each language and provides brief descriptions and context about each language.
The document provides an overview of application lifecycle management (ALM) in a serverless world. It discusses key concepts like continuous integration/delivery and testing practices for serverless applications. Serverless architectures using AWS Lambda and API Gateway are highlighted, along with how to manage deployments, configurations, and monitor applications.
Necto 16 training 20 component mode & java scriptPanorama Software
This document provides an overview of using JavaScript with Necto SDK to manipulate Necto. The objectives are to show JavaScript basics, debug JavaScript in IE, and use the Necto SDK. The agenda includes an overview of JavaScript with Necto, debugging in Necto and IE, and an example. JavaScript can interact with HTML and the DOM. The Necto SDK has APIs that can be called from JavaScript. Debugging requires disabling script debugging in IE options. Examples manipulate XML data and add functionality to a workboard.
The document provides an overview of the Java programming language and related technologies including servlets, JSP, Struts, Hibernate, and Tiles. It discusses what Java is, its history and technology, the different Java editions, J2EE and its components, how servlets and JSP work, database handling with JDBC, the MVC pattern implemented by Struts, and object relational mapping with Hibernate. Tiles is described as a framework for assembling web pages from individual visual components.
Apache Samza is a stream processing framework that provides high-level APIs and powerful stream processing capabilities. It is used by many large companies for real-time stream processing. The document discusses Samza's stream processing architecture at LinkedIn, how it scales to process billions of messages per day across thousands of machines, and new features around faster onboarding, powerful APIs including Apache Beam support, easier development through high-level APIs and tables, and better operability in YARN and standalone clusters.
Similar to SubScript: A Process Algebra extension progress and perspectives (20)
Revolutionizing Visual Effects Mastering AI Face Swaps.pdfUndress Baby
The quest for the best AI face swap solution is marked by an amalgamation of technological prowess and artistic finesse, where cutting-edge algorithms seamlessly replace faces in images or videos with striking realism. Leveraging advanced deep learning techniques, the best AI face swap tools meticulously analyze facial features, lighting conditions, and expressions to execute flawless transformations, ensuring natural-looking results that blur the line between reality and illusion, captivating users with their ingenuity and sophistication.
Web:- https://undressbaby.com/
UI5con 2024 - Keynote: Latest News about UI5 and it’s EcosystemPeter Muessig
Learn about the latest innovations in and around OpenUI5/SAPUI5: UI5 Tooling, UI5 linter, UI5 Web Components, Web Components Integration, UI5 2.x, UI5 GenAI.
Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
Microservice Teams - How the cloud changes the way we workSven Peters
A lot of technical challenges and complexity come with building a cloud-native and distributed architecture. The way we develop backend software has fundamentally changed in the last ten years. Managing a microservices architecture demands a lot of us to ensure observability and operational resiliency. But did you also change the way you run your development teams?
Sven will talk about Atlassian’s journey from a monolith to a multi-tenanted architecture and how it affected the way the engineering teams work. You will learn how we shifted to service ownership, moved to more autonomous teams (and its challenges), and established platform and enablement teams.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
Most important New features of Oracle 23c for DBAs and Developers. You can get more idea from my youtube channel video from https://youtu.be/XvL5WtaC20A
WhatsApp offers simple, reliable, and private messaging and calling services for free worldwide. With end-to-end encryption, your personal messages and calls are secure, ensuring only you and the recipient can access them. Enjoy voice and video calls to stay connected with loved ones or colleagues. Express yourself using stickers, GIFs, or by sharing moments on Status. WhatsApp Business enables global customer outreach, facilitating sales growth and relationship building through showcasing products and services. Stay connected effortlessly with group chats for planning outings with friends or staying updated on family conversations.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-fusion-buddy-review
AI Fusion Buddy Review: Key Features
✅Create Stunning AI App Suite Fully Powered By Google's Latest AI technology, Gemini
✅Use Gemini to Build high-converting Converting Sales Video Scripts, ad copies, Trending Articles, blogs, etc.100% unique!
✅Create Ultra-HD graphics with a single keyword or phrase that commands 10x eyeballs!
✅Fully automated AI articles bulk generation!
✅Auto-post or schedule stunning AI content across all your accounts at once—WordPress, Facebook, LinkedIn, Blogger, and more.
✅With one keyword or URL, generate complete websites, landing pages, and more…
✅Automatically create & sell AI content, graphics, websites, landing pages, & all that gets you paid non-stop 24*7.
✅Pre-built High-Converting 100+ website Templates and 2000+ graphic templates logos, banners, and thumbnail images in Trending Niches.
✅Say goodbye to wasting time logging into multiple Chat GPT & AI Apps once & for all!
✅Save over $5000 per year and kick out dependency on third parties completely!
✅Brand New App: Not available anywhere else!
✅ Beginner-friendly!
✅ZERO upfront cost or any extra expenses
✅Risk-Free: 30-Day Money-Back Guarantee!
✅Commercial License included!
See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
#AIFusionBuddyReview,
#AIFusionBuddyFeatures,
#AIFusionBuddyPricing,
#AIFusionBuddyProsandCons,
#AIFusionBuddyTutorial,
#AIFusionBuddyUserExperience
#AIFusionBuddyforBeginners,
#AIFusionBuddyBenefits,
#AIFusionBuddyComparison,
#AIFusionBuddyInstallation,
#AIFusionBuddyRefundPolicy,
#AIFusionBuddyDemo,
#AIFusionBuddyMaintenanceFees,
#AIFusionBuddyNewbieFriendly,
#WhatIsAIFusionBuddy?,
#HowDoesAIFusionBuddyWorks
What is Master Data Management by PiLog Groupaymanquadri279
PiLog Group's Master Data Record Manager (MDRM) is a sophisticated enterprise solution designed to ensure data accuracy, consistency, and governance across various business functions. MDRM integrates advanced data management technologies to cleanse, classify, and standardize master data, thereby enhancing data quality and operational efficiency.
Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
Requirement — Collecting the Requirements is the first Phase in the SSLC process.
Feasibility Study — after completing the requirement process they move to the design phase.
Design — in this phase, they start designing the software.
Coding — when designing is completed, the developers start coding for the software.
Testing — in this phase when the coding of the software is done the testing team will start testing.
Installation — after completion of testing, the application opens to the live server and launches!
Maintenance — after completing the software development, customers start using the software.
Takashi Kobayashi and Hironori Washizaki, "SWEBOK Guide and Future of SE Education," First International Symposium on the Future of Software Engineering (FUSE), June 3-6, 2024, Okinawa, Japan
4. Meet SubScript
• An extension to Scala programming language
• Adds a syntax for process description inspired by
the Algebra of Communicating Processes
• Aims for simplification of event-driven and
concurrent programming
5. Brief history
• Started as a library (VM), then the syntax was added by a compiler fork - it was difficult to
get started
• Developed into a preprocessor based on parser combinators to specify the syntax. It is
managed by an SBT plugin - easy to get started and play with the syntax
scalaVersion := "2.11.7"
libraryDependencies += "org.subscript-lang" %% "subscript-swing" % "3.0.3"
SubscriptSbt.projectSettings
addSbtPlugin("org.subscript-lang" %% "subscript-sbt-plugin" % "3.0.3")
build.sbt
project/build.sbt
7. Example: Hello World
import subscript.language
import subscript._
import subscript.Predef._
object Main extends SubScriptApplication {
script live = println("Hello") println("World")
}
Short
Verbose import subscript.language
import subscript._
import subscript.Predef._
object Main {
def main(args: Array[String]): Unit = runScript(live)
script live = {:println("Hello"):} {:println("World"):}
}
8. Operators
• Sequential: space, line break, “;” - identical
• Parallel: &&, &, ||, | - behaviour inspired by Boolean logic
• Choice: “+” operator selects between its operands
• Disruption: “/“ - left hand side disrupted by the right
hand side
• Conditional: if-then-else (boolean script result values as
a predicate), do-then-else (script success status as a
predicate)
9. Data Flow
• Each script can have a result value, it can be set
with a special syntax
• The result value can be processed using the
dataflow notation
script..
live = msg ~~(message: String)~~> println(message)
msg = ^"Hello World"
10. Example application: Eye Test
object Main extends SubScriptApplication {
script..
live = initGui
[ new WaitScreen || initData^ ]~~(repos: Repositories)~~>
[ new MainScreen(repos); let repos.close()]
initGui = javax.swing.UIManager.setLookAndFeel:
"com.sun.java.swing.plaf.nimbus.NimbusLookAndFeel"
initData = ^{*new DerbyRepo("eyetest-db")*}
}
11. Example application: Eye Test
class Test extends Frame with FrameProcess {
script..
live = mainTestProcess^ / cancelBtn
mainTestProcess = eyeTest("Right")^^1
eyeTest("Left" )^^2
eyeTest(eyeName: String) = let testArea.font = new Font("Ariel", ..., 20)
let testArea.text = s"Look with $eyeName eye, OK when ready"
let answerField.enabled = false
sleep: 250
Key.Enter + okBtn
doTest( if(eyeName=="Right") previousScoreRight
else previousScoreLeft )^
}