ActiveMQ is an open source message broker that implements the Java Message Service (JMS) API. It allows applications written in different languages to communicate asynchronously. Apache Camel is an open source integration framework that can be used to build messaging routes between different transports and APIs using a simple domain-specific language. It provides mediation capabilities and supports common integration patterns. Both ActiveMQ and Camel aim to simplify integration between disparate systems through message-based communication.
This document provides an overview and agenda for a MuleSoft Meetup event in São Paulo on managing APIs with MuleSoft. The meetup will include introductions, a sponsor presentation from Cognizant, a discussion of API gateway concepts, a demo, and questions. It will provide a safe space for attendees to learn and share integration experiences. The goal is to discuss topics key to successful application integration on MuleSoft's Anypoint Platform. Networking time will conclude the event.
This document discusses WebAssembly and its potential as a game changer for web development. It begins by providing background on how JavaScript evolved and its performance limitations. WebAssembly is presented as a solution to address JavaScript's performance issues by allowing code written in languages like C/C++ to run in the browser at near-native speed. The document explains that WebAssembly is a binary format and build target that works with JavaScript. It discusses how browsers execute WebAssembly, the interaction between WebAssembly and JavaScript, usage scenarios, security considerations, current support and future possibilities like garbage collection and threads. Examples of WebAssembly in use are also provided.
Accelerate Quality with Postman - BasicsKnoldus Inc.
This document provides an overview of Postman, an API development environment and tool. It discusses Postman's core concepts like collections, environments and scripts. Collections allow organizing requests into folders for documentation, testing and workflows. Environments enable customizing requests for different setups. Scripts add dynamic behavior to requests through pre-request and test scripts. The document also covers executing collections through Postman's collection runner or Newman CLI, and integrating Postman into development workflows.
The document discusses using Postman for API testing over 10 days. It covers topics like the Postman UI, creating and organizing API requests and collections, using variables and environments, running collections from the command line and generating HTML reports, and common authentication, authorization, and status codes.
Irfan Baqui, Senior Engineer at LunchBadger, breaks down the important role of the API Gateway in Microservices. Additionally, Irfan covers how to get started with Express Gateway, an open source API Gateway built entirely on Express.js. Originally presented at the San Francisco Node Meetup.
Spring cloud for microservices architectureIgor Khotin
I'm covering a new trend in distributed enterprise architecture – microservices. How the leading technology companies like Netflix and Amazon come to use that approach. How does it help them to scale their infrastructure. And how the newest set of tools in the Spring family would help you to apply those design principles in practice.
Spring has always been about patterns and Spring Cloud brings you implementation of several widespread ones for distributed apps.
And we'll try to show why DevOps should come in front of Microservices approach
In this webinar, Postman Developer Advocate Arlemi Turpault will show you:
- How to get started with Postman
- Key tips and tricks
- Where to look for documentation and help
BlazeMeter Presents at the High Performance Drupal MeetupBlazeMeter
BlazeMeter is a cloud-based load testing service that is 100% compatible with Apache JMeter. It aims to simplify load testing for developers and testers by handling the infrastructure and providing an easy-to-use interface. Key features include the ability to run load tests with thousands of users in under 10 minutes, analyze response times and errors under different loads, and compare performance with caching enabled versus disabled.
APIs are the lynchpin to the success of your digital business. Explore how you can effectively design, secure, monitor and manage APIs across the enterprise.
Prometheus: Monitoring by "Pravin Magdum" from "Crevise". The presentation was done at #doppa17 DevOps++ Global Summit 2017. All the copyrights are reserved with the author
Postman is an API development tool that allows users to design, manage, run, test, document, and share APIs. It provides features like request building, documentation, environments, test automation, and collaboration. Alternatives include Paw, Insomnia, command line tools like cURL, and services from Apigee and Apiary. The document recommends using any tool that helps share APIs, especially for complex projects and team collaboration.
This document discusses API testing and tools for API test automation. It begins with an overview of APIs and their history, then defines API testing and discusses considerations for API testing today and in the future. Top concerns for API testing are listed as functionality, performance, security, and availability. RESTful web services and their use of HTTP requests and JSON format are covered. Finally, the document introduces Postman, SoapUI, and Robot Framework as examples of tools for API test automation and provides brief descriptions of each tool.
Introduction to Integration Testing With CypressErez Cohen
A quick overview over Cypress, a front end testing library, going over the motivation to incorporate it for integration tests and some best practices of how to use it.
This document provides an overview of HTTP and REST APIs. It describes how HTTP allows sending documents over the web using URLs to identify resources and HTTP verbs like GET, PUT, DELETE and POST. It defines common response codes. It explains that REST stands for Representational State Transfer and relies on a stateless, client-server architecture using the HTTP protocol. The key design constraints of REST include having a uniform interface, being resource-based and using representations to manipulate resources with self-descriptive messages. Benefits include statelessness for scalability, cacheability to improve performance, separating clients from servers, and using a layered system with intermediary servers.
Learn all about microservices from Product Marketing Manager Dan Giordano. We'll cover how to get started, the benefits, potential challenges, and how SmartBear can help.
Dynatrace is an APM solution that provides deep visibility into application performance across complex, distributed environments. It uses PurePath technology to capture timing and code-level context for all transactions end-to-end. This allows Dynatrace to identify performance issues and their root causes faster than other tools. Dynatrace can monitor Apache Tomcat servers and provide metrics on JVM performance, database queries, requests, and more. It helps diagnose common issues like inefficient database access, microservice problems, and coding issues.
Driving Pipeline Automation With Newman and the Postman APIPostman
This document discusses strategies for integrating Postman workflows into CI/CD pipelines using Newman and the Postman API. It covers common strategies like running Postman collections and reporting test results. It also discusses automating test discovery and execution by using labels on Postman assets and wiring pipelines to take advantage of this flexibility. The presenter encourages observing everything, measuring lead time, and finding a balance between challenges and capacity for flow and joy.
WebSockets allow for bidirectional communication between a client and server over a single TCP connection. They provide lower latency and overhead than traditional HTTP requests which require a new connection for each request. The talk demonstrated how to use WebSockets with JavaScript on the client and event-driven servers like Node.js on the server. While browser support is still limited and the specification is in flux, WebSockets offer a way to build real-time applications without hacks like long-polling that HTTP requires.
Introduction to Microservices Patterns. In these slides we explore microservices vs monolith apis. We try to identify the challenges of moving to microservices ecosystem and try to analyze possible solutions for data consistency, inter-communication, event driven and distributed transactions.
This document provides an overview and summary of ActiveMQ features for message-oriented middleware including messaging domains, durability vs persistence, message acknowledgement vs transactions, synchronous vs asynchronous message consumption, broker clustering, master/slave configurations, security options, wire formats for non-Java clients, handling disconnected producers/consumers, consumer options, slow consumer strategies, monitoring broker statistics, and an introduction to Apache Camel for integration.
Messaging for Web and Mobile with Apache ActiveMQdejanb
This document summarizes a presentation on messaging for web and mobile applications using Apache ActiveMQ. The presentation covered challenges with HTTP messaging, advantages of STOMP and MQTT protocols, and examples of using STOMP over WebSocket for browser messaging and MQTT for mobile apps. It also provided an overview of Apache ActiveMQ's support for STOMP, including client examples in Java.
Apache ActiveMQ - Enterprise messaging in actiondejanb
This document provides an overview of Apache ActiveMQ, an open source messaging platform. It discusses key ActiveMQ concepts like topics, queues, and messaging protocols. It also covers ActiveMQ enterprise features such as high availability, clustering, security, and monitoring. The document concludes by discussing ActiveMQ performance tuning, scaling, and future plans.
This document summarizes common problems and solutions when using ActiveMQ. It addresses questions about creating JMS clients from scratch, efficiently managing connections, consuming only certain messages, reasons for locking/freezing, when a network of brokers is needed, and using a master/slave configuration. Spring JMS and selectors are recommended over building clients from scratch. Connection pooling and caching are advised for efficiency. Selectors and proper design can filter messages. Memory, prefetch limits, and cursors impact performance and need configuration. Networked brokers improve availability while master/slave configurations provide high availability.
This document provides an overview of Apache ActiveMQ, an open source messaging system. It discusses what ActiveMQ is, its basics like topics and queues, techniques for scaling such as vertical, horizontal and hybrid approaches, ensuring high availability, and its future direction with ActiveMQ Apollo. The presentation aims to explain how ActiveMQ works and how to configure it for different deployment needs.
Getting Started with Apache Camel at DevNation 2014Claus Ibsen
Get off to a good start with Apache Camel. This session will give you an introduction to Apache Camel and teach you:
- How Camel is related to enterprise integration patterns (EIPs).
- How to use EIPs in Camel routes written in Java code or XML files.
- How to get started developing with Camel, including how to set up new projects from scratch using Maven and Eclipse.
- With a live demo, how to build Camel applications in Java, Spring, and OSGi Blueprint.
- How ready-to-use features make integration much easier.
- About the web console tools that give you insight into your running Apache Camel applications, including visual route diagrams with tracing, debugging, and profiling capabilities.
- Useful resources to learn more about Camel.
This session will be taught with a 50/50 mix of slides and live demos, and it will conclude with Q&A time.
This document provides an overview of Apache ActiveMQ and messaging with JMS. It discusses what JMS is and how it abstracts message brokers. It then describes what ActiveMQ is and its goals as open source message-oriented middleware. The document outlines examples, configurations, transports, topologies and high availability options for ActiveMQ. It also discusses security, monitoring, visualization and integration with Apache Camel.
Developing Microservices with Apache CamelClaus Ibsen
Red Hat Microservices Architecture Day - New York, November 2015. Presented by Claus Ibsen.
Apache Camel is a very popular integration library that works very well with microservice architecture. This talk introduces you to Apache Camel and how you can easily get started with Camel on your computer. Then we cover how to create new Camel projects from scratch as microservices, which you can boot using Camel or Spring Boot, or other micro containers such as Jetty or fat JARs. We then take a look at what options you have for monitoring and managing your Camel microservices using tooling such as Jolokia, and hawtio web console.
Messaging is the backbone of many top enterprises. It affords reliable, asynchronous data passing to achieve loosely coupled, highly scalable distributed systems. As enterprises large and small become more interconnected, demand for remote and limited devices to be integrated with enterprise systems is surging. Come see how the most widely used, open-source messaging broker, Apache ActiveMQ, fits nicely and how it supports polyglot messaging.
System Integration with Akka and Apache Camelkrasserm
This document summarizes the Apache Camel integration framework and how it can be used with Akka actors. Camel provides a domain-specific language and components for integration patterns and protocols. Akka actors handle asynchronous message processing and can be used as Camel consumers and producers through Akka-Camel integration. Consumer actors receive messages from Camel endpoints, while producer actors send messages to endpoints. Actor components allow actors to be used directly in Camel routes.
This document provides an overview and agenda for a presentation on Apache ActiveMQ and Apache ServiceMix. The presentation covers installing and configuring ActiveMQ, using ActiveMQ with Spring JMS, ActiveMQ features like message routing and topologies, an introduction to Apache ServiceMix for enterprise service buses and message routing, and options for using ActiveMQ like directly, with message-driven beans, or with Spring message listeners.
Getting started with Apache Camel - jDays 2013Claus Ibsen
In this session will teach you how to get a good start with Apache Camel. We will introduce you to Apache Camel and how Camel its related to Enterprise Integration Patterns. And how you go about using these patterns in Camel routes, written in Java code or XML files.
We will then discuss how you can get started developing with Camel, and how to setup new projects from scratch using Maven and Eclipse tooling.
This session includes live demos that show how to build Camel applications in Java, Spring, OSGi Blueprint and alternative languages such as Scala and Groovy. You will also hear what other features Camel provides out of the box, which can make integration much easier for you.
We also take a moment to look at hawtio, then hot new web console tooling that allows you to get insight into your running Apache Camel applications, which has among others visual route diagrams with tracing/debugging and profiling capabilities.
Before opening up for QA, we will share useful links where you can dive into learning more about Camel.
Sascha Möllering discusses infrastructure as code and provides an overview of VMware SDKs, Chef, and using Chef to configure JBoss middleware. He explains that VMware has multiple SDKs and that the VI Java SDK simplifies development. Chef is introduced as a tool to automate and standardize server configurations. The presentation then covers using Chef recipes to deploy and configure JBoss application servers and integrating with JBoss Operations Network for monitoring.
Enterprise Integration Patterns with ActiveMQRob Davies
This document discusses enterprise integration patterns and deployments using Apache ActiveMQ. It provides an overview of key integration concepts like message channels, routing, types of messages, push and pull integration models, request/reply patterns, and job processing. It also covers deployment patterns such as hub and spoke and failover between data centers. Finally, it introduces Apache Camel as a powerful integration framework that supports these patterns and can be used with ActiveMQ.
Integration using Apache Camel and GroovyClaus Ibsen
Apache Camel is versatile integration library that supports a huge number of components, enterprise integration patterns, and programming languages.
In this this talk I first introduce you to Apache Camel and its concepts. Then we move on to see how you can use the Groovy programming language with Camel as a first class Groovy DSL to build integration flows.
You will also learn how to build a new Camel and Groovy app from scratch from a live demo.
And we also touch how you can use Camel from grails using the grails-camel plugin.
I will also show the web console tools that give you insight into your running Apache Camel applications, including visual route diagrams with tracing, debugging, and profiling capabilities.
This session will be taught with a 50/50 mix of slides and live demos, and it will conclude with Q&A time.
Burr Sutter describes, discusses and demonstrates an industrial/enterprise-oriented architecture associated with large scale sensor rollout, covering critical areas such as ingestion, integration and analytics. You will learn how to connect the physical world to your traditional enterprise IT infrastructure (Apache Camel), supporting high-speed sensor data acquisition (Apache ActiveMQ) with real-time (Apache SparkStreaming) analytics. In addition, we will show-off various IoT developer prototyping platforms like Raspberry Pi, Intel Edison, Arduino, NXP 1768 with mbed, Particle.io Photon and more.
As Mark Twain once said "The reports of my death are greatly exaggerated". This statement may now easily be applied to Java. Even if the official stewards of Java seemed to have lost their enthusiasm, there are many groups and companies supporting and thriving with Java. Innovation is occurring within the enterprise Java space at a constant rate, more organizations are solving new and exciting problems with advanced Java technologies and project. Java is not dead.
The Java Message Service (JMS) API allows Java applications to create, send, receive, and read messages. It defines a common set of interfaces for messaging implementations to enable communication between software components. JMS supports both point-to-point and publish/subscribe messaging domains. Key concepts in JMS include connections, sessions, message producers/consumers, destinations, and connection factories which are administered objects that clients use to access the JMS provider.
The document discusses Java Message Service (JMS) API which allows applications to asynchronously communicate by creating, sending, receiving and reading messages. It describes JMS architecture including administered objects like connection factories and destinations that clients look up, connections to providers, sessions for producing and consuming messages, and message producers and consumers. It also covers point-to-point and publish/subscribe messaging domains and how messages can be consumed synchronously or asynchronously.
This document provides an overview of different JMS message types including TextMessage, ObjectMessage, MapMessage, ByteMessage, and StreamMessage. It describes key features of each message type such as carrying text payloads for TextMessage, serializable Java objects for ObjectMessage, and name-value pairs for MapMessage. Examples are given showing how to set and get content from messages of each type using the appropriate JMS API methods.
Indianapolis mule soft_meetup_12_june_2021ikram_ahamed
This document summarizes an event held by the Indianapolis MuleSoft Meetup Group about JMS capabilities with MuleSoft. The organizer was Ikram Mohamed from OneAmerica and the speaker was Jitendra Bafna from Capgemini. The agenda included introductions, an overview of JMS queues and topics, the JMS connector, design patterns, behavior related to clustering and server groups, and a trivia quiz. Key points discussed were the differences between queues and topics in JMS, how to use the JMS connector in MuleSoft including various operations and design patterns like request-response, ensuring guaranteed delivery and durable topic subscriptions, and how behavior differs when applications are deployed on clusters versus server groups.
This document provides an overview of messaging frameworks and Java Message Service (JMS). It defines messaging as communication between disparate systems and explains why messaging is important for enabling asynchronous and reliable communication. The key concepts covered include messaging fundamentals using a message-oriented middleware, common messaging protocols like AMQP and JMS, JMS domains for point-to-point and publish/subscribe messaging, consuming messages synchronously and asynchronously, the JMS API for creating connections and messages, and best practices for building robust JMS applications. It concludes with an example of designing a drone delivery system using JMS queues.
This document provides an overview of messaging and distributed system design patterns. It discusses how messaging systems provide scalability, independence, and standardization. Common integration approaches like shared databases, file transfer, and remoting are introduced. Key concepts of messaging systems include channels, messages, multi-step delivery, routing, and transformation. Common messaging architecture patterns are then described in 3-4 sentences each, including pipe and filters, message routers, publishers and subscribers, and scatter-gather patterns.
This document provides an overview of distributed systems and distributed computing paradigms. It defines distributed systems as a collection of independent computers that can communicate with each other over a network. It discusses several distributed computing paradigms including message passing, client-server, peer-to-peer, publish/subscribe, remote procedure call (RPC), collaborative applications, and mobile agents. For each paradigm, it provides examples and explanations of how the paradigm works.
I've covered below topics in current presentation:
- Message Queue Introduction
- Architecture
- Key Capabilities
- Simple Use Case
- Difference between Web Service and Message Queue
- ActiveMQ Portal
I'll be adding one more presentation on MQ Testing through Parasoft SOATest.
Please feel free to contact if you need more information.
I've covered Message queue related below points:
- Introduction: MQ Testing
- MQ Architecture
- Key Capabilities
- MQ : Simple Use Case / Purpose
- Difference between Web Service and Message Queue (MQ)
- Shorthand View of MQ Dashboard
I'll be sharing one more presentation on "MQ Testing through Parasoft SOATest".
Please feel free to contact me if you need more information.
Synchronous and asynchronous software communication components allow applications to exchange information. Synchronous components like REST APIs use requests and responses over HTTP to transfer data immediately. Asynchronous message queues decouple systems by allowing producers to send messages without waiting for consumers to process them, improving scalability. Messages in queues can be retrieved when consumers are ready. Real-world examples of asynchronous communication include email and job processing queues that separate workloads across independent systems.
This document provides an overview of Java Message Service (JMS) for asynchronous messaging between software components. Key points include:
- JMS allows applications to asynchronously send and receive messages via queues or topics. This allows components that are not available at the same time to communicate.
- Messages sent via JMS remain in queues until a client receives them, ensuring reliable and guaranteed delivery.
- The document demonstrates a simple example of an order fulfillment scenario using JMS, and provides code samples for a basic message producer client.
- Core JMS concepts like providers, clients, destinations, connection factories and message types are defined to explain the JMS programming model.
ActiveMQ is an open-source message broker written in Java that uses the Java Message Service (JMS). It provides features that help promote communication between distributed systems. ActiveMQ is often used instead of databases for reliable communication between processes because databases can fall over when handling high volumes of messages, whereas message-oriented middleware like ActiveMQ are optimized to handle large volumes of messages efficiently. Key components of ActiveMQ include KahaDB for fast persistence and JMS, which is an API that supports formal messaging between systems.
Integration Patterns With Spring integrationEldad Dor
Enterprise Integration Patterns (EIP) is well implemented in
Spring Integration, let's take a look
source code:
https://github.com/EldadDor/Spring-Integration-ShowCase
The document discusses Java Message Service (JMS) and its architecture, describing key JMS concepts like connections, sessions, message producers and consumers, and administered objects. It also covers message types and how to implement asynchronous messaging using a message-driven bean within a J2EE application.
The document summarizes JMS (Java Messaging Service), including its architecture, core concepts like messaging domains (point-to-point and publish/subscribe), administered objects like connection factories and destinations, and how to create and use message producers, consumers, listeners and messages. JMS enables loosely coupled, asynchronous communication between distributed applications using messages sent to queues or topics.
MuleSoft Surat Virtual Meetup#26 - Implementing Hybrid MuleSoft Runtime - Anypoint Clustering and Server Group | Competing and Fault Tolerance Queue Consumer Pattern
-Explain the basics JMS
- Use API of Java
References
YouTube link :
https://www.youtube.com/playlist?list=PLtDIUAtyP4lhV7CsYfLuIx26UeG4J-ujZ
GitHub :
https://github.com/Ghadeerof
This document provides an overview of Java Message Service (JMS) and how to use it. JMS allows applications to asynchronously and reliably send and receive messages. It uses Java Naming and Directory Interface (JNDI) to lookup connection information instead of hardcoding addresses. Sample code demonstrates how to publish messages to a topic and subscribe to receive them. JMS provides loose coupling between applications and supports point-to-point and publish-subscribe messaging models.
The document provides an overview of the Java Message Service (JMS) API. It discusses how JMS allows for asynchronous and reliable messaging between loosely coupled applications. JMS uses the Java Naming and Directory Interface (JNDI) to abstract provider details and make administrative objects easily organized. Example code is given to demonstrate publishing messages to a topic and subscribing to receive messages from a topic.
Blockchain technology is transforming industries and reshaping the way we conduct business, manage data, and secure transactions. Whether you're new to blockchain or looking to deepen your knowledge, our guidebook, "Blockchain for Dummies", is your ultimate resource.
Choose our Linux Web Hosting for a seamless and successful online presencerajancomputerfbd
Our Linux Web Hosting plans offer unbeatable performance, security, and scalability, ensuring your website runs smoothly and efficiently.
Visit- https://onliveserver.com/linux-web-hosting/
Sustainability requires ingenuity and stewardship. Did you know Pigging Solutions pigging systems help you achieve your sustainable manufacturing goals AND provide rapid return on investment.
How? Our systems recover over 99% of product in transfer piping. Recovering trapped product from transfer lines that would otherwise become flush-waste, means you can increase batch yields and eliminate flush waste. From raw materials to finished product, if you can pump it, we can pig it.
Advanced Techniques for Cyber Security Analysis and Anomaly DetectionBert Blevins
Cybersecurity is a major concern in today's connected digital world. Threats to organizations are constantly evolving and have the potential to compromise sensitive information, disrupt operations, and lead to significant financial losses. Traditional cybersecurity techniques often fall short against modern attackers. Therefore, advanced techniques for cyber security analysis and anomaly detection are essential for protecting digital assets. This blog explores these cutting-edge methods, providing a comprehensive overview of their application and importance.
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-InTrustArc
Six months into 2024, and it is clear the privacy ecosystem takes no days off!! Regulators continue to implement and enforce new regulations, businesses strive to meet requirements, and technology advances like AI have privacy professionals scratching their heads about managing risk.
What can we learn about the first six months of data privacy trends and events in 2024? How should this inform your privacy program management for the rest of the year?
Join TrustArc, Goodwin, and Snyk privacy experts as they discuss the changes we’ve seen in the first half of 2024 and gain insight into the concrete, actionable steps you can take to up-level your privacy program in the second half of the year.
This webinar will review:
- Key changes to privacy regulations in 2024
- Key themes in privacy and data governance in 2024
- How to maximize your privacy program in the second half of 2024
Implementations of Fused Deposition Modeling in real worldEmerging Tech
The presentation showcases the diverse real-world applications of Fused Deposition Modeling (FDM) across multiple industries:
1. **Manufacturing**: FDM is utilized in manufacturing for rapid prototyping, creating custom tools and fixtures, and producing functional end-use parts. Companies leverage its cost-effectiveness and flexibility to streamline production processes.
2. **Medical**: In the medical field, FDM is used to create patient-specific anatomical models, surgical guides, and prosthetics. Its ability to produce precise and biocompatible parts supports advancements in personalized healthcare solutions.
3. **Education**: FDM plays a crucial role in education by enabling students to learn about design and engineering through hands-on 3D printing projects. It promotes innovation and practical skill development in STEM disciplines.
4. **Science**: Researchers use FDM to prototype equipment for scientific experiments, build custom laboratory tools, and create models for visualization and testing purposes. It facilitates rapid iteration and customization in scientific endeavors.
5. **Automotive**: Automotive manufacturers employ FDM for prototyping vehicle components, tooling for assembly lines, and customized parts. It speeds up the design validation process and enhances efficiency in automotive engineering.
6. **Consumer Electronics**: FDM is utilized in consumer electronics for designing and prototyping product enclosures, casings, and internal components. It enables rapid iteration and customization to meet evolving consumer demands.
7. **Robotics**: Robotics engineers leverage FDM to prototype robot parts, create lightweight and durable components, and customize robot designs for specific applications. It supports innovation and optimization in robotic systems.
8. **Aerospace**: In aerospace, FDM is used to manufacture lightweight parts, complex geometries, and prototypes of aircraft components. It contributes to cost reduction, faster production cycles, and weight savings in aerospace engineering.
9. **Architecture**: Architects utilize FDM for creating detailed architectural models, prototypes of building components, and intricate designs. It aids in visualizing concepts, testing structural integrity, and communicating design ideas effectively.
Each industry example demonstrates how FDM enhances innovation, accelerates product development, and addresses specific challenges through advanced manufacturing capabilities.
YOUR RELIABLE WEB DESIGN & DEVELOPMENT TEAM — FOR LASTING SUCCESS
WPRiders is a web development company specialized in WordPress and WooCommerce websites and plugins for customers around the world. The company is headquartered in Bucharest, Romania, but our team members are located all over the world. Our customers are primarily from the US and Western Europe, but we have clients from Australia, Canada and other areas as well.
Some facts about WPRiders and why we are one of the best firms around:
More than 700 five-star reviews! You can check them here.
1500 WordPress projects delivered.
We respond 80% faster than other firms! Data provided by Freshdesk.
We’ve been in business since 2015.
We are located in 7 countries and have 22 team members.
With so many projects delivered, our team knows what works and what doesn’t when it comes to WordPress and WooCommerce.
Our team members are:
- highly experienced developers (employees & contractors with 5 -10+ years of experience),
- great designers with an eye for UX/UI with 10+ years of experience
- project managers with development background who speak both tech and non-tech
- QA specialists
- Conversion Rate Optimisation - CRO experts
They are all working together to provide you with the best possible service. We are passionate about WordPress, and we love creating custom solutions that help our clients achieve their goals.
At WPRiders, we are committed to building long-term relationships with our clients. We believe in accountability, in doing the right thing, as well as in transparency and open communication. You can read more about WPRiders on the About us page.
Measuring the Impact of Network Latency at TwitterScyllaDB
Widya Salim and Victor Ma will outline the causal impact analysis, framework, and key learnings used to quantify the impact of reducing Twitter's network latency.
Best Programming Language for Civil EngineersAwais Yaseen
The integration of programming into civil engineering is transforming the industry. We can design complex infrastructure projects and analyse large datasets. Imagine revolutionizing the way we build our cities and infrastructure, all by the power of coding. Programming skills are no longer just a bonus—they’re a game changer in this era.
Technology is revolutionizing civil engineering by integrating advanced tools and techniques. Programming allows for the automation of repetitive tasks, enhancing the accuracy of designs, simulations, and analyses. With the advent of artificial intelligence and machine learning, engineers can now predict structural behaviors under various conditions, optimize material usage, and improve project planning.
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
Best Practices for Effectively Running dbt in Airflow.pdfTatiana Al-Chueyr
As a popular open-source library for analytics engineering, dbt is often used in combination with Airflow. Orchestrating and executing dbt models as DAGs ensures an additional layer of control over tasks, observability, and provides a reliable, scalable environment to run dbt models.
This webinar will cover a step-by-step guide to Cosmos, an open source package from Astronomer that helps you easily run your dbt Core projects as Airflow DAGs and Task Groups, all with just a few lines of code. We’ll walk through:
- Standard ways of running dbt (and when to utilize other methods)
- How Cosmos can be used to run and visualize your dbt projects in Airflow
- Common challenges and how to address them, including performance, dependency conflicts, and more
- How running dbt projects in Airflow helps with cost optimization
Webinar given on 9 July 2024
Scaling Connections in PostgreSQL Postgres Bangalore(PGBLR) Meetup-2 - MydbopsMydbops
This presentation, delivered at the Postgres Bangalore (PGBLR) Meetup-2 on June 29th, 2024, dives deep into connection pooling for PostgreSQL databases. Aakash M, a PostgreSQL Tech Lead at Mydbops, explores the challenges of managing numerous connections and explains how connection pooling optimizes performance and resource utilization.
Key Takeaways:
* Understand why connection pooling is essential for high-traffic applications
* Explore various connection poolers available for PostgreSQL, including pgbouncer
* Learn the configuration options and functionalities of pgbouncer
* Discover best practices for monitoring and troubleshooting connection pooling setups
* Gain insights into real-world use cases and considerations for production environments
This presentation is ideal for:
* Database administrators (DBAs)
* Developers working with PostgreSQL
* DevOps engineers
* Anyone interested in optimizing PostgreSQL performance
Contact info@mydbops.com for PostgreSQL Managed, Consulting and Remote DBA Services
Mitigating the Impact of State Management in Cloud Stream Processing SystemsScyllaDB
Stream processing is a crucial component of modern data infrastructure, but constructing an efficient and scalable stream processing system can be challenging. Decoupling compute and storage architecture has emerged as an effective solution to these challenges, but it can introduce high latency issues, especially when dealing with complex continuous queries that necessitate managing extra-large internal states.
In this talk, we focus on addressing the high latency issues associated with S3 storage in stream processing systems that employ a decoupled compute and storage architecture. We delve into the root causes of latency in this context and explore various techniques to minimize the impact of S3 latency on stream processing performance. Our proposed approach is to implement a tiered storage mechanism that leverages a blend of high-performance and low-cost storage tiers to reduce data movement between the compute and storage layers while maintaining efficient processing.
Throughout the talk, we will present experimental results that demonstrate the effectiveness of our approach in mitigating the impact of S3 latency on stream processing. By the end of the talk, attendees will have gained insights into how to optimize their stream processing systems for reduced latency and improved cost-efficiency.
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3. Introduction
● ActiveMQ is used in enterprise service bus
implementations such as Apache ServiceMix and
Mule.
● Apache ActiveMQ is a message broker which fully
implements the Java Messaging Service API. It can
be used by programs written Java,C/C++,.NET,PHP
etc.
4. JMS (Java Messaging Service)
The Java Message Service (JMS) API is a Java Message Oriented Middleware (MOM)
API for sending messages between two or more clients. It is a messaging standard that
allows application components based on the Java Enterprise Edition (Java EE) to
create, send, receive, and read messages. An application can communicate with any
number of applications using JMS.This communication is loosely coupled. Instead,
those applications are communicated by connecting to a common destination. An
application can send messages to the destination and can take messages from the
same destination.The concept is shown below as a schematic.This technology is too
simple and it can be easily integrated with existing applications so that those
applications can communicate each other.
5. Destination
Type
Description
Topic In JMS a Topic implements publish and subscribe semantics. When you
publish a message it goes to all the subscribers who are interested - so zero
to many subscribers will receive a copy of the message. Only subscribers
who had an active subscription at the time the broker receives the message
will get a copy of the message.
Queue A JMS Queue implements load balancer semantics. A single message will be
received by exactly one consumer. If there are no consumers available at the
time the message is sent it will be kept until a consumer is available that can
process the message. If a consumer receives a message and does not
acknowledge it before closing then the message will be redelivered to
another consumer. A queue can have many consumers with messages load
balanced across the available consumers.
6. JMS Sessions
A session is a single-threaded context for producing and consuming messages. We use
sessions to create the following:
● Message producers
● Message consumers
● Messages
● Destination
When a client creates a JMS session it must specify the mode in which the Session will
acknowledge the messages that it receives and dispatches. The modes supported are
summarized in the table below.
7. Acknowledge
Mode
Description
AUTO_ACKNOWL
EDGE
With this acknowledgement mode, the session automatically acknowledges
a client's receipt of a message either when the session has successfully
returned from a call to receive or when the message listener the session has
called to process the message successfully returns.
CLIENT_ACKNOW
LEDGE
With this acknowledgement mode, the client acknowledges a consumed
message by calling the message's acknowledge method. Acknowledging a
consumed message acknowledges all messages that the session has
consumed. When client acknowledgement mode is used, a client may build
up a large number of unacknowledged messages while attempting to
process them. A JMS provider should provide administrators with a way to
limit client overrun so that clients are not driven to resource exhaustion and
ensuing failure when some resource they are using is temporarily blocked.
DUPS_OK_ACKN
OWLEDGE
This acknowledgement mode instructs the session to lazily acknowledge the
delivery of messages. This is likely to result in the delivery of some duplicate
messages if the JMS provider fails, so it should only be used by consumers
that can tolerate duplicate messages. Use of this mode can reduce session
overhead by minimizing the work the session does to prevent duplicates.
SESSION_TRANS
ACTED
Session is Transacted and the acknowledge of messages is handled
internally.
INDIVIDUAL_ACK
NOWLEDGE
Acknowledges are applied to a single message only. Unlike
CLIENT_ACKNOWLEDGE where the acknowledgement applies to all
messages received up to that point for the entire session, this mode applied
only to a single message allowing the client to be more selective about
which messages are acknowledged.
8. Messaging Domains
JMS API supports Point-to-Point and Publish-Subscribe approaches.
Point-to-Point Approach :
The point to point approach consists of a sender , a receiver and a queue.The sender
addresses a message to the queue, and the receiving clients extract messages from the
queues established to hold their messages. The queue keeps the message till a receiving
client receives it or till the message expires. While any number of producers can send
messages to the queue, each message is guaranteed to be delivered, and consumed by
one consumer.
9. Publish/Subscribe Approach :
The publish/subscribe model supports publishing messages to a particular message topic.
Subscribers may register interest in receiving messages on a particular message topic. In
this model, neither the publisher nor the subscriber knows about each other. A good analogy
for this is an anonymous bulletin board.
● Zero or more consumers will receive the message.
● There is a timing dependency between publishers and subscribers. The publisher
has to create a message topic for clients to subscribe. The subscriber has to remain
continuously active to receive messages, unless it has established a durable
subscription. In that case, messages published while the subscriber is not connected
will be redistributed whenever it reconnects.
10. A JMS message has 3 parts
a)header :- The header contains meta-information about the message—
who sent it, where it’s going, and so on.
b)body :- As the name suggests it is the body of messages. JMS API allows five
types of message bodies.
1. TextMessage :- Body contains String data
2. ByteMessage :- Body contains byte data
3. MapMessage :- Body contains data in key/value pair
4. StreamMessage :-Body contains a stream of primitive values
5. ObjectMessage : – Body contains an object
6. Message :- Nothing in body. Only header and properties.
c)properties :- Additional properties other than header.
11. Why Messaging as Communication Style?
● File Transfer and Shared Database enable applications to share their data
but not their functionality.
● Remote Procedure Invocation enables applications to share functionality, but
it tightly couples them as well. Often the challenge of integration is about
making collaboration between separate systems as timely as possible,
without coupling systems together in such a way that they become unreliable
either in terms of application execution or application development.
● The data transfer should be asynchronous so that the sender does not need
to wait on the receiver, especially when retry is necessary.
● Use Messaging to transfer packets of data frequently, immediately, reliably,
and asynchronously, using customizable formats.
12. Why ActiveMQ?
Imagine you need to communicate with two or more systems. A common
approach these days will be web services which is fine if you need an answers
right away.
However: web services can be down and not available - what do you do then?
Putting your message into a message queue (which has a component on your
machine/server, too) typically will work in this scenario - your message just
doesn't get delivered and thus processed right now - but it will later on, when
the other side of the service comes back online.
The Message Queue receives the message, places it in the proper queue, and
waits for the application to retrieve the message when ready.
13. Connect an application to a messaging channel using a Message Endpoint, a
client of the messaging system that the application can then use to send or
receive Messages.We need a message endpoint to connect the system
explicitly to the integration solution. The endpoint can be a special piece of code
or a channel adapter provided by an integration software vendor.
For example, one data format may store the customer name in two fields, called
FIRST_NAME and LAST_NAME, while the other system may use a single field
called Customer_Name. Likewise, one system may support multiple customer
addresses while the other system only supports a single address. Because the
internal data format of an application can often not be changed the middleware
needs to provide some mechanism to convert one application’s data format in
the other’s. We call this step translation.
14. So far we can send data from one system to another and accommodate
differences in data formats. What happens if we integrate more than two
systems? Where does the data have to be moved? We could expect each
application to specify the target system(s) for the data it is sending over the
channel. For example, if the customer address changes in the customer care
system we could make that system responsible for sending the data to all other
systems that store copies of the customer address. As the number of systems
increases this becomes very tedious and requires the sending system to have
knowledge about all other systems. Every time a new system is added, the
customer care system would have to be adjusted to the new environment.
Things would be a lot easier of the middleware could take care of sending
messages to the correct places. This is the role of a routing component such as
a message broker.
Integration solutions can quickly become complex because they deal with
multiple applications, data formats, channels, routing and transformation. All
these elements may be spread across multiple operating platforms and
geographic locations. In order to have any idea what is going on inside the
system we need a systems management function. This subsystem monitors the
flow of data, makes sure that all applications and components are available and
reports error conditions to a central location.
15. When a standard message is sent to a queue from a producer, it is sent to the broker,
which persists it in its message store. By default this is in KahaDB, but it can configured to
be stored in memory, which buys performance at the cost of reliability. Once the broker
has confirmation that the message has been persisted in the journal (the terms journal and
message store are often used interchangeably), it responds with an acknowledgement
back to the producer. The thread sending the message from the producer is blocked at this
time.
16. On the consumption side, when a message listener is registered or a call to receive() is
made, the broker creates a subscription to that queue. Messages are fetched from the
message store and passed to the consumer; it’s usually done in batches, and the fetching
is a lot more complex than simply read from disk, but that’s the general idea. With the
default behaviour, assuming the Session.AUTO_ACKNOWLEDGE is being used, the
consumer will acknowledge that the message has been received before processing it. On
receiving the acknowledgement, the broker updates the message store marking that
message as consumed, or just deletes it (this depends on the persistence mechanism).
18. This figure also illustrates two important messaging concepts:
1. Send and forget
—In step 2, the sending application sends the message to the message channel.
Once that send is complete, the sender can go on to other work while the
messaging system transmits the message in the background. The sender can be
confident that the receiver will eventually receive the message and does not
have to wait until that happens.
2. Store and forward
—In step 2, when the sending application sends the message to the message
channel, the messaging system stores the message on the sender’s computer,
either in memory or on disk. In step 3, the messaging system delivers the
message by forwarding it from the sender’s computer to the receiver’s computer,
and then stores the message once again on the receiver’s computer. This store-and-
forward process may be repeated many times as the message is moved
from one computer to another until it reaches the receiver’s computer.
19. Benefits :
Using messaging as an integration or communication style leads to many benefits such as:
● Allowing applications built with different languages and on different operating systems to
integrate with each other
● Location transparency – client applications don’t need to know where the service
applications are located
● Reliable communication – the producers/consumers of messages don’t have to be
available at the same time, or certain segments along the route of the message can go
down and come back up without impacting the message getting to the service/consumer
● Scaling – can scale horizontally by adding more services that can handle the messages if
too many messages are arriving
● Asynchronous communication – a client can fire a message and continue other
processing instead of blocking until the service has sent a response; it can handle the
response message only when the message is ready
● Reduced coupling – the assumptions made by the clients and services are greatly
reduced as a result of the previous 5 benefits. A service can change details about itself,
including its location, protocol, and availability, without affecting or disrupting the client.
23. Introduction
● Apache Camel “a powerful open source integration framework based on
known Enterprise Integration Patterns with powerful Bean Integration”.
● Camel is a mediation and routing engine that lets you implement EIP’s. It
uses a simple URI notation to identify the different transport and messaging
models.
● Camel is open-source integration framework which allows you to build routes
for integration scenario's quickly and efficiently. You can deploy these routes
directly on ServiceMix by deploying the plain Spring XML route or by
packaging the route in an OSGi bundle.
● The best thing about Camel is that it can be embedded into your current java
application to implement integrations. On a larger scale Camel is part of
Apache ServiceMix ESB.
● The Camel project was started in early 2007.
24. About Camel
● Building complex systems from scratch is a very costly endeavor, and one
that’s almost never successful. Apache Camel is such an integration
framework that provides simple, manageable abstractions for the complex
systems you’re integrating and the “glue” for plugging them together
seamlessly.
● Camel’s most important features: message routing. At the core of the Camel
framework is a routing engine, or more precisely a routing engine builder. It
allows you to define your own routing rules, decide from which sources to
accept messages, and determine how to process and send those messages
to other destinations.
For example: JMS -> JSON, HTTP -> JMS or funneling FTP -> JMS, HTTP
-> JMS, JSON -> JMS
25. ● Camel has two main ways of defining routing rules: the Java-based domain
specific language (DSL) and the Spring XML configuration format.
● One of the fundamental principles of Camel is that it makes no assumptions
about the type of data you need to process. This is an important point,
because it gives you, the developer, an opportunity to integrate any kind of
system, without the need to convert your data to a canonical format.
● Camel isn’t an enterprise service bus(ESB), although some call Camel a
lightweight ESB because of its support for routing, transformation,
monitoring, orchestration, and so forth. Camel doesn’t have a container or a
reliable message bus, but it can be deployed in one, such as Open-ESB or
the ServiceMix. For that reason, we prefer to call Camel an integration
framework rather than an ESB. Camel was designed not to be a server or
ESB but instead to be embedded in whatever platform you choose.
26. Camel’s message model
In Camel, there are two abstractions for modeling messages,
■ org.apache.camel.Message
—The fundamental entity containing the data being carried and routed in Camel.
—The Message interface provides an abstraction for a single message, such as a
request, reply or exception message. In Camel terminology, the request, reply and
exception messages are called in, out and fault messages.
■ org.apache.camel.Exchange
—The Camel abstraction for an exchange of messages. This exchange of messages
has an “in” message and as a reply, an “out” message.
—The Exchange interface provides an abstraction for an exchange of messages,
that is, a request message and its corresponding reply or exception message.
27. Example on Routing Files:
Suppose you need to read files from one directory (data/inbox), process them in
some way, and write the result to another directory (data/outbox). For simplicity,
you’ll skip the processing, so your output will be merely a copy of the original file.
Below figure illustrates this process.
It looks pretty simple, right? Here’s a possible solution using pure Java (with no
Camel) but it still results in 34 lines of code. You have to use low-level file APIs
and ensure that resources get closed properly, a task that can easily go wrong.
But if an integration framework like Apache Camel is used, we can create a file-polling
route in just one line of Java code
29. CamelContext
A CamelContext object represents the Camel runtime system.
CamelContext is the heart of Camel its where all the routes, endpoints,
components, etc. is registered. You typically have one CamelContext object in
an application. A typical application executes the following steps.
● Create a CamelContext object.
● Add endpoints – and possibly Components, to the CamelContext object.
● Add routes to the CamelContext object to connect the endpoints.
● Invoke the start() operation on the CamelContext object. This starts
Camel-internal threads that are used to process the sending, receiving and
processing of messages in the endpoints.
● Eventually invoke the stop() operation on the CamelContext object. Doing
this gracefully stops all the endpoints and Camel-internal threads.
30. Components
Component is confusing terminology; EndpointFactory would have
been more appropriate because a Component is a factory for
creating Endpoint instances.
Processor
The Processor interface represents a class that processes a
message. Notice that the parameter to the process() method is
an Exchange rather than a Message.
RouteBuilders
A route is the step-by-step movement of a Message from an input
queue, through arbitrary types of decision making (such as filters
and routers) to a destination queue (if any). A DSL wires Endpoints
and Processors together to form routes. Camel provides two ways
for an application developer to specify routes. One way is to specify
route information in an XML file. A discussion of that approach is
outside the scope of this document. The other way is through what
Camel calls a Java DSL (domain-specific language).
31. Here are some examples of the DSL using different languages and staying functionally
equivalent:
Java DSL
from("file:data/inbox").to("jms:queue:order");
Spring DSL
<route>
<from uri="file:data/inbox"/>
<to uri="jms:queue:order"/>
</route>
Scala DSL
from "file:data/inbox" -> "jms:queue:order"
These examples are real code, and they show how easily you can route files from a folder to a
JMS queue.
32. Content Based Router
The Content Based Router from the EIP patterns allows you to route
messages to the correct destination based on the contents of the
message exchanges.
The Content-Based Router examines the message content and routes
the message onto a different channel based on data contained in the
message.
33. Message Filter
The Message Filter from the EIP patterns allows you to filter messages.
The Message Filter has only a single output channel. If the message
content matches the criteria specified by the Message Filter, the
message is routed to the output channel. If the message content does
not match the criteria, the message is discarded.