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In this talk, we'll explore how Spring Cloud Stream and its support for Apache Kafka can streamline the process of developing event-driven microservices that use Apache Kafka and its high-throughput capabilities as a backbone. In this hands-on session, we'll examine the general Kafka support provided by Spring Cloud Stream, as well as the building blocks it provides for developing stateful stream processing applications through its support for Kafka Streams library. Along the way, we'll explore various concepts like streams, tables, stream-table duality, interactive queries in stateful stream processing, etc. We'll also venture into seeing how the new functional programming model in Spring Cloud Stream makes it easier to write Kafka- and Kafka Streams-based applications. Speakers: Soby Chacko, Principal Software Engineer, Pivotal; Oleg Zhurakousky, Developer, Pivotal Filmed at SpringOne Platform 2019 SlideShare: 🤍
This video covers how to leverage Kafka Streams using Spring Cloud stream by creating multiple spring boot microservices 📌 Related Links = 🔗 Github code: 🤍 🔗 Kafka setup: 🤍 🔗 Public Domain API: 🤍 📌 Related Videos = 🔗 Spring Boot with Spring Kafka Producer example - 🤍 🔗 Spring Boot with Spring Kafka Consumer example - 🤍 📌 Related Playlist 🔗Spring Boot Primer - 🤍 🔗Spring Cloud Primer - 🤍 🔗Spring Microservices Primer - 🤍 🔗Spring JPA Primer - 🤍 🔗Java 8 Streams - 🤍 🔗Spring Security Primer - 🤍 💥 Join TechPrimers Slack Community: 🤍 💥 Telegram: 🤍 💥 TechPrimer HindSight (Blog): 🤍 💥 Website: 🤍 💥 Slack Community: 🤍 💥 Twitter: 🤍 💥 Facebook: 🤍 💥 GitHub: 🤍 or 🤍 🎬Video Editing: FCP - 🔥 Disclaimer/Policy: The content/views/opinions posted here are solely mine and the code samples created by me are open sourced. You are free to use the code samples in Github after forking and you can modify it for your own use. All the videos posted here are copyrighted. You cannot re-distribute videos on this channel in other channels or platforms. #KafkaStreams #SpringCloudStream #TechPrimers
Spark Programming and Azure Databricks ILT Master Class by Prashant Kumar Pandey - Fill out the google form for Course inquiry. 🤍 - Data Engineering using is one of the highest-paid jobs of today. It is going to remain in the top IT skills forever. Are you in database development, data warehousing, ETL tools, data analysis, SQL, PL/QL development? I have a well-crafted success path for you. I will help you get prepared for the data engineer and solution architect role depending on your profile and experience. We created a course that takes you deep into core data engineering technology and masters it. If you are a working professional: 1. Aspiring to become a data engineer. 2. Change your career to data engineering. 3. Grow your data engineering career. 4. Get Databricks Spark Certification. 5. Crack the Spark Data Engineering interviews. ScholarNest is offering a one-stop integrated Learning Path. The course is open for registration. The course delivers an example-driven approach and project-based learning. You will be practicing the skills using MCQ, Coding Exercises, and Capstone Projects. The course comes with the following integrated services. 1. Technical support and Doubt Clarification 2. Live Project Discussion 3. Resume Building 4. Interview Preparation 5. Mock Interviews Course Duration: 6 Months Course Prerequisite: Programming and SQL Knowledge Target Audience: Working Professionals Batch start: Registration Started Fill out the below form for more details and course inquiries. 🤍 Learn more at 🤍 Best place to learn Data engineering, Bigdata, Apache Spark, Databricks, Apache Kafka, Confluent Cloud, AWS Cloud Computing, Azure Cloud, Google Cloud - Self-paced, Instructor-led, Certification courses, and practice tests. SPARK COURSES - 🤍 🤍 🤍 🤍 🤍 KAFKA COURSES 🤍 🤍 🤍 AWS CLOUD 🤍 🤍 PYTHON 🤍 We are also available on the Udemy Platform Check out the below link for our Courses on Udemy 🤍 = You can also find us on Oreilly Learning 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 = Follow us on Social Media 🤍 🤍 🤍 🤍 🤍 🤍
In this tutorial, you will learn how to create a Spring boot Apache Kafka real-world project step by step. We will create two microservices and use Kafka as a messaging system to exchange messages between microservices. Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines. GitHub link - 🤍 We will read a large amount of real-time stream data from the Wikimedia and then we will write that data to the MySQL database. Lectures or Chapters - Lecture 1. Real-World Project Overview - 0:00:08 Lecture 2. Spring Boot Kafka Project Setup - 0:03:28 Lecture 3. Install and Setup Kafka - 0:04:30 Lecture 4. Wikimedia Producer Spring Boot Project Setup - 0:12:35 Lecture 5. Configure Wikimedia Producer and Create a Topic - 0:21:08 Lecture 6. Wikimedia Producer Implementation - 0:25:54 Lecture 7. Run Wikimedia Producer - 0:41:38 Lecture 8. Kafka Consumer Project Setup - 0:49:49 Lecture 9. Configure Kafka Consumer - 0:54:13 Lecture 10. Kafka Consumer Implementation - 0:57:44 Lecture 11 Configure MySQL Database - 1:04:10 Lecture 12. Save Wikimedia Data into MySQL Database - 1:11:18 #springboot #kafka #microservicios
Microservices - Event Driven with Spring Cloud Stream (Apache Kafka) - From HTTP Rest To Kafka Topic (Foreign event-driven sources) In this series, we will be talking about Microservices patterns associated with Event-Driven Architecture. We will also talk a little bit about Domain Driven Design (but not our focus). In this series, we will create a business case related to Loan Mortgages. We will have some microservices to accomplish this use case. We will cover topics like: - Publish-Subscribe Pattern (vs Point-to-point) - Domain-Driven Design - CQRS, Event-Sourcing, Transaction Outbox Pattern, Command vs Event, DLQ, etc.
Spark Programming and Azure Databricks ILT Master Class by Prashant Kumar Pandey - Fill out the google form for Course inquiry. 🤍 - Data Engineering using is one of the highest-paid jobs of today. It is going to remain in the top IT skills forever. Are you in database development, data warehousing, ETL tools, data analysis, SQL, PL/QL development? I have a well-crafted success path for you. I will help you get prepared for the data engineer and solution architect role depending on your profile and experience. We created a course that takes you deep into core data engineering technology and masters it. If you are a working professional: 1. Aspiring to become a data engineer. 2. Change your career to data engineering. 3. Grow your data engineering career. 4. Get Databricks Spark Certification. 5. Crack the Spark Data Engineering interviews. ScholarNest is offering a one-stop integrated Learning Path. The course is open for registration. The course delivers an example-driven approach and project-based learning. You will be practicing the skills using MCQ, Coding Exercises, and Capstone Projects. The course comes with the following integrated services. 1. Technical support and Doubt Clarification 2. Live Project Discussion 3. Resume Building 4. Interview Preparation 5. Mock Interviews Course Duration: 6 Months Course Prerequisite: Programming and SQL Knowledge Target Audience: Working Professionals Batch start: Registration Started Fill out the below form for more details and course inquiries. 🤍 Learn more at 🤍 Best place to learn Data engineering, Bigdata, Apache Spark, Databricks, Apache Kafka, Confluent Cloud, AWS Cloud Computing, Azure Cloud, Google Cloud - Self-paced, Instructor-led, Certification courses, and practice tests. SPARK COURSES - 🤍 🤍 🤍 🤍 🤍 KAFKA COURSES 🤍 🤍 🤍 AWS CLOUD 🤍 🤍 PYTHON 🤍 We are also available on the Udemy Platform Check out the below link for our Courses on Udemy 🤍 = You can also find us on Oreilly Learning 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 = Follow us on Social Media 🤍 🤍 🤍 🤍 🤍 🤍
Kafka is ideal for log aggregation, particularly for applications that use microservices and are distributed across multiple hosts. This is an example Spring Boot application that uses Log4j2's Kafka appender to send JSON formatted log messages to a Kafka topic. Here's the Github repo: 🤍
This video explain you 1.What is Apache kafka 2. Basic Architecture of Kafka 3. Environment setup for kafka 4.How to publish plain text and object using Kafka GitHub: 🤍 Blogs: 🤍 Facebook group: 🤍 Like & subscribe
In this tutorial, we will be creating a simple Kafka Producer in Java. We will post a simple and Complex message on a Kafka topic using Spring Boot and Spring Kafka GitHub CodeLink: 🤍 Other Video: - How to Install Apache Kafka on Windows: 🤍 Spring Boot Tutorials: 🤍 Quarkus Tutorials: 🤍 Follow us on : Website: 🤍 Facebook: 🤍 Twitter: 🤍 Instagram: 🤍 GitHub: 🤍 My Laptop : ASUS ROG Zephyrus G14, 14" - 🤍 ASUS ROG Zephyrus G14, 14" (US) - 🤍 Audio Gear : Maono AU-A04 Condenser Microphone : 🤍 Maono AU-A04 Condenser Microphone (US) :🤍 Secondary Audio : Maono AU-100 Condenser Clip On Lavalier Microphone : 🤍 Recommended Books: Mastering Spring Boot 2.0 (Kindle): 🤍 Mastering Spring Boot 2.0 (US) : 🤍 Building Microservices(Kindle) : 🤍 Building Microservices(US) : 🤍 Spring Boot in Action : 🤍 Spring Boot in Action (US) : 🤍 Spring Microservices in Action : 🤍 Spring Microservices in Action(US): 🤍 Music: - Otis McMusic (Sting): 🤍 Hear the Noise (Sting): 🤍 Song of Mirrors: 🤍 “Sound effects obtained from 🤍“ #Kafka #SpringKafka #Producer #DailyCodeBuffer #ApacheKafka #Apache #Spring #SpringBoot
Data transformation with Spring Cloud Stream using Function. GitHub: 🤍 In this series, we will be talking about Microservices patterns associated with Event-Driven Architecture. We will also talk a little bit about Domain Driven Design (but not our focus). In this series, we will create a business case related to Loan Mortgages. We will have some microservices to accomplish this use case. We will cover topics like: - Publish-Subscribe Pattern (vs Point-to-point) - Domain-Driven Design - CQRS, Event-Sourcing, Transaction Outbox Pattern, Command vs Event, DLQ - Test Coontainer - Spring Cloud Contract, etc.
Spring Boot Microservices Project Example - Part 8 | Event Driven Architecture using Kafka In this video, we will explore implementing Event Driven Architecture pattern in our microservices project using Kafka as the message broker. Source Code 🤍 ⭐️⭐️ You can follow me on Social Media through the below Links⭐️⭐️ Twitter: 🤍 Blog: 🤍 Dev.to: 🤍 Facebook Page: 🤍
In this video I will show how to configure Spring Cloud to publish and read messages from Apache Kafka for the Message Queuing pattern. I will show how to configure Spring Cloud for both the raw Apache Kafka dependency and for the Stream dependency. This is the fifth video of the playlist where I will build a microservices architecture for a webpage, how to create microservices with Spring Boot and Spring Cloud, and how to handle the microservices with Docker and Kubernetes: 🤍 Content: * what is the messages queuing pattern; * how Apache Kafka implements the message queuing pattern; * how to configure Spring Cloud to publish and read from Apache Kafka; * how to configure Spring Cloud Streams to publish and read from Apache Kafka via Streams. Repository: 🤍 My NEW eBook: 🤍 My Spring Boot Academy: 🤍 Facebook: 🤍 Twitter: 🤍 Buy Me a Coffee: 🤍 Icons: * Servers by Alexander Skowalsky from NounProject.com
🤍 | Learn how to annotate a Java class with KafkaListener, set a topic to subscribe to, and specify a deserialization method. After running, you'll see the producer messages you set up in a previous lesson arriving from Kafka on Confluent Cloud (i.e. proceeding from your producer class through Confluent Cloud back to your consumer class). Verify this using a client on Confluent Cloud itself, where you can also see metrics. Use the promo code SPRING101 to get $25 of free Confluent Cloud usage: 🤍 Promo code details: 🤍 LEARN MORE ► Kafka Listeners – Explained: 🤍 ► Annotation Type KafkaListener: 🤍 ► KafkaListener Annotation Example: 🤍 CONNECT Subscribe: 🤍 Site: 🤍 GitHub: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Instagram: 🤍 ABOUT CONFLUENT Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit 🤍confluent.io. #kafka #springboot #java
The talk from Java Fest 2020 Online conference. Presentation: 🤍 Fb: 🤍 Website: 🤍 В процессе доклада напишем приложение, использующее Kafka Streams и Spring, в реальном времени обрабатывающее данные датчика погоды Raspberry Pi. Разберёмся как течёт время в Kafka Streams и почему это грозит вам бессонными ночами debug’a. Вы узнаете как обрабатывать потоки данных в Kafka c помощью библиотеки Kafka Streams и абстракций Spring Cloud. Мы обсудим окна, агрегации, графы обработки данных и топологии. Напоследок, обсудим нюансы деплоя Kafka Streams приложений. Java is a registered trademark of Oracle and/or its affiliates, used by permission.
Hi Spring fans! In this installment of Spring Tips we look at stream processing in Spring Boot applications with Apache Kafka, Apache Kafka Streams and the Spring Cloud Stream Kafka Streams binder. presenter: Josh Long 🤍
How to implement asynchronous communication between microservices using Kafka, Create Kafka cluster in Confluent Cloud.
🤍 | Learn to set up Cloud Schema Registry with Spring Boot, first enabling it in Confluent Cloud then collecting your endpoint and credentials. The latter will need to be added to your Spring application along with some dependencies. Use the promo code SPRING101 to get $25 of free Confluent Cloud usage: 🤍 Promo code details: 🤍 LEARN MORE ► Using Schema Registry and Avro in Spring Boot Applications: 🤍 ► Quick Start for Schema Management on Confluent Cloud: 🤍 ► Schema Registry and Confluent Cloud: 🤍 ► Confluent Cloud Schema Registry Tutorial: 🤍 CONNECT Subscribe: 🤍 Site: 🤍 GitHub: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Instagram: 🤍 ABOUT CONFLUENT Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit 🤍confluent.io. #kafka #springboot #java
Kafka is becoming popular messaging system due to its upscaling and downscaling Features and the ease of Locating the message and simplicity of structure of the message . This video gives an Introduction to Kafka with Spring Boot. pre-requisites . Follow the previous Video at : Kafka with Spring Boot Introduction-1: 🤍 Kafka with Spring Boot Introduction-2: 🤍 Kafka with Spring Boot Introduction-3: 🤍 The remaining episode gives you an Idea of How to Publish them . Stay Tuned. Code details are available at 🤍
Github link: 🤍 In summary, a dead letter queue is a message queue used to store messages that could not be delivered to their intended recipient due to various reasons, such as invalid format or system outage. The messages can be reprocessed or analysed to identify and fix the root cause of the failure. Stateful retries refer to a mechanism for retrying failed operations in a way that takes into account the state of the previous attempts. In other words, stateful retries keep track of previous attempts and use this information to make more informed decisions about how to retry the operation. #kafka #springcloud #deadletterqueue #springboot #springcloudstream
Spark Programming and Azure Databricks ILT Master Class by Prashant Kumar Pandey - Fill out the google form for Course inquiry. 🤍 - Data Engineering using is one of the highest-paid jobs of today. It is going to remain in the top IT skills forever. Are you in database development, data warehousing, ETL tools, data analysis, SQL, PL/QL development? I have a well-crafted success path for you. I will help you get prepared for the data engineer and solution architect role depending on your profile and experience. We created a course that takes you deep into core data engineering technology and masters it. If you are a working professional: 1. Aspiring to become a data engineer. 2. Change your career to data engineering. 3. Grow your data engineering career. 4. Get Databricks Spark Certification. 5. Crack the Spark Data Engineering interviews. ScholarNest is offering a one-stop integrated Learning Path. The course is open for registration. The course delivers an example-driven approach and project-based learning. You will be practicing the skills using MCQ, Coding Exercises, and Capstone Projects. The course comes with the following integrated services. 1. Technical support and Doubt Clarification 2. Live Project Discussion 3. Resume Building 4. Interview Preparation 5. Mock Interviews Course Duration: 6 Months Course Prerequisite: Programming and SQL Knowledge Target Audience: Working Professionals Batch start: Registration Started Fill out the below form for more details and course inquiries. 🤍 Learn more at 🤍 Best place to learn Data engineering, Bigdata, Apache Spark, Databricks, Apache Kafka, Confluent Cloud, AWS Cloud Computing, Azure Cloud, Google Cloud - Self-paced, Instructor-led, Certification courses, and practice tests. SPARK COURSES - 🤍 🤍 🤍 🤍 🤍 KAFKA COURSES 🤍 🤍 🤍 AWS CLOUD 🤍 🤍 PYTHON 🤍 We are also available on the Udemy Platform Check out the below link for our Courses on Udemy 🤍 = You can also find us on Oreilly Learning 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 = Follow us on Social Media 🤍 🤍 🤍 🤍 🤍 🤍
What is Spring Cloud Stream? Learn Spring Cloud Stream with pub-sub model. Queries Solved - Spring Cloud Stream - Spring Cloud Stream with kafka - Spring Cloud Stream with Rabbitmq #Spring Cloud Stream #kafka #RabbitMq Github URL for Source code :- 🤍 Don't click this: 🤍 If you like the video , Please do subscribe my channel. Keep Supporting me so that I can Continue to provide you free content. - Thank you for watching -
🤍 | Learn how to inject a StreamsBuilder class to initiate a Kafka Streams application in Spring. In your StreamsBuilder class you'll set up a serializer/deserializer, select a topic to read, process topic text with regexes so you can count words, then group by key. You'll then create a new topic with TopicBuilder to send your word counts to a topic on Confluent Cloud. View your topics on Confluent Cloud, then in your Spring application with KafkaListener. Finally, build a REST endpoint to access a state store for your Spring application. Store your word counts in Kafka Streams so they are available, then query them via REST. Use the promo code SPRING101 to get $25 of free Confluent Cloud usage: 🤍 Promo code details: 🤍 LEARN MORE ► Class StreamsBuilder: 🤍 ► KafkaStreams Interactive Queries and gRPC: 🤍 ► KafkaStreams, Spring Boot, and Confluent Cloud: 🤍 ► What's New in Kafka Streams Metrics API 2.7.0: 🤍 CONNECT Subscribe: 🤍 Site: 🤍 GitHub: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Instagram: 🤍 ABOUT CONFLUENT Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit 🤍confluent.io. #kafka #springboot #java
A quick introduction to how Apache Kafka works and differs from other messaging systems using an example application. In this video I explain partitioning, consumer offsets, replication and many other concepts found in Kafka. Please support me through my Udemy courses: Pass your coding interview in Java : 🤍 Python: 🤍 Ruby: 🤍 JavaScript: 🤍 Learn Dynamic Programming in, Java: 🤍 Python: 🤍 Ruby: 🤍 Multithreading in, Go Lang: 🤍 Python: 🤍 Java: 🤍 Blog: 🤍
This video will show you how to use Spring Cloud Stream + Kafka to aggregate min, max based on windowed-event-time in the fast ways (real-time). As long as data arrives in your data ingestion platform, it will be aggregated immediately, even with the late arriving records. It will help us to resolve 4 common problem with typical batch processing: real-time, accuracy with late arriving records, scalability/no performance issues with db query, alerts. Website: 🤍 Github: 🤍 Kafka: 🤍 Spring Cloud Stream: 🤍 © Copyright 2018 by Justin Nguyen
Use the promo code SPRINGSTREAMS200 to receive an additional $200 of free Confluent Cloud usage. VIDEO LINKS Confluent Cloud: 🤍 Code from today's stream: 🤍 Kafka Summit: 🤍 Kafkathon 2020: 🤍 Viktor's talk on SpringOne: 🤍 Spring Initializr: 🤍 Learn Kafka: 🤍 GCP Ping: 🤍 Can Your Kafka Consumers Handle a Poison Pill?: 🤍 Configuring default SerDes in Kafka Streams: 🤍 Enabling/disabling caching in Kafka Streams: 🤍 TIMESTAMPS 0:00 - We're live! 7:23 - Welcome to Kafka Summit! 11:40 - Kafkathon 2020 16:23 - Getting started with Spring Boot and Kafka Streams 34:30 - Connecting to Confluent Cloud 38:55 - Fixing errors by creating topic explicitly 43:50 - Vote for the next episode (it could be error handling practices!) 45:30 - Fixing errors by increasing the replication factor 48:50 - Setting up the Confluent Cloud CLI tool to produce messages to a cloud topic 51:30 - Fixing StreamsException/ClassCastException by explicitly defining SerDes 58:22 - Viktor is quoting a very famous character from a very famous movie 1:05:20 - A few words on Kafka Streams caching CONNECT Subscribe: 🤍 Site: 🤍 GitHub: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Instagram: 🤍 ABOUT CONFLUENT Confluent, founded by the creators of Apache Kafka®, enables organizations to harness business value of live data. The Confluent Platform manages the barrage of stream data and makes it available throughout an organization. It provides various industries, from retail, logistics and manufacturing, to financial services and online social networking, a scalable, unified, real-time data pipeline that enables applications ranging from large volume data integration to big data analysis with Hadoop to real-time stream processing. To learn more, please visit 🤍 #confluent #apachekafka #kafka
This video covers Spring Boot with Spring kafka consumer Example 🔗Github Code: 🤍 🔗Kafka Producer Video: 🤍 📌 Related Playlist 🔗Spring Boot Primer - 🤍 🔗Spring Cloud Primer - 🤍 🔗Spring Microservices Primer - 🤍 🔗Spring JPA Primer - 🤍 🔗Java 8 Streams - 🤍 🔗Spring Security Primer - 🤍 🔗Containers Primer - 🤍 🔗Kubernetes Primer - 🤍 🔗AWS Primer - 🤍 💥Join TechPrimers Slack Community: 🤍 💥Telegram: 🤍 💥TechPrimer HindSight (Blog): 🤍 💥Website: 🤍 💥Slack Community: 🤍 💥Twitter: 🤍 💥Facebook: 🤍 💥GitHub: 🤍 or 🤍 🎬Video Editing: iMovie 🎼Background Music: Broke For Free - Day Bird 🤍 The Passion HiFi - What We Came To Do Joakin Karud Dyalla - 🔥 Disclaimer/Policy: The content/views/opinions posted here are solely mine and the code samples created by me are open sourced. You are free to use the code samples in Github after forking and you can modify it for your own use. All the videos posted here are copyrighted. You cannot re-distribute videos on this channel in other channels or platforms. #Kafka #SpringBoot #TechPrimers
Learn how to integrate Spring Boot with Docker image of Kafka Streaming Platform. Spring Boot provides ready made templates to implement Kafka Producer and Kafka Consumer applications that write and read data to and from Kafka topics. In this example we run the Kafka on Docker Container and try to invoke the producer with Spring REST API and write data to kafka topic and once the data or message arrived on kafka topic Kafka consumer will read the message by deserializing it from kafka topic and prints the message on console. You can see also how install / run kafka in docker. Nowadays Spring Kafka combination getting more popular, since the many companies started building Event driven systems or microservices. Kafka very well fit into event sourcing architectures. And also we can use Kafka as Event bus so that any producer application can publish messages to the kafka topics and any kafka consumer application can subscribe to particular topic and can consume messages. Spring provides kafka listener template to consume the messages from kafka topics in easy way. ✅ Github link: 🤍 ▬▬▬▬▬▬ ⏰T I M E S T A M P S ⏰ ▬▬▬▬▬▬ 0:00 - Introduction 0:11 - Intro to Spring Boot & Kafka 1:59 - Building Project with Spring Initializer 3:50 - Creating Kafka Producer 8:45 - Creating Kafka Consumer 12:05 - Creating docker compose file 15:20 - Testing with Postman client app. ▬▬▬▬▬▬▬▬ ✅ Spring Boot & Docker related Videos ✅ ▬▬▬▬▬▬▬▬▬▬ ► Spring Boot & Cassandra Integration with Docker Compose: 🤍 ► Spring Boot & PostgreSQL Integration with Docker Compose: 🤍 ► Spring Boot & MySQL Integration & Deployment on K8s: 🤍 ► Spring Boot with Protocol Buffers: 🤍 ► Spring Boot & Kafka Producer and Consumer Example: 🤍 #springboot #kafka #docker #techtter ▬▬▬▬▬▬▬▬ ✅ Subscribe To Channel on Social Media ✅▬▬▬▬▬▬▬▬ YOUTUBE: ► 🤍 FACEBOOK: ► 🤍 TWITTER: ► 🤍 INSTAGRAM: ► 🤍 DEV: ► 🤍 WEB: ► 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🔥 Disclaimer/Policy: The content of the videos, ideas given in videos all are self opinionated. The code samples shown in the video are collected from opensource projects shared on github and from other sources. The trademarks and logos shown on thumbnails and in videos are registered for respective companies. This video is not certified or accredited by them.
Spring Boot com Feign, Kafka, Banco de Dados e Docker #Parte 1 * Parte 1 - Direcionado a implementação com Feign para consumir API, seja interna ou externa; * Parte 2 - Direcionado a implementação para envio de mensagem para fila Kafka; * Parte 2 - Direcionado a implementação para consumir a mensagem Kafka e persistir no banco de dados; Pré-requisitos: 1 - Criar projeto Spring Boot - Spring IO: 🤍 - Dependencias: Web, OpenFeign e Lombok Se este vídeo te ajudou de alguma maneira? Compartilhe e deixe o seu comentário Links: Vídeo: 🤍 Canal: 🤍 Git: 🤍 Nosso Contato: Email: maddytec🤍gmail.com
You will learn how to create Kafka Producer and Consumer with Spring Boot in Java. GitHub Link: 🤍 You can start the Zookeeper and Kafka servers by using the below commands. Start Zookeeper: $ zookeeper-server-start /usr/local/etc/kafka/zookeeper.properties Start Kafka server: $ kafka-server-start /usr/local/etc/kafka/server.properties My Top Playlists: Spring Boot with Angular : 🤍 Spring Boot with Docker & Docker Compose : 🤍 Spring Boot with Kubernetes : 🤍 Spring Boot with AWS : 🤍 Spring Boot with Azure : 🤍 Spring Data with Redis : 🤍 Spring Boot with Apache Kafka : 🤍 Spring Boot with Resilience4J : 🤍
GitHub code: 🤍 In this series, we will be talking about Microservices patterns associated with Event-Driven Architecture. We will also talk a little bit about Domain Driven Design (but not our focus). In this series, we will create a business case related to Loan Mortgages. We will have some microservices to accomplish this use case. We will cover topics like: - Publish-Subscribe Pattern (vs Point-to-point) - Domain-Driven Design - CQRS, Event-Sourcing, Transaction Outbox Pattern, Command vs Event, DLQ - Test Coontainer - Spring Cloud Contract, etc.
Stateful retries refer to a mechanism for retrying failed operations in a way that takes into account the state of the previous attempts. In other words, stateful retries keep track of previous attempts and use this information to make more informed decisions about how to retry the operation.
Understanding the basic concepts of Asynchronous Communications using Spring Cloud Stream and Apache Kafka, GIT: 🤍 Read the readme.pdf file in order to install and configure Apache Zookeeper and Apache Kafka. About the Speaker: Tadeu Barbosa (tadeu.barbosa🤍cbds.com.br) get a degree in Computer Science from PUC-SP. He has been working with Java since 2003, most of which as an official Sun Microsystems and Oracle Instructor, currently a Java Software Engineer at CBDS. It has the certifications: SCJP, SCWCD, OCMJEA, Oracle WLS 12c, and Scrum Master.
In this video we will see how Spring Boot makes it easy to integrate Apache Kafka to our app. We will create a producer to publish messages to a Kafka topic and a consumer to consume messages from it. To test it, we will create a REST API to post messages to Kafka. You can find the source code for the demo at the following github url: 🤍
In this episode of Livestreams, Viktor Gamov (Developer Advocate, Confluent) shows how to use Avro and Protobuf serialization in Apache Kafka® and Kafka Streams projects with Spring Boot and Confluent Cloud. Use the promo code SPRINGSTREAMS200 to receive an additional $200 of free Confluent Cloud usage. VIDEO LINKS Confluent Cloud: 🤍 Code: 🤍 Kafka Summit: 🤍 TIMESTAMPS 0:00 - The stream starts! 5:16 - Register for Kafka Summit 10:50 - RSVP to Kafkathon 2020 at 🤍 11:23 - What are we going to be doing today? 13:20 - Creating Spring Boot for a Kafka project 17:25 - Let's code a stream processor 21:14 - Serialization/deserialization 101 25:39 - Writing Avro schema 28:48 - Generate a Java object from Avro schema 34:21 - Writing Protobuf schema 37:04 - Generate a Java object from Protobuf 44:35 - Subscribe to the Confluent YouTube channel 42:25 - Writing a producer 1:00:30 - Running the app and fixing errors 1:04:45 - Configuring specific Avro serializers 1:27:00 - It's a wrap! CONNECT Subscribe: 🤍 Site: 🤍 GitHub: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Instagram: 🤍 ABOUT CONFLUENT Confluent, founded by the creators of Apache Kafka®, enables organizations to harness business value of live data. The Confluent Platform manages the barrage of stream data and makes it available throughout an organization. It provides various industries, from retail, logistics and manufacturing, to financial services and online social networking, a scalable, unified, real-time data pipeline that enables applications ranging from large volume data integration to big data analysis with Hadoop to real-time stream processing. To learn more, please visit 🤍 #confluent #apachekafka #kafka
Разворачиваем кафка на Docker, слушаем, публикуем и обрабтываем сообщения с помощью Spring. Опросник по аннотациям Spring JPA: 🤍 🤍 В качестве обертки - делаем проект для распределения маршрутов самолтеов. GitHub: 🤍 Регистратура: 🤍 Offset Explorer платная, но на триале можно использовать: 🤍
This video talks about creating a Kafka Consumer to read String & JSON schema messages from Kafka topic using Spring Boot. Source Code: 🤍 Like | Subscribe | Share
In this tutorial, we will be creating a simple Kafka Consumer in Java using Spring Boot and Spring Kafka GitHub CodeLink: 🤍 Other Video: - How to Install Apache Kafka on Windows: 🤍 Simple Kafka Producer example: 🤍 Spring Boot Tutorials: 🤍 Quarkus Tutorials: 🤍 Follow us on : Website: 🤍 Facebook: 🤍 Twitter: 🤍 Instagram: 🤍 GitHub: 🤍 My Laptop : ASUS ROG Zephyrus G14, 14" - 🤍 ASUS ROG Zephyrus G14, 14" (US) - 🤍 Audio Gear : Maono AU-A04 Condenser Microphone : 🤍 Maono AU-A04 Condenser Microphone (US) :🤍 Secondary Audio : Maono AU-100 Condenser Clip On Lavalier Microphone : 🤍 Recommended Books: Mastering Spring Boot 2.0 (Kindle): 🤍 Mastering Spring Boot 2.0 (US) : 🤍 Building Microservices(Kindle) : 🤍 Building Microservices(US) : 🤍 Spring Boot in Action : 🤍 Spring Boot in Action (US) : 🤍 Spring Microservices in Action : 🤍 Spring Microservices in Action(US): 🤍 Music: - Otis McMusic (Sting): 🤍 Hear the Noise (Sting): 🤍 Song of Mirrors: 🤍 “Sound effects obtained from 🤍“ #Kafka #SpringKafka #Consumer #DailyCodeBuffer #ApacheKafka #Apache #Spring #SpringBoot
Udemy course: Master event-driven microservices architecture with patterns using Spring boot, Spring cloud, Kafka and Elasticsearch 🤍 Hi there! My name is Ali Gelenler. I'm here to help you learn event-driven microservices architecture by applying best practices for real-life challenges. In this course, you will focus on the development of microservices. With the help of microservices you can independently develop and deploy your application components . You can also easily scale services according to each service's own resource needs, for example you can scale better and create more instances of a service that requires more requests. When moving from a monolith application to microservices architecture, some challenges will arise as a result of having a distributed application and system. In this course you will learn how to deal with these challenges using event-driven architecture (EDA) architecture with Apache Kafka. With an event-driven architecture; - You will truly decouple the services and create resilient services because a service has no direct communication with other services - You will use asynchronous/non-blocking communication between services - You will use an event/state store (Kafka), and remove the state from the services for better scalability Tanima: "This is one of the best course i ever had in udemy, instructor is super responsive and always deals with complex problem during the course, Thank you so much Professor i will always be grateful to you for this course, and will keep eye on your next course release." The microservices patterns that you will be implementing are: - Externalized configuration with Spring Cloud Config - CQRS with Kafka and Elastic search - Api versioning for versioning of Rest APIs - Service Registration and Discovery with Spring Cloud and Netflix Eureka - Api Gateway with Spring Cloud Gateway - Circuit breaker with Spring Cloud Gateway and Resilience4j - Rate limiting with Spring Cloud Gateway and Redis to use Redis as the Rate limiter - Distributed tracing with SLF4J MDC, Spring Cloud Sleuth and Zipkin - Log aggregation with ELK stack (Elasticsearch, Logstash and Kibana) - Client side load balancing with Spring Cloud Load Balancer - Database per Service - Messaging between microservices using Kafka You will also implement Spring Security Oauth 2.0 and OpenID connect protocols for Authentication and Authorization using Keycloak and JWT. The use of Oauth for authorization of services and OpenID connect for authentication is widely used in microservices archictecture with Spring boot security. While introducing event-driven microservices, you will understand the basics of Apache Kafka by covering Kafka topics, Kafka partitions, Kafka consumer and producer APIs, Kafka admin client and Avro messaging. There is also a reactive development section in this course which demonstrates querying elasticsearch reactively with Reactive Spring, WebFlux, WebClient and Reactive Thymeleaf. In this section you will learn how to use Spring Webflux and Spring reactive components to create an asynchronous flow between microservices. You will be following a hands-on approach and be developing a project from scratch in which you will have multiple microservices surrounded with multiple modules to accomplish the specific tasks. So you will need to make your hands dirty in this course where I will be guiding you from start to finish. You will also find multiple choice quizes in each section to check your progress throughout the course. At the end of the course you will not only understand the real life challenges of a distributed application with multiple services and components, but also you will be able to apply solutions to this challenges. Ido Charar: "This course by Ali Gelenler is outstanding. It is not just about Spring Cloud with kafka and elastic. This course gives you much more knowledge around technologies related to Spring Cloud in particular and Cloud Computing in general. Among them are technologies like reactive programming, streaming, linux OS, security, Design Patterns and much much more. All the information is given in succinct but ingestable form, which allows you broaden your skills in shortest possible time. Very appreciate the investment in material, lecturer involvement, constant assistance and help to the students. Will recommend to take this course everyone who want to level up her/his skills." For more detailed information on the progress of this course, you can check the introductory video and free lessons, and if you decide to enroll in this course, you are always welcome to ask and discuss the concepts and implementation details on Q/A and messages sections. I will guide you from start to finish to help you successfully complete the course and gain as much knowledge and experience as possible from this course.
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