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Integrating Spring Boot with Apache Kafka ft. Viktor Gamov
Manage episode 424666824 series 2510642
Viktor Gamov (Developer Advocate, Confluent) joins Tim Berglund on this episode to talk all about Spring and Apache Kafka®. Viktor’s main focus lately has been helping developers build their apps with stream processing, and helping them do this effectively with different languages. Viktor recently hosted an online Spring Boot workshop that turned out to be a lot of fun. This means it was time to get him back on the show to talk about this all-important framework and how it integrates with Kafka and Kafka Streams.
Spring Boot enables you to do more with less. Its features offer numerous benefits, making it easy to create standalone, production-grade Spring-based applications that you can just run. The pattern also runs inside the Spring framework for a long time. The Spring Integration Framework implements many enterprise integration patterns and also has a pre-built Kafka connector.
Spring Boot was highly inspired by a 12-factor app manifesto that allows you to write portable apps and extract the configuration, providing different profiles for you to customize your deployment.
This is a critical part of the Kafka client infrastructure. Even though it's a Java client, Confluent offers a native Spring for Apache Kafka integration for the configuration as a springboard inside Confluent Cloud. If you try to connect your application, you can copy a snippet and place it directly to your Spring application, which works with Confluent Cloud. Now, he’s working on bringing Spring Cloud Stream like YAML-based configuration into Confluent Cloud too so folks can easily copy and paste to work out of the box.
To close, Viktor shares about an interesting new project that the Confluent Developer Relations team is working on. Stick around to hear all about it and learn how Spring and Kafka work together.
EPISODE LINKS
- Spring example in streaming-ops
- Avro, Protobuf, Spring Boot, Kafka Streams and Confluent Cloud | Livestreams
- Event-Driven Microservices with Spring Boot and Confluent Cloud | Livestreams
- Choosing Christmas Movies with Kubernetes, Spring Boot, and Apache Kafka | Livestreams 015
- Spring Cloud Stream and Confluent Cloud | Livestreams 018
- Joining Forces with Spring Boot, Apache Kafka, and Kotlin ft. Josh Long
- Mastering DevOps with Apache Kafka, Kubernetes, and Confluent Cloud ft. Rick Spurgeon and Allison Walther
- Follow Viktor Gamov on Twitter
- Join the Confluent Community Slack
- Learn more with Kafka tutorials, resources, and guides at Confluent Developer
- Live demo: Kafka streaming in 10 minutes on Confluent Cloud
- Use 60PDCAST to get an additional $60 of free Confluent Cloud usage (details)
265 פרקים
Manage episode 424666824 series 2510642
Viktor Gamov (Developer Advocate, Confluent) joins Tim Berglund on this episode to talk all about Spring and Apache Kafka®. Viktor’s main focus lately has been helping developers build their apps with stream processing, and helping them do this effectively with different languages. Viktor recently hosted an online Spring Boot workshop that turned out to be a lot of fun. This means it was time to get him back on the show to talk about this all-important framework and how it integrates with Kafka and Kafka Streams.
Spring Boot enables you to do more with less. Its features offer numerous benefits, making it easy to create standalone, production-grade Spring-based applications that you can just run. The pattern also runs inside the Spring framework for a long time. The Spring Integration Framework implements many enterprise integration patterns and also has a pre-built Kafka connector.
Spring Boot was highly inspired by a 12-factor app manifesto that allows you to write portable apps and extract the configuration, providing different profiles for you to customize your deployment.
This is a critical part of the Kafka client infrastructure. Even though it's a Java client, Confluent offers a native Spring for Apache Kafka integration for the configuration as a springboard inside Confluent Cloud. If you try to connect your application, you can copy a snippet and place it directly to your Spring application, which works with Confluent Cloud. Now, he’s working on bringing Spring Cloud Stream like YAML-based configuration into Confluent Cloud too so folks can easily copy and paste to work out of the box.
To close, Viktor shares about an interesting new project that the Confluent Developer Relations team is working on. Stick around to hear all about it and learn how Spring and Kafka work together.
EPISODE LINKS
- Spring example in streaming-ops
- Avro, Protobuf, Spring Boot, Kafka Streams and Confluent Cloud | Livestreams
- Event-Driven Microservices with Spring Boot and Confluent Cloud | Livestreams
- Choosing Christmas Movies with Kubernetes, Spring Boot, and Apache Kafka | Livestreams 015
- Spring Cloud Stream and Confluent Cloud | Livestreams 018
- Joining Forces with Spring Boot, Apache Kafka, and Kotlin ft. Josh Long
- Mastering DevOps with Apache Kafka, Kubernetes, and Confluent Cloud ft. Rick Spurgeon and Allison Walther
- Follow Viktor Gamov on Twitter
- Join the Confluent Community Slack
- Learn more with Kafka tutorials, resources, and guides at Confluent Developer
- Live demo: Kafka streaming in 10 minutes on Confluent Cloud
- Use 60PDCAST to get an additional $60 of free Confluent Cloud usage (details)
265 פרקים
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1 How to use Python with Apache Kafka 31:57

1 Next-Gen Data Modeling, Integrity, and Governance with YODA 55:55

1 Migrate Your Kafka Cluster with Minimal Downtime 1:01:30

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1 What is the Future of Streaming Data? 41:29

1 What can Apache Kafka Developers learn from Online Gaming? 55:32


1 How to use OpenTelemetry to Trace and Monitor Apache Kafka Systems 50:01

1 What is Data Democratization and Why is it Important? 47:27

1 Git for Data: Managing Data like Code with lakeFS 30:42

1 Using Kafka-Leader-Election to Improve Scalability and Performance 51:06

1 Real-Time Machine Learning and Smarter AI with Data Streaming 38:56

1 The Present and Future of Stream Processing 31:19

1 Top 6 Worst Apache Kafka JIRA Bugs 1:10:58

1 Learn How Stream-Processing Works The Simplest Way Possible 31:29

1 Building and Designing Events and Event Streams with Apache Kafka 53:06

1 Rethinking Apache Kafka Security and Account Management 41:23

1 Real-time Threat Detection Using Machine Learning and Apache Kafka 29:18

1 Improving Apache Kafka Scalability and Elasticity with Tiered Storage 29:32

1 Decoupling with Event-Driven Architecture 38:38

1 If Streaming Is the Answer, Why Are We Still Doing Batch? 43:58

1 Security for Real-Time Data Stream Processing with Confluent Cloud 48:33

1 Running Apache Kafka in Production 58:44

1 Build a Real Time AI Data Platform with Apache Kafka 37:18

1 Optimizing Apache JVMs for Apache Kafka 1:11:42


1 Application Data Streaming with Apache Kafka and Swim 39:10

1 International Podcast Day - Apache Kafka Edition | Streaming Audio Special 1:02:22


1 Real-Time Stream Processing, Monitoring, and Analytics With Apache Kafka 34:07

1 Reddit Sentiment Analysis with Apache Kafka-Based Microservices 35:23

1 Capacity Planning Your Apache Kafka Cluster 1:01:54

1 Streaming Real-Time Sporting Analytics for World Table Tennis 34:29

1 Real-Time Event Distribution with Data Mesh 48:59

1 Apache Kafka Security Best Practices 39:10

1 What Could Go Wrong with a Kafka JDBC Connector? 41:10

1 Apache Kafka Networking with Confluent Cloud 37:22

1 Event-Driven Systems and Agile Operations 53:22

1 Streaming Analytics and Real-Time Signal Processing with Apache Kafka 1:06:33

1 Blockchain Data Integration with Apache Kafka 50:59

1 Automating Multi-Cloud Apache Kafka Cluster Rollouts 48:29

1 Common Apache Kafka Mistakes to Avoid 1:09:43
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