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Kafka Applications with Tim Berglund (Repeat)

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Manage episode 280200073 series 1433319
Sisällön tarjoaa Open Source Archives - Software Engineering Daily. Open Source Archives - Software Engineering Daily tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

Originally published September 17, 2019

Ever since Apache Kafka was open sourced from LinkedIn, it has been used to solve a wide variety of problems in distributed systems and data engineering.

Kafka is a distributed messaging queue that is used by developers to publish messages and subscribe to topics with a certain message type. Kafka allows information to flow throughout a company such that multiple systems can consume the messages from a single sender.

In previous shows, we have covered design patterns within Kafka, Kafka streams, event sourcing with Kafka, and many other subjects relating to the technology. Kafka is broadly useful, and new strategies for using Kafka continue to emerge as the open source project develops new functionality and becomes a platform for data applications.

In today’s episode, Tim Berglund returns to Software Engineering Daily for a discussion of how applications are built today using Kafka–including systems that are undergoing a refactoring, data engineering applications, and systems with a large number of communicating services.

If you are interested in learning more about how companies are using Kafka, the Kafka Summit in San Francisco is September 30th – October 1st. Companies like LinkedIn, Uber, and Netflix will be talking about how they use Kafka. Full disclosure: Confluent (the company where Tim works) is a sponsor of Software Engineering Daily.

Sponsorship inquiries: [email protected]

The post Kafka Applications with Tim Berglund (Repeat) appeared first on Software Engineering Daily.

  continue reading

143 jaksoa

Artwork
iconJaa
 
Manage episode 280200073 series 1433319
Sisällön tarjoaa Open Source Archives - Software Engineering Daily. Open Source Archives - Software Engineering Daily tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

Originally published September 17, 2019

Ever since Apache Kafka was open sourced from LinkedIn, it has been used to solve a wide variety of problems in distributed systems and data engineering.

Kafka is a distributed messaging queue that is used by developers to publish messages and subscribe to topics with a certain message type. Kafka allows information to flow throughout a company such that multiple systems can consume the messages from a single sender.

In previous shows, we have covered design patterns within Kafka, Kafka streams, event sourcing with Kafka, and many other subjects relating to the technology. Kafka is broadly useful, and new strategies for using Kafka continue to emerge as the open source project develops new functionality and becomes a platform for data applications.

In today’s episode, Tim Berglund returns to Software Engineering Daily for a discussion of how applications are built today using Kafka–including systems that are undergoing a refactoring, data engineering applications, and systems with a large number of communicating services.

If you are interested in learning more about how companies are using Kafka, the Kafka Summit in San Francisco is September 30th – October 1st. Companies like LinkedIn, Uber, and Netflix will be talking about how they use Kafka. Full disclosure: Confluent (the company where Tim works) is a sponsor of Software Engineering Daily.

Sponsorship inquiries: [email protected]

The post Kafka Applications with Tim Berglund (Repeat) appeared first on Software Engineering Daily.

  continue reading

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