This document discusses exactly once semantics in Apache Kafka 0.11. It provides an overview of how Kafka achieved exactly once delivery between producers and consumers. Key points include:
- Kafka 0.11 introduced exactly once semantics with changes to support transactions and deduplication.
- Producers can write in a transactional fashion and receive acknowledgments of committed writes from brokers.
- Brokers store commit markers to track the progress of transactions and ensure no data loss during failures.
- Consumers can read from brokers in a transactional mode and receive data only from committed transactions, guaranteeing no duplication of records.
- This allows reliable message delivery semantics between producers and consumers with Kafka acting as
This document discusses messaging queues and platforms. It begins with an introduction to messaging queues and their core components. It then provides a table comparing 8 popular open source messaging platforms: Apache Kafka, ActiveMQ, RabbitMQ, NATS, NSQ, Redis, ZeroMQ, and Nanomsg. The document discusses using Apache Kafka for streaming and integration with Google Pub/Sub, Dataflow, and BigQuery. It also covers benchmark testing of these platforms, comparing throughput and latency. Finally, it emphasizes that messaging queues can help applications by allowing producers and consumers to communicate asynchronously.
This document discusses exactly once semantics in Apache Kafka 0.11. It provides an overview of how Kafka achieved exactly once delivery between producers and consumers. Key points include:
- Kafka 0.11 introduced exactly once semantics with changes to support transactions and deduplication.
- Producers can write in a transactional fashion and receive acknowledgments of committed writes from brokers.
- Brokers store commit markers to track the progress of transactions and ensure no data loss during failures.
- Consumers can read from brokers in a transactional mode and receive data only from committed transactions, guaranteeing no duplication of records.
- This allows reliable message delivery semantics between producers and consumers with Kafka acting as
This document discusses messaging queues and platforms. It begins with an introduction to messaging queues and their core components. It then provides a table comparing 8 popular open source messaging platforms: Apache Kafka, ActiveMQ, RabbitMQ, NATS, NSQ, Redis, ZeroMQ, and Nanomsg. The document discusses using Apache Kafka for streaming and integration with Google Pub/Sub, Dataflow, and BigQuery. It also covers benchmark testing of these platforms, comparing throughput and latency. Finally, it emphasizes that messaging queues can help applications by allowing producers and consumers to communicate asynchronously.
This document discusses encouraging writing technology blogs and the benefits of doing so. It provides details about the author's own blog and experience running it for over 5 years. The author explains that starting a blog helped them thoroughly understand new technologies, speed up learning, and share knowledge with others. Tips are provided for keeping a blog going, such as writing on any topic of interest and not putting pressure on post frequency. Analytics from the author's blog are also shown and it is concluded that blogging can be a fun output experience.
Red Hat Tech Night#2のLT。virtual-kubeletで OSSとマネージドサービスの いいとこ取りを考える。
内容はいつかのDocker Meetupと一部かぶります。
詳しくはこちらを参照。
https://blog.mosuke.tech/entry/2019/02/03/virtual-kubelet/