For the last several years, internal infrastructure at LinkedIn has been built around a self-service model, enabling developers to onboard themselves with minimal support. We have various user experiences that let application teams provision their own resources and infrastructure, generally by filling out forms or using command-line tools. For example,...
Data Streams Articles
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- Topics:
- Stream Processing,
- Data Streams,
- Open Source
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Co-Authors: Yuhong Cheng, Shangjin Zhang, Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. This, in turn, helps engineers to develop and deploy data processing applications quickly and easily, powering various business requirements, and enhancing member...
- Topics:
- Apache Samza,
- Spark,
- Stream Processing,
- apache,
- Data Streams
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Less than a year ago, we announced the first open source release of Apache Incubator Samza, a framework for processing big data streams. Today we are releasing Samza 0.7.0, a big milestone that reflects Samza's growing maturity. This is a good opportunity to look back at how far we've come in the last year. Samza is no longer a research project, but is now...
- Topics:
- Stream Processing,
- Data,
- Data Streams,
- Performance,
- Agility,
- Kafka,
- Samza
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We're excited to announce that we've open sourced Samza, LinkedIn's stream processing framework. It is now an incubator project with...
- Topics:
- Data Streams,
- Kafka
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Kafka is a distributed publish-subscribe messaging system. It was originally developed at LinkedIn and became an Apache project in...
- Topics:
- Big Data,
- Distributed Systems,
- Kafka,
- Data Streams,
- Open Source
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Come by LinkedIn Headquarters on Thursday, September 15 for a public tech talk "Big Data in Real Time: Processing Data Streams at...