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Microservices written in Go was a key component of a new system that would enable The Economist to deliver scalable, high performing services and quickly iterate new products. Go's baked in concurrency and API support along with its design as a static, compiled language enabled a distributed eventing system. Overall, The Economist team's experience with Go has been positive experience.
The authors discuss how to migrate apps to the cloud using funnels and buckets, and then scale them and test for resilience.
In this article we described how Analytics Zoo can help real-world users to build end-to-end deep learning pipelines for big data, including unified pipelines for distributed TensorFlow and Keras on Apache Spark, easy-to-use abstractions such as transfer learning and Spark ML pipeline support, built-in deep learning models and reference use cases, etc.
Ryan Johnson discusses common issues and solutions to them for teams moving from a waterfall approach to an agile one.
Olaf Gradin shares Fiserv’s experience working with Pivotal Application Service, what worked and what didn’t.
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