The authors take a deep dive into the history of NoSQL at Amazon.com, from the world of relational databases to the Dynamo days to the world of managed services like DynamoDB.
Aish Fenton discusses Netflix' machine learning algorithms, including distributed Neural Networks on AWS GPUs, providing insight into offline experimentation and online AB testing.
Derek Collison discusses some of the technologies and approaches for building a self-healing infrastructure: Intelligent layer 7 SDN with semantic awareness, self healing techniques, etc.
Chris Swan takes a look at Docker: what it is, why it was chosen, how it became an established platform, and what it takes to package applications and application infrastructure for use with Docker.
Adrian Cockcroft discusses strategies, patterns and pathways to perform a gradual migration towards modern enterprise applications based on cloud, microservices and denormalized NoSQL databases.
Shawn Gandhi overviews real-time processing use cases, and how developers are using AWS Kinesis to shift from a traditional batch-oriented approach to a continual real-time data processing model.
Randy Shoup describes KIXEYE's analytics infrastructure from Kafka queues through Hadoop 2 to Hive and Redshift, built for flexibility, experimentation, iteration, testability, and reliability.
Jacob Mather shows how to transition a development stack from a local machine to a virtual solution on a server that can be extended to a private cloud.
Ryan Vanderwerf explains how to create and deploy a Grails application on AWS VPC using various services such as RDS, S3, autoscaling, S3FS, EBS, etc.
Sebastian Stadil advises on selecting the right cloud from EC2, GCE, or OpenStack based on one's needs, outlining the deployment and administrative challenges to be faced with each option.
Brenden Matthews describes the infrastructure built at Airbnb using Mesos in order to support Hadoop and Storm.
Nic Williams discusses deploying Cloud Foundry on AWS or OpenStack using Bosh, a tool chain for release engineering, deployment and lifecycle management of large scale distributed services.