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http://traffic.libsyn.com/sedaily/cloudbuilding_edited.mp3Podcast: Play in new window | Download Google Compute Engine is the public cloud built by Google. It provides infrastructure- and platform-as-a-service capabilities that rival Amazon Web Services. Today’s guest Joe Beda was there from the beginning of GCE, and he was also one of the early engineers on the Kubernetes project. Google’s internal systems have made it easy for employees to spin up compute resources, but it was not
http://traffic.libsyn.com/sedaily/CloudClients_edited.mp3Podcast: Play in new window | Download Google builds cloud services for developers, such as PubSub, Cloud Storage, BigQuery, and Cloud DataStore. On Software Engineering Daily, we’ve done lots of shows about how these types of services are built. In this episode, we are zooming in on the interaction between the developer using a cloud service and the design and engineering of the client APIs. To build a useful cloud
http://traffic.libsyn.com/sedaily/Scalable_Architecture.mp3Podcast: Play in new window | Download Lee Atchison spent seven years at Amazon working in retail, software distribution, and Amazon Web Services. He then moved to New Relic, where he has spent four years scaling the company’s internal architecture. From his decade of experience at fast growing web technology companies, Lee has written the book Architecting for Scale, from O’Reilly. As an application scales, it becomes significantly more
http://traffic.libsyn.com/sedaily/Cloud_Providers_Edited.mp3Podcast: Play in new window | Download In 1999, it took $50,000 to buy a server. Once you bought that server, you had to know how to operate and maintain it. Today, cloud service providers have changed how we build software. Servers, load balancers, networking, storage–these hardware concerns have been turned into software. Don Pezet joins the show today to discuss the fundamentals of a cloud service provider. These are
http://traffic.libsyn.com/sedaily/Serverless_Code_Edited.mp3Podcast: Play in new window | Download The unit of computation has evolved from on premise servers to virtual machines in the cloud to containers running in those virtual machines. Serverless computation is another stage in the evolution of computational unit management. With a serverless architecture, a function call to the cloud spins up a transient container, calls the function on that container, and then spins down the container. Ryan
http://traffic.libsyn.com/sedaily/Serverless_Edited.mp3Podcast: Play in new window | Download Virtual machines were the unit of cloud computation for many years. Amazon Web Services pioneered the democratized model of allowing anyone to deploy a service to the cloud, running on a virtual machine on Amazon’s servers. After virtual machines, containers have become the unit of scale in the cloud. We break up our virtualized servers into even smaller units of computation called containers.
From Eric Tschetter’s answer via Quora: The difference you are asking about though is ParAccel vs. Druid. ParAccel is the software that Amazon is licensing for RedShift. Aside from just potential differences in performance, there are some functional differences (these are all based on a cursory understanding of what ParAccel does, I’ve read what I could find on it, but a lot of my understanding is extracted from interpretations of marketing