Category Cloud Engineering

Reinforcement Learning with Michal Kempa

http://traffic.libsyn.com/sedaily/ReinforcementLearning.mp3Podcast: Play in new window | Download Reinforcement learning is a type of machine learning where a program learns how to take actions in an environment based on how that program has been rewarded for actions it took in the past. When program takes an action, and it receives a reward for that action, it is likely to take that action again in the future because it was positively reinforced.

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Apparel Machine Learning with Colan Connon and Thomas Bell

http://traffic.libsyn.com/sedaily/ApparelMachineLearning.mp3Podcast: Play in new window | Download In its most basic definition, machine learning is a tool that makes takes a data set, finds a correlation in that data set, and uses that correlation to improve a system. Any complex system with well-defined behavior and clean data can be improved with machine learning. Several precipitating forces have caused machine learning to become widely used: more data, cheaper storage, and better

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Backups with Kenny To

http://traffic.libsyn.com/sedaily/Rubrik.mp3Podcast: Play in new window | Download Every software company backs up critical data sources. Backing up databases is a common procedure, whether a company is in the cloud or on-prem. Backing up virtual machine instances is less common. Rubrik is a company that is known for building backup infrastructure for enterprises. Their main product is an appliance that sits on prem at an enterprise and stores snapshots of virtual

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Deployment with Avi Cavale

http://traffic.libsyn.com/sedaily/Shippable.mp3Podcast: Play in new window | Download Software deployment evolves over time. In the 90s, a “deployment” might have meant issuing a new edition of your software via CD-ROM. Today, a deployment is often a multi-stage process. A new software build will undergo automated unit tests and integration tests, before being deployed to users.  The deployment might only go out to a small percentage of total users initially, with that

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Kafka in the Cloud with Neha Narkhede

http://traffic.libsyn.com/sedaily/KafkaCloud.mp3Podcast: Play in new window | Download Apache Kafka is an open-source distributed streaming platform. Kafka was originally developed at LinkedIn, and the creators of the project eventually left LinkedIn and started Confluent, a company that is building a streaming platform based on Kafka. Kafka is very popular, but is not easy to deploy and operationalize. That is why Confluent has built a Kafka-as-a-service product, so that managing Kafka is

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Software Architecture with Simon Brown

http://traffic.libsyn.com/sedaily/softwarearchitecture_edited.mp3Podcast: Play in new window | Download Software architecture address the challenge of communicating and navigating large, complex systems to stakeholders, both technical and non-technical.  Over the years software architecture has gone in and out of fashion.  Today we discuss why software architecture is important, what it means to have software architecture, and how to properly structure teams and incorporate architecture. Today’s show is guest hosted by David Curry. David

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IoT Edge with Olivier Bloch

http://traffic.libsyn.com/sedaily/azureiot_edited.mp3Podcast: Play in new window | Download A self-driving car needs to be able to quickly respond to changes in driving conditions. A factory needs to be able to quickly respond to changes in workplace safety. For these kinds of applications, we need processing power closer to the user of the application. If we put all of our application logic in the cloud, we will have to make a network

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Google Early Days with John Looney

http://traffic.libsyn.com/sedaily/googleearlydays_edited.mp3Podcast: Play in new window | Download John Looney spent more than 10 years at Google. He started with infrastructure, and was part of the team that migrated Google File System to Colossus, the successor to GFS. Imagine migrating every piece of data on Google from one distributed file system to another. In this episode, John sheds light on the engineering culture that has made Google so successful. He has

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Container Engines with David Aronchick and Chen Goldberg

http://traffic.libsyn.com/sedaily/containerengines.mp3Podcast: Play in new window | Download Kubernetes makes it easier for engineering teams to manage their distributed systems architecture. But it’s still not simple to deploy and operate a Kubernetes cluster. Google Container Engine (GKE) is a managed control plane for Kubernetes. Just as developers can use Google App Engine to easily deploy monolithic apps against a platform as a service, we can use Google Container Engine to deploy

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DNS with Phil Stanhope

http://traffic.libsyn.com/sedaily/dns_edited.mp3Podcast: Play in new window | Download DNS stands for domain name system. This is the naming system that maps the entire internet. It associates information with domain names. More specifically, DNS specifies mappings between numerical IP addresses and domain names. Most engineers know these basic facts about DNS, but they may not know how much engineering a complex company like Etsy or Zappos puts into their DNS configuration. Dynamic

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GitLab with Pablo Carranza

http://traffic.libsyn.com/sedaily/gitlab_edited.mp3Podcast: Play in new window | Download On January 31st 2017, GitLab experienced a major outage of their online repository hosting service. The primary database server experienced data loss due to a combination of malicious spam attacks and engineering mistakes that occurred while trying to respond to those spam attacks. GitLab responded to the event transparently. The company put up a postmortem describing the event in detail. In subsequent posts,

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Universal Healthcare with Thomas Bukowski

http://traffic.libsyn.com/sedaily/UniversalHealthcare.mp3Podcast: Play in new window | Download Everyone in the world should have some basic level of guaranteed healthcare. This is not controversial. But what should that basic level of healthcare be? Should it extend into the later years of your life, when the majority of your health costs are incurred? And how much has modern technology driven down the cost of what it should cost to treat a patient?

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Healthcare Engineering with Isaac Councill

http://traffic.libsyn.com/sedaily/OscarEngineering.mp3Podcast: Play in new window | Download Healthcare is a complex business. Oscar is a company that wanted to build a new insurance provider–but realized that healthcare is so interconnected that in order to build a new insurance provider, realized it actually needed to build an entire healthcare business too, complete with patient management and facilities. Since Oscar is a modern technology company, the focus on customer service, engineering, and

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Microservices Transition with Cassandra Shum

http://traffic.libsyn.com/sedaily/CassandraShum.mp3Podcast: Play in new window | Download Many companies are transitioning from a monolith to microservices architecture. Tools for cloud computing, containerization, and continuous delivery are making this easier. But there are still technological and organizational challenges that a company will encounter while making this transition. Cassandra Shum is an engineer with ThoughtWorks. She has worked with major financial institutions and other large companies to architect their migrations from monolith

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Firebase with Doug Stevenson

http://traffic.libsyn.com/sedaily/Firebase.mp3Podcast: Play in new window | Download Firebase is a backend-as-a-service. The key efficiency of a backend-as-a-service is that it enables developers to go from having a 3-tier architecture (client, server, database) to a 2-tier architecture (client, backend-as-a-service). The team who started Firebase built it as a pivot. They had started a social network, and then they realized there wasn’t a good backend for chat tools. And so they started

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Spring Boot with Josh Long

http://traffic.libsyn.com/sedaily/SpringBoot.mp3Podcast: Play in new window | Download Spring Framework is an application framework for Java and JVM languages. Spring was originally built around dependency injection, but grew to become an entire ecosystem of tools and plugins for Java developers. Spring was originally released 15 years ago, and since then a lot has changed around application development. For example, many engineers deploy applications to the cloud in microservices architectures. The expectations

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Microservices Practitioners with Austin Gunter and Richard Li

http://traffic.libsyn.com/sedaily/microservicesmacro_edited.mp3Podcast: Play in new window | Download The word “microservices” started getting used after a series of events–companies were moving to cloud virtual machines. Those VMs got broken up into containers, and the containers can fit to the size of the service. Services that are more narrowly defined take up smaller containers, and can be packed more densely into the virtual machines–hence the term “microservices.” As this change to software

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Elasticsearch with Philipp Krenn

http://traffic.libsyn.com/sedaily/Elasticsearch.mp3Podcast: Play in new window | Download Search is a common building block for applications. Whether we are searching Wikipedia or our log files, the behavior is similar: a query is entered and the most relevant documents are returned. The core data structure for search is an inverted index. Elasticsearch is a scalable, resilient search tool that shards and replicates a search index. Philipp Krenn from Elastic joins the show

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API Design Standards with Andy Beier

http://traffic.libsyn.com/sedaily/api-design.mp3Podcast: Play in new window | Download There are various standards at play when creating and consuming Application Program Interfaces (APIs).  These standards, though, are mostly technical and mostly lower-level than the content of the API. Andy Beier has experienced the broad range of API quality in his role with Domo in creating integrations with other businesses.  He has made standardization of good practices in creating APIs his mission, with

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Failure Injection with Kolton Andrus

http://traffic.libsyn.com/sedaily/gremlin_edited.mp3Podcast: Play in new window | Download Servers in a data center fail. Sometimes entire data centers have a power outage. Bugs in an application make it into production. Human operators make mistakes and cause data to be deleted. Failure is unavoidable. We make backups and replicate our servers so that when a failure occurs, we can quickly respond to it without making the user feel much pain. But how

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