Category Cloud Engineering

Cloud and Edge with Steve Herrod

http://traffic.libsyn.com/sedaily/2018_02_23_VMWareCTO.mp3Podcast: Play in new window | Download Steve Herrod led engineering at VMWare as the company scaled from 30 engineers to 3,000 engineers. After 11 years, he left to become a managing director for General Catalyst, a venture capital firm. Since he has both operating experience and a wide view of the technology landscape as an investor, he is well-equipped to discuss a topic that we have been covering on

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Serverless Systems with Eduardo Laureano

http://traffic.libsyn.com/sedaily/2018_02_22_MicrosoftServerless.mp3Podcast: Play in new window | Download On Software Engineering Daily, we have been covering the “serverless” movement in detail. For people who don’t use serverless functions, it seems like a niche. Serverless functions are stateless, auto-scaling, event driven blobs of code. You might say “serverless sounds kind of cool, but why don’t I just use a server? It’s a paradigm I’m used to.” Serverless is exciting not because of

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Cloud Foundry Overview with Mike Dalessio

http://traffic.libsyn.com/sedaily/2018_02_21_MikeDaLessio.mp3Podcast: Play in new window | Download Earlier this year we did several shows about Cloud Foundry, followed by several shows about Kubernetes. Both of these projects allow you to build scalable, multi-node applications–but they serve different types of users. Cloud Foundry encompasses a larger scope of the application experience than Kubernetes. Kubernetes is lower level, and is actually being used within newer versions of Cloud Foundry to give Cloud

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Box Kubernetes Migration with Sam Ghods

http://traffic.libsyn.com/sedaily/2018_02_13_BoxKubernetes.mp3Podcast: Play in new window | Download Over 12 years of engineering, Box has developed a complex architecture of services. Whenever a user uploads a file to Box, that upload might cause 5 or 6 different services to react to the event. Each of these services is managed by a set of servers, and managing all of these different servers is a challenge. Sam Ghods is the cofounder and services

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Scaling Box with Jeff Quiesser

http://traffic.libsyn.com/sedaily/2018_02_12_BoxEngineering.mp3Podcast: Play in new window | Download When Box started in 2006, the small engineering team had a lot to learn. Box was one of the earliest cloud storage companies, with a product that allowed companies to securely upload files to remote storage. This was two years before Amazon Web Services introduced on-demand infrastructure, so the Box team managed their own servers, which they learned how to do as they

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Load Testing Mobile Applications with Paulo Costa and Rodrigo Coutinho

http://traffic.libsyn.com/sedaily/2018_02_08_OutSystems.mp3Podcast: Play in new window | Download Applications need to be ready to scale in response to high-load events. With mobile applications, this can be even more important. People rely on mobile applications such as banking, ride sharing, and GPS. During Black Friday, a popular ecommerce application could be bombarded by user requests–you might not be able to complete a request to buy an item at the Black Friday discount.

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Serverless at the Edge with Kenton Varda

http://traffic.libsyn.com/sedaily/2018_02_06_CloudFlareWorkers.mp3Podcast: Play in new window | Download Over the last decade, computation and storage has moved from on-premise hardware into the cloud data center. Instead of having large servers “on premise,” companies started to outsource their server workloads to cloud service providers. At the same time, there has been a proliferation of devices at the “edge.” The most common edge device is your smartphone, but there are many other smart

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Linkedin Resilience with Bhaskaran Devaraj and Xiao Li

http://traffic.libsyn.com/sedaily/2018_02_05_LinkedinResilience.mp3Podcast: Play in new window | Download How do you build resilient, failure tested systems? Redundancy, backups, and testing are all important. But there is also an increasing trend towards chaos engineering–the technique of inducing controlled failures in order to prove that a system is fault tolerant in the way that you expect. In last week’s episode with Kolton Andrus, we discussed one way to build chaos engineering as a

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Chaos Engineering with Kolton Andrus

http://traffic.libsyn.com/sedaily/2018_02_02_Gremlin.mp3Podcast: Play in new window | Download The number of ways that applications can fail are numerous. Disks fail all the time. Servers overheat. Network connections get flaky. You assume that you are prepared for such a scenario, because you have replicated your servers. You have the database backed up. Your core application is spread across multiple availability zones. But are you really sure that your system is resilient? The

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How to Change an Enterprise’s Software and Culture with Zhamak Dehghani

http://traffic.libsyn.com/sedaily/2018_02_01_MicroservicesZhamakDehgani.mp3Podcast: Play in new window | Download On this show, we spend a lot of time talking about CI/CD, data engineering, and microservices. These technologies have only been widely talked about for the last 5-10 years. That means that they are easy to adopt for startups that get founded in the last 5-10 years, but not necessarily for older enterprises. Within a large enterprise, it can be challenging to make

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Serverless Containers with Sean McKenna

http://traffic.libsyn.com/sedaily/2018_01_25_SeanMcKenna.mp3Podcast: Play in new window | Download After two weeks of episodes about Kubernetes, our in-depth coverage of container orchestration is drawing to a close. We have a few more shows on the topic before we move on to covering other aspects of software. If you have feedback on this thematic format (whether you like it or not), send me an email: jeff@softwareengineeringdaily.com Today’s episode fits nicely into some of

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Container Instances with Gabe Monroy

http://traffic.libsyn.com/sedaily/2018_01_22_ContainerInstances.mp3Podcast: Play in new window | Download In 2011, platform-as-a-service was in its early days. It was around that time that Gabe Monroy started a container platform called Deis, with the goal of making an open source platform-as-a-service that anyone could deploy to whatever infrastructure they wanted. Over the last six years, Gabe had a front row seat to the rise of containers, the variety of container orchestration systems, and

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Service Mesh Design with Oliver Gould

http://traffic.libsyn.com/sedaily/2018_01_19_ConduitProxy.mp3Podcast: Play in new window | Download Oliver Gould worked at Twitter from 2010 to 2014. Twitter’s popularity was taking off, and the engineering team was learning how to scale the product. During that time, Twitter adopted Apache Mesos, and began breaking up its monolithic architecture into different services. As more and more services were deployed, engineers at Twitter decided to standardize communications between those services with a tool called

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Kubernetes Storage with Bassam Tabbara

http://traffic.libsyn.com/sedaily/2018_01_18_RookKubernetesStorage.mp3Podcast: Play in new window | Download Modern applications store most of their data on hosted storage solutions. We use hosted block storage to back databases, hosted object storage for objects such as videos, and hosted file storage for file systems. Using a cloud provider for these storage systems can simplify scalability, durability, and availability–it can be less painful than taking care of storage yourself. One downside: the storage systems

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Kubernetes State Management with Niraj Tolia

http://traffic.libsyn.com/sedaily/2018_01_17_KubernetesDataNiraj.mp3Podcast: Play in new window | Download A common problem in a distributed system: how do you take a snapshot of the global state of that system? Snapshot is difficult because you need to tell every node in the system to simultaneously record its state. There are several reasons to take a snapshot. You might want to take a picture of the global state for the purposes of debugging. Or

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Kubernetes Operations with Brian Redbeard

http://traffic.libsyn.com/sedaily/2018_01_16_MulticloudKubernetes.mp3Podcast: Play in new window | DownloadIn the last four years, CoreOS has been at the center of enterprise adoption of containers. During that time, Brian Harrington (or “Redbeard”) has seen a lot of deployments. In this episode, Brian discusses the patterns he has seen among successful Kubernetes deployments–and the pitfalls of the less successful. How should you manage configuration? How can you avoid IP address overlap between containers? How

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FluentD with Eduardo Silva

http://traffic.libsyn.com/sedaily/2018_01_15_FluentD.mp3Podcast: Play in new window | Download A backend application can have hundreds of services written in different programming frameworks and languages. Across these different languages, log messages are produced in different formats. Some logging is produced in XML, some is produced in JSON, some is in other formats. These logs need to be unified into a common format, and centralized for any developer who wants to debug. The popularity

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The Gravity of Kubernetes

http://traffic.libsyn.com/sedaily/2018_01_13_GravityOfKubernetes.mp3Podcast: Play in new window | Download Kubernetes has become the standard way of deploying new distributed applications. Most new internet businesses started in the foreseeable future will leverage Kubernetes (whether they realize it or not). Many old applications are migrating to Kubernetes too. Before Kubernetes, there was no standardization around a specific distributed systems platform. Just like Linux became the standard server-side operating system for a single node, Kubernetes

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Kubernetes Vision with Brendan Burns

http://traffic.libsyn.com/sedaily/BrendanBurns.mp3Podcast: Play in new window | Download Kubernetes has become the standard system for deploying and managing clusters of containers. But the vision of the project goes beyond managing containers. The long-term goal is to democratize the ability to build distributed systems. Brendan Burns is a co-founder of the Kubernetes project. He recently announced an open source project called Metaparticle, a standard library for cloud-native development: Metaparticle builds on top

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High Volume Distributed Tracing with Ben Sigelman

http://traffic.libsyn.com/sedaily/DistributedTracing.mp3Podcast: Play in new window | Download You are requesting a car from a ridesharing service such as Lyft. Your request hits the Lyft servers and begins trying to get you a car. It takes your geolocation, and passes the geolocation to a service that finds cars that are nearby, and puts all those cars into a list. The list of nearby cars is sent to another service, which sorts

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