Tag Distributed Systems

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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Scalable Multiplayer Games with Yan Cui

http://traffic.libsyn.com/sedaily/ScalableMultiplayerGames.mp3Podcast: Play in new window | DownloadRemember when the best game you could play on your phone was Snake? In 1998, Snake was preloaded on Nokia phones, and it was massively popular. That same year Half-Life won game of the year on PC. Metal Gear Solid came out for Playstation. The first version of Starcraft also came out in 1998. In 1998, few people would have anticipated that games with

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Decentralized Objects with Martin Kleppman

http://traffic.libsyn.com/sedaily/CRDTs_Decentralized_Files.mp3Podcast: Play in new window | DownloadThe Internet was designed as a decentralized system. Theoretically, if Alice wants to send an email to Bob, she can set up an email client on her computer and send that email to Bob’s email server on his computer. In reality, very few people run their own email servers. We all send our emails to centralized services like Gmail, and connect to those centralized

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Cloud-Native SQL with Alex Robinson

http://traffic.libsyn.com/sedaily/CloudNativeSQL.mp3Podcast: Play in new window | Download Applications built in the cloud are often serving requests from all around the world. A user in Hong Kong could have written to a database entry at the moment just before a user in San Francisco and a user in Germany simultaneously try to read from that database. If the user in San Francisco is allowed to see a different database entry than

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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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Distributed Deep Learning with Will Constable

http://traffic.libsyn.com/sedaily/Distributeddeeplearning.mp3Podcast: Play in new window | Download Deep learning allows engineers to build models that can make decisions based on training data. These models improve over time using stochastic gradient descent. When a model gets big enough, the training must be broken up across multiple machines. Two strategies for doing this are “model parallelism” which divides the model across machines and “data parallelism” which divides the data across multiple copies

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Data Intensive Applications with Martin Kleppmann

http://traffic.libsyn.com/sedaily/dataintensive_edited_fixed.mp3Podcast: Play in new window | Download A new programmer learns to build applications using data structures like a queue, a cache, or a database. Modern cloud applications are built using more sophisticated tools like Redis, Kafka, or Amazon S3. These tools do multiple things well, and often have overlapping functionality. Application architecture becomes less straightforward. The applications we are building today are data-intensive rather than compute-intensive. Netflix needs to

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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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Deep Learning with Adam Gibson

http://traffic.libsyn.com/sedaily/DeepLearning.mp3Podcast: Play in new window | Download Deep learning uses neural networks to identify patterns. Neural networks allow us to sequence “layers” of computing, with each layer using learning algorithms such as unsupervised learning, supervised learning, and reinforcement learning. Deep learning has taken off in the last few years, but it has been around for much longer. Adam Gibson founded Skymind, the company behind Deeplearning4j. Deeplearning4j is a distributed deep

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The End of Cloud Computing with Peter Levine

http://traffic.libsyn.com/sedaily/endofcloud_edited.mp3Podcast: Play in new window | Download Cloud computing has pushed computation away from our own private servers and into virtual machines running on a data center. In the world of cloud computing, processing is centralized in these data centers, and our smartphone and laptop application performance suffers from having high latency between the client and the cloud server. As machine learning proliferates, the current model of cloud computing will

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Urbit with Curtis Yarvin and Galen Wolfe-Pauly

http://traffic.libsyn.com/sedaily/urbit_edited.mp3Podcast: Play in new window | Download Urbit is a completely new way of looking at computing. Every user gets a personal server, which runs your apps, wrangles your connected devices, and defines your secure identity. Your urbit presents your whole digital life as a single web service. Urbit feels foreign and confusing for those of us coming from the traditional web because the normal paradigm is to iterate and

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Apache Geode with Swapnil Bawaskar

http://traffic.libsyn.com/sedaily/geode_edited.mp3Podcast: Play in new window | Download There is a hierarchy of ways to access and store data in a computer system. The cheapest, slowest way to store and retrieve data is disk. On the faster end, we have memory. As we architect systems with increasing complexity, we have additional considerations–network latency, transient compute nodes, and numerous caching layers. Apache Geode is a distributed, in-memory system for the JVM. It

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Netflix Scheduling with Sharma Podila

http://traffic.libsyn.com/sedaily/scheduling_at_netflix_edited.mp3Podcast: Play in new window | Download At Netflix, developers write applications with a variety of requirements–from simple requests for a list of movies to more resource-intensive requests like a complex machine learning workflow. Netflix wants developers to be able to request the resources they need from a compute cluster and receive those resources on-demand, without thinking too much about the state of that pool of resources they are drawing

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Slack’s Architecture with Keith Adams

http://traffic.libsyn.com/sedaily/Slack_Architecture.mp3Podcast: Play in new window | Download Slack is a chat application that is rapidly growing in popularity. The focus of Slack is to create a polished, responsive tool for productivity that cuts down on the emailing, context switching, and useless meetings that take place at a typical enterprise.   Keith Adams, the chief architect at Slack, joins the show to explain how those high level principles translate into engineering

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Uber’s Postgres Problems with Evan Klitzke

http://traffic.libsyn.com/sedaily/Uber_DBs.mp3Podcast: Play in new window | Download When a company switches the relational database it uses, you wouldn’t expect the news of the switch to go viral. Most engineers are not interested in the subtle differences between MySQL and Postgres, right?   Uber recently switched from having Postgres as its main relational database to using MySQL. Evan Klitzke wrote a detailed blog post about the migration, and post got very

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Relational Databases with Craig Kerstiens

http://traffic.libsyn.com/sedaily/RelationalDBs.mp3Podcast: Play in new window | Download Relational databases are used by most applications. MySQL, Postgres, Microsoft SQL Server, and other products implement the core features of a relational database in different ways. A developer who has never studied this space in detail may not know the differences between these databases, and in this episode we describe some tradeoffs that relational databases can make. Craig Kerstiens is an engineer at

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CoreOS with Brandon Philips

http://traffic.libsyn.com/sedaily/CoreOS_Edited_2.mp3Podcast: Play in new window | Download Google’s infrastructure has been the source inspiration for research papers, software projects, and entire companies. Google pioneered the idea that we care less about the individual machines we are running our applications on, and more about the applications themselves.   Containers are the abstraction we use to separate the concerns of the application from those of the underlying hardware. CoreOS is an operating system

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Distributed Tracing with Reshmi Krishna

http://traffic.libsyn.com/sedaily/distributed_tracing_edited_fixed.mp3Podcast: Play in new window | Download In a microservices architecture, a user request will often make its way through several different services before it returns a result to the end user. If a user experiences a failed request, the root cause could be in any of the services along that request path. Even more problematic is the challenge of debugging latency in this kind of request chain.   Reshmi

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Prometheus Monitoring with Brian Brazil

http://traffic.libsyn.com/sedaily/prometheusbrian_edited_fixed.mp3Podcast: Play in new window | Download Prometheus is a tool for monitoring our distributed applications. It allows us to focus on the services we are deploying rather than the individual machines that make up instances of that service.   The monitoring service itself is a portion of a distributed system that is treated differently than the services we are monitoring. We don’t want to use a consensus-based tool like

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