#392
Oct 21, 2016 · 1 hr 12 min
Counted on this page — what you have heard stays on this device, so it is not something the list can be paged by.
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#391Oct 20, 2016 · 1 hrGoogle Cloudbuilding with Joe Beda
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 a simple task to make this internal cloud consumable by the public–not to mention competitive with AWS. In order for a cloud provider to be successful, it needs to offer self-healing, self-managing infrastructure that can run microservices.
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#390Oct 19, 2016 · 1 hr 4 minDocker Cloudcasting with Brian Gracely
Cloud computing was something much different in 2011, when Brian Gracely and Aaron Delp started The Cloudcast, a podcast I listen to on a regular basis. The Cloudcast features technical discussions about cloud infrastructure technology, and one of the most recent shows was a monologue by Brian Gracely where he explained his perspective on the industry rumblings about a Docker fork. The utility of a container for so many different purposes leads to different organizations having differing preferences for what use case is optimized for. The impression that I took away from this conversation, as well as the next episode that will air with Joe Beda, is that the diverse opinions and products in the container and orchestration ecosystem is quite healthy. Brian does a great job explaining his perspective on The Cloudcast, and he discusses his beliefs further in this episode.
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#389Oct 18, 2016 · 1 hr 3 minSimpsons Data Science with Todd Schneider
The Simpsons is a classic, beloved television show. The scripts of The Simpsons have been made publicly available, and include dialogue, location, and character information. Todd Schneider used these scripts and other information sources as a corpus to analyze The Simpsons and find interesting statistics–such as who the most important supporting characters were, and how the ratings of the show have trended over time relative to other TV shows that have declined in ratings. Todd works at Genius in New York, and I took the opportunity to ask him other questions about pop culture, given that Genius is a place where pop culture and data collide. If you haven’t seen the site, it started out as a wiki for rap music, and quickly grew to more aspects of pop culture. Todd also has a variety of other side projects, involving betting markets, analysis of taxis vs Lyft and Uber, and a systematic study of the wedding section of the New York Times.
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#388Oct 17, 2016 · 57 minPANCAKE STACK Data Engineering with Chris Fregly
Data engineering is the software engineering that enables data scientists to work effectively. In today’s episode, we explore the different sides of data engineering–the data science algorithms that need to be processed and the implementation of software architectures that enable those algorithms to run smoothly. The PANCAKE STACK is a 12-letter acronym that Chris Fregly gave to a collection of data engineering technologies including Presto, Cassandra, Kafka, Elastic Search, and Spark. In his current life, Chris travels around the world giving workshops on how to deploy and use the PANCAKE STACK. Before that, he was an engineer at Netflix, where he received an Emmy for Streaming Engineering Excellence.
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#387Oct 14, 2016 · 1 hrKafka Event Sourcing with Neha Narkhede
When a user of a social network updates her profile, that profile update needs to propagate to several databases that want to know about such an update–search indexes, user databases, caches, and other services. When Neha Narkhede was at LinkedIn, she helped develop Kafka, which was deployed at LinkedIn to help solve this very problem. Using Kafka as an event queue, LinkedIn adopted the CQRS architectural pattern together with event sourcing. Event sourcing is an architectural pattern that allows changes to our application model to be represented as events. Each event is published to an event queue, and is pulled off of the queue by each of the various services that need to consume that event. Event sourcing and the related architectural pattern CQRS allow for a flow of information through an application that is easy to reason about, and has several other desirable properties. In today’s episode, Neha explains how to use Kafka for event sourcing and how related software patterns are improving the architectures of companies like Netflix and Uber. For more information, check out this Confluent blog entry.
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#386Oct 13, 2016 · 52 minDevOps Handbook with Gene Kim
The intent of the DevOps movement is to get organizations moving faster and more effectively by breaking down siloes, and improving communication. Gene Kim’s book The Phoenix Project illustrated this by telling the fictional story of a company adopting a DevOps mentality. Although that book was fiction, Gene is an experienced engineer, having worked as founder and CTO of Tripwire, a software company that makes security and compliance automation software. In his new book The DevOps Handbook, Gene presents a practical companion to The Phoenix Project. Together with his co-authors, Gene has written a guide for how to move an organization toward DevOps, and in this episode we explore some of the topics from his book. Check out an excerpt from Gene’s book here: DevOps Handbook
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#385Oct 12, 2016 · 49 minNetflix Scheduling with Sharma Podila
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 from. At the cluster level, this means scheduling the application requests intelligently. Sharma Podila, a distributed systems software architect at Netflix, explains how Netflix has built a cloud native scheduling system on top of Mesos.
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#384Oct 11, 2016 · 58 minMonitoring Architecture with Theo Schlossnagle
Building a monitoring system is a complex distributed systems problem. Events are produced from different points in an application and must be aggregated in order to form metrics. These events are often ingested by a time series database, which forms the backbone of our monitoring system. Theo Schlossnagle is the CEO of Circonus, where he has been working on architecting the company’s monitoring software for six years. In this episode, we talk about how to build a monitoring system and the requirements for the underlying time-series database, as well as what monitoring even is.
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#383Oct 10, 2016 · 53 minContinuous Delivery with David Rice
In order to move software updates from the development team to production, companies do a variety of things. Some teams might email files to each other or use FTP or even floppy disks. Most companies today at least use version control systems like Git together with separate servers for development and production. When code is ready to move to production, a build that is on the development server gets copied over to the production servers, and the production servers begin serving real users. This process is known as deployment, and over the last few decades companies have started deploying more rapidly (even “continuously”), leading to faster iterations and better feedback loops between the software development team and the users of the product. A particularly effective version of this workflow is known as continuous delivery. In today’s episode, David Rice from ThoughtWorks joins the show to give a short history of continuous delivery, and how continuous delivery actually looks in practice.
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#382Oct 7, 2016 · 59 minKafka Streams with Jay Kreps
Kafka Streams is a library for building streaming applications that transform input Kafka topics into output Kafka topics. In a time when there are numerous streaming frameworks already out there, why do we need yet another? To quote today’s guest Jay Kreps “the gap we see Kafka Streams filling is less the analytics-focused domain these frameworks focus on and more building core applications and microservices that process data streams.” Jay is the CEO of Confluent, a company that is building Kafka technology, and he is one of the original authors of Kafka. We began with a brief history of why Kafka evolved to be the message broker of choice for so many data engineering stacks, then we got into a discussion of streaming–what is streaming? How does Kafka communicate with streaming frameworks? Our conversation concluded with a discussion of Kafka Streams and the future of the Kafka data platform.
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#381Oct 6, 2016 · 54 minScalaJS with Haoyi Li
Scala is a functional programming language built on the JVM. For more than a decade, this didn’t mean anything to front end web developers. More recently, ScalaJS has brought Scala to the front end. ScalaJS is a project that compiles any Scala program down to JavaScript–so that all of your Scala programs can run on the browser. Haoyi Li has worked on ScalaJS extensively and has written an online book about ScalaJS. If you are a front end developer looking for a safer way to write your web apps, you will like this episode–or if you are a fan of functional programming.
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#380Oct 5, 2016 · 37 minDeveloper Roles with Dave Curry and Fred George
Software teams are traditionally composed of roles such as project manager, developer, QA, and manager. What happens if you throw out all of those titles, hire mostly engineers, and ask them to do whatever they think is best? That is the core idea behind Fred George’s idea of Developer Anarchy. In today’s episode, David Curry guest hosts an interview with Fred George. They talk about the structure of teams and the idea of developer anarchy. For a great complement to this episode, check out the Software Engineering Radio episode about developer anarchy.
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#379Oct 4, 2016 · 59 minPlatform as a Service with Sinclair Schuller
Platform as a service can mean different things to different people. The most prominent feature of a PaaS is the ability to abstract away issues that every developer within an organization has to deal with. As an example, developers today don’t need to fear scalability and load balancing issues as much as engineers of the 90’s and early 2000s. We can develop our applications without worrying about the scaling that is going on under the covers. Sinclair Schuller is the CEO of Apprenda and he joins the show today to discuss what is involved in building a PaaS, particularly one targeted at enterprises. His company was started in 2007, just a few years after AWS got started. We also talked about the potential Docker Fork, for which Sinclair had useful business and engineering perspectives.
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#378Oct 3, 2016 · 56 minDocker Fork with Alex Williams and Joab Jackson
Docker containers changed how engineers think about building software, and the company most responsible for the widespread adoption of containers is Docker itself. Since containerization has caught on in the mainstream, companies like RedHat, Google, Huawei, and many other big players have built platform products that utilize Docker containers. Docker containers are the unit that many engineers use to deploy their applications, but the servers that run those containers are usually on infrastructure providers like Amazon, Google, or Rackspace. This raises the question–how will Docker the company make money? Having raised $180M in equity, Docker has plenty of time to find something that works, but there are suspicions in the open source community that aggressive changes to the open source Docker project are being made by Docker the company with the long-term objective of monetization. These changes–namely the default support for Docker Swarm–are not nefarious, but they might be less likely to occur of Docker were just an open source project, as opposed to an open source project being tended by a well-financed company. The New Stack broke the story about the potential Docker Fork, and Alex Williams and Joab Jackson of The New Stack join me on today’s episode. We go deep into the facts and speculations about why a fork might occur, the motivations of different key players, and the disputes within the community that have led us to this moment.
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#377Sep 30, 2016 · 58 minAndela with Brice Nkengsa
Africa has a huge reservoir of untapped technical talent. Tech companies have a huge amount of work they need skilled employees for. Andela recruits the most talented technologists across Africa, shapes them into world-class software developers, and places them with tech companies worldwide such as Google and Microsoft. Brice Nkengsa is the director of engineering at Andela, and he joins the show to discuss Andela. This episode touches on many of the themes of Software Engineering Daily–boot camps, scaling an organization, microservices, and the future of work.
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#376Sep 29, 2016 · 57 minRemote Work with Scott Berkun
After nine years at Microsoft, Scott Berkun left to become an author. One of his books on project management was read by Matt Mullenweg, the creator of the WordPress blogging tool that runs a large percentage of the internet (including Software Engineering Daily). Scott became friends with the WordPress founder, who is also the CEO of Automattic, a company that sells WordPress hosting and support. Around that time, Automattic was run as a completely flat company. Everyone reported to Matt. This was unsustainable, and eventually Matt decided that Automattic should try management, and he convinced Scott to take a break from his writing career to return to the world of software engineering as Automattic’s first manager. Scott accepted the role under the condition that he could write a book about the experience, and the result of that agreement is “The Year Without Pants: WordPress.com and the Future of Work”, which is a brilliant depiction of what it is like to work at a completely remote software company. Scott joins the show today to talk about his book and his career journey–from Microsoft, to writing, to WordPress, and back to writing. He also shares his thoughts on the workplace dynamics that we spend our days in at software companies.
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#375Sep 28, 2016 · 58 minZuckerberg Files with Michael Zimmer and Nick Proferes
Mark Zuckerberg may be the most powerful person in the world. At no other time in history has a single human had such fine-grained control over the most influential tool for media. Today’s guests are Michael Zimmer and Nick Proferes, the creators of The Zuckerberg Files, an index of every recorded word that Mark Zuckerberg has said in text, video, or audio. Why would someone create this? I was partly expecting Michael and Nick to be anti-Facebook, because The Zuckerberg Files sounds like a tool to hold the Facebook CEO accountable. In reality, Michael and Nick have a nuanced view of Facebook and Zuckerberg–they are Facebook users themselves, and they initially built The Zuckerberg Files as a way to portent product directions that Facebook might lean towards–particularly those related to privacy.
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#374Sep 27, 2016 · 34 minScikit-learn with Andreas Mueller
Scikit-learn is a set of machine learning tools in Python that provides easy-to-use interfaces for building predictive models. In a previous episode with Per Harald Borgen about Machine Learning For Sales, he illustrated how easy it is to get up and running and productive with scikit-learn, even if you are not a machine learning expert. Srini Kadamati hosts today’s show and interviews Andreas Mueller, a core committer to scikit-learn. Srini and Andreas discuss the background and implementation of scikit-learn and walk through some prototypical workflows for using it.
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#373Sep 26, 2016 · 1 hr 2 minContainer Security with Phil Estes
Containers have become the unit of infrastructure that many technology stacks deploy to. With the shift to containers, the attack surface of an application has changed, and we need to reconsider our security models; the resource allocation of our containers, the interactions between different containers on a single machine, and the big picture–how the external web may interact with our containers. Phil Estes joins the show to discuss container security, as well as the OCI, container orchestration, as well as other container related topics.