Category Cloud Engineering

Serverless Event-Driven Architecture with Danilo Poccia

http://traffic.libsyn.com/sedaily/ServerlessEvents.mp3Podcast: Play in new window | Download In an event driven application, each component of application logic emits events, which other parts of the application respond to. We have examined this pattern in previous shows that focus on pub/sub messaging, event sourcing, and CQRS. In today’s show, we examine the intersection of event driven architecture and serverless architecture. Serverless applications can be built by combining functions-as-a-service (like AWS Lambda) together

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Netflix Serverless-like Platform with Vasanth Asokan

http://traffic.libsyn.com/sedaily/NetflixServerless.mp3Podcast: Play in new window | Download The Netflix API is accessed by developers who build for over 1000 device types: TVs, smartphontes, VR headsets, laptops. If it has a screen, it can probably run Netflix. On each of these different devices, the Netflix experience is different. Different screen sizes mean there is variable space to display the content. When you open up Netflix, you want to efficiently browse through

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Serverless Authentication with Bobby Johnson

http://media.blubrry.com/audio_reviews/p/traffic.libsyn.com/sedaily/Webtask.mp3Podcast: Play in new window | Download Serverless architecture is software that runs without an addressable server. Serverless is made possible by two types of technology: platform as a service providers like Auth0, and functions as a service like AWS Lambda. With both of these technologies, we can program logic that runs without being deployed to a server. Functions as a service are cheap and scalable. Write your code for

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Augmented Reality with Scott Montgomerie

http://traffic.libsyn.com/sedaily/ScopeAR.mp3Podcast: Play in new window | Download Augmented reality applications are slowly making their way into the world of the consumer. Pokemon Go created the magical experience of seeing Pokemon superimposed upon the real world. IKEA’s mobile app lets you see how a couch would fit into your living room, which has a significant improvement on the furniture buying process. Augmented reality applications can have even more dramatic impact on

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Elastic Load Balancing with Ranga Rajagopalan

http://traffic.libsyn.com/sedaily/Avi_Networks_complete_with_preamble.mp3Podcast: Play in new window | Download Computational load is the amount of demand that is being placed on a computer system. “Load” can take the form of memory, CPU, network bandwidth, disk space, and other finite resources. When we design systems, we need to prepare for high-load events. On a social network, people are much more active in the mornings. On an e-commerce site, Black Friday causes many more

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IFTTT Architecture with Nicky Leach

http://traffic.libsyn.com/sedaily/IFTTT.mp3Podcast: Play in new window | Download It’s 9pm at night, and you are hungry. You order a pizza from Domino’s. You live on a street that’s dark, and so you have installed a smart lightbulb in front of your mailbox that lights up the address. When the pizza at Domino’s is ready, you want the lightbulb on your mailbox to light up so that the delivery person can read

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Quantum Computing Introduction with Zlatko Minev

http://traffic.libsyn.com/sedaily/QuantumComputing.mp3Podcast: Play in new window | Download Computer chips have physical limitations. When transistors get too small, electrons start to behave in ways that make the hardware modules less reliable. Our reliable technological progress has been enabled by Moore’s Law: the idea that the number of components we can fit on a chip doubles roughly every 12-18 months. We can’t keep shrinking the size of these components, because physics is

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Internet Monitoring with Matt Kraning

http://traffic.libsyn.com/sedaily/InternetMonitoring.mp3Podcast: Play in new window | Download How would you build a system for indexing and monitoring the entire Internet? Start by breaking the Internet up into IP address ranges. Give each of those address ranges to servers distributed around the world. On each of those servers, iterate through your list of IP addresses, sending packets to them. Depending on what sorts of packets those IP addresses respond to, and

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Scala Native with Denys Shabalin

http://traffic.libsyn.com/sedaily/ScalaNative.mp3Podcast: Play in new window | Download Scala is a functional and object oriented programming language built on the JVM. Scala Native takes this language, loved by many, and brings it to bare metal. Scala Native is an optimizing ahead-of-time compiler and lightweight managed runtime designed specifically for Scala. Denys Shabalin is a Research Assistant at the EPFL and the primary creator of Scala Native. In this episode, Adam Bell

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Tinder Engineering Management with Bryan Li

http://traffic.libsyn.com/sedaily/TinderManagement.mp3Podcast: Play in new window | Download Tinder is a rapidly growing social network for meeting people and dating. In the past few years, Tinder’s userbase has grown rapidly, and the engineering team has scaled to meet the demands of increased popularity. On Tinder, you are presented with a queue of suggested people that you might match with, and you swipe left or right to indicate that you like or

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Video Infrastructure with Matt McClure and Jon Dahl

http://traffic.libsyn.com/sedaily/VideoInfrastructure.mp3Podcast: Play in new window | Download Playing a video on the Internet seems simple. You press play, the video gets delivered, and boom–you are watching Game of Thrones, right? It’s a bit more complicated. Unless you have built an application that involves video, you probably have not dealt with the world of codecs, bitrates, and streaming. Depending on the bandwidth between the user and the server, you might want

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Tinder Growth Engineering with Alex Ross

http://traffic.libsyn.com/sedaily/TinderGrowthEngineering.mp3Podcast: Play in new window | Download Tinder is a popular dating app where each user swipes through a sequence of other users in order to find a match. Swiping left means you are not interested. Swiping right means you would like to connect with the person. The simple premise of Tinder has led to massive growth, and the app is now also used to discover new friends and create

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Spotify Event Delivery with Igor Maravic

http://traffic.libsyn.com/sedaily/SpotifyEventDelivery.mp3Podcast: Play in new window | Download Spotify is a streaming music company with more than 50 million users. Whenever a user listens to a song, Spotify records that event and uses it as input to learn more about the user’s preferences. Listening to a song is one type of event–there are hundreds of others. Opening the Spotify app, skipping a song, sharing a playlist with a friend–all of these

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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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Error Diagnosis with James Smith

http://traffic.libsyn.com/sedaily/ErrorDiagnosis.mp3Podcast: Play in new window | Download When a user experiences an error in an application, the engineers who are building that application need to find out why that error occurred. The root cause of that error may be on the user’s device, or within a piece of server-side logic, or hidden behind a black box API. To fix a complex error, we need a stack trace of contextual information

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Open Compute Project with Steve Helvie

http://traffic.libsyn.com/sedaily/OpenComputeProject.mp3Podcast: Play in new window | Download Facebook was rapidly outgrowing its infrastructure in 2009. Classic data center design was not up to the task of the rapid influx of new users and data, photos and streaming video hitting Facebook’s servers. A small team of engineers spent the next two years designing a data center from the ground up to be cheaper, more energy efficient, and more ergonomic for the

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Serverless Continuous Delivery with Robin Weston

http://traffic.libsyn.com/sedaily/ServerlessCD.mp3Podcast: Play in new window | Download Serverless computing reduces the cost of using the cloud. Serverless also makes it easy to scale applications. The downside: building serverless apps requires some mindset shift. Serverless functions are deployed to transient units of computation that are spun up on demand. This is in contrast to the typical model of application delivery–the deployment of an application to a server or a container that

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Serverless Startup with Yan Cui

http://traffic.libsyn.com/sedaily/ServerlessBurningMonk.mp3Podcast: Play in new window | Download After raising $18 million, social networking startup Yubl made a series of costly mistakes. Yubl hired an army of expensive contractors to build out its iOS and Android apps. Drama at the executive level hurt morale for the full-time employees. Most problematic, the company was bleeding cash due to a massive over-investment in cloud services. This was the environment in which Yan Cui

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Platform Continuous Delivery with Andy Appleton

http://traffic.libsyn.com/sedaily/HerokuCI.mp3Podcast: Play in new window | Download Continuous delivery is a model for deploying small, frequent changes to an application. In a continuous delivery workflow, code changes that are pushed to a repository set off a build process that spins up a new version of the application. Testing is performed against that new build before advancing it to production, merging it with the existing codebase. Many continuous delivery products are

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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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