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Software Engineering Daily

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Software Daily: The world through the lens of software.

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#1432
Jun 9, 2020 · 45 min
Human in the Loop Data Analytics with Aditya Parameswaran
The life cycle of data management includes data cleaning, extraction, integration, analysis and exploration, and machine learning models. It would be great if all of this data management could be handled with automation, but unfortunately that is not an option. For most applications, data management requires a human in the loop. A human in the loop might be responsible for working in a spreadsheet, or labeling data as a mechanical turk, or creating an algorithm for data labeling in Snorkel. Data scientists and data analysts are humans in the loop, studying large data sets. Aditya Parameswaran is an assistant professor at UC Berkeley. He studies human-in-the-loop data analytics, and he joins the show to talk about the work and the projects that he is focused on, including DataSpread, an alternative to Excel, and OrpheusDB, a relational database versioning system.
#1431
Jun 8, 2020 · 51 min
Tilt: Kubernetes Tooling with Dan Bentley
Kubernetes continues to mature as a platform for infrastructure management. At this point, many companies have well-developed workflows and deployment patterns for working with applications built on Kubernetes. The complexity of some of these deployments may be daunting, and when a new employee joins a company, that employee needs to get quickly onboarded with the custom dev environment. Environment management is not the only issue with Kubernetes development. When a service gets updated, that update needs to be live and usable as fast as possible. When Kubernetes-related errors occur, those problems need to be easily accessible in a UI for triage. Dan Bentley is the CEO of Windmill Engineering, a company that makes a set of Kubernetes tools called Tilt. Dan joins the show to talk about the workflow for deploying Kubernetes infrastructure and the role of Tilt, the product he has been working on.
#1430
Jun 5, 2020 · 45 min
Uber’s Data Visualization Tools with Ib Green
Uber needs to visualize data on a range of different surfaces. A smartphone user sees cars moving around on a map as they wait for their ride to arrive. Data scientists and operations researchers within Uber study the renderings of traffic moving throughout a city. Data visualization is core to Uber, and the company has developed a stack of technologies around visualization in order to build appealing, highly functional applications. DeckGL is a library for high-performance visualizations of large data sets. LumaGL is a set of components that targets high performance rendering. These and other tools make up VisGL, the data visualization technology that powers Uber. Uber’s visualization team included Ib Green, who left Uber to co-found Unfolded.ai, a company that builds geospatial analytics products. He joins the show to discuss his work on visualization products and libraries at Uber, as well as the process of taking that work to found Unfolded.ai. Full disclosure: I am an investor in Unfolded.ai.
#1429
Jun 4, 2020 · 48 min
Prisma: Modern Database Tooling with Johannes Schickling
A frontend developer issuing a query to a backend server typically requires the developer to issue that query through an ORM or a raw database query. Prisma is an alternative to both of these data access patterns, allowing for easier database access through auto-generated, type-safe query building tailored to an existing database schema. By integrating with Prisma, the developer gets a database client that has query autocompletion, and an API server with less boilerplate code. Prisma also has a system called Prisma Migrate, which simplifies database and schema migrations. Johannes Schickling is CEO of Prisma, and he joins the show to talk about the developments of Prisma that have occurred since we last spoke, and where the company is headed.
#1428
Jun 3, 2020 · 53 min
Tecton: Machine Learning Platform from Uber with Kevin Stumpf
Machine learning workflows have had a problem for a long time: taking a model from the prototyping step and putting it into production is not an easy task. A data scientist who is developing a model is often working with different tools, or a smaller data set, or different hardware than the environment which that model will be deployed to. This problem existed at Uber just as it does at many other companies. Models were difficult to release, iterations were complicated, and collaboration between engineers could never reach a point that resembled a harmonious “DevOps”-like workflow. To address these problems, Uber developed an internal system called Michelangelo. Some of the engineers working on Michelangelo within Uber realized that there was a business opportunity in taking the Michelangelo work and turning it into a product company. Thus, Tecton was born. Tecton is a machine learning platform focused on solving the same problems that existed within Uber. Kevin Stumpf is the CTO at Tecton, and he joins the show to talk about the machine learning problems of Uber, and his current work at Tecton.
#1426
Jun 2, 2020 · 56 min
HoloClean: Data Quality Management with Theodoros Rekatsinas
Many data sources produce new data points at a very high rate. With so much data, the issue of data quality emerges. Low quality data can degrade the accuracy of machine learning models that are built around those data sources. Ideally, we would have completely clean data sources, but that’s not very realistic. One alternative is a data cleaning system, which can allow us to clean up the data after it has already been generated. HoloClean is a statistical inference engine that can impute, clean, and enrich data. HoloClean is centered around “The Probabilistic Unclean Database Model”, which allows for two systems–an “intension” and a “realizer” to work together to fill in missing fields and fix erroneous fields in data. HoloClean was created by Theo Rekatsinas, and he joins the show to talk about the problem of fast, unclean data, and his work with HoloClean. We also talk about other problems in machine learning and the engineering workflows around data.
#1425
Jun 1, 2020 · 57 min
Disaggregated Servers with Yiying Zhang
Server infrastructure traditionally consists of monolithic servers containing all of the necessary hardware to run a computer. These different hardware components are located next to each other, and do not need to communicate over a network boundary to connect the CPU and memory. LegoOS is a model for disaggregated, network-attached hardware. LegoOS disseminates the traditional operating system functionalities into loosely-coupled hardware and software components. By disaggregating data center infrastructure, the overall resource usage and failure rate of server infrastructure can be improved. Yiying Zhang is an assistant professor of computer science at UCSD. Her research focuses on operating systems, distributed systems, and datacenter networking. She joins the show to discuss her work and its implications for data centers and infrastructure.
#1424
May 29, 2020 · 46 min
Kubernetes vs. Serverless with Matt Ward
Kubernetes has become a highly usable platform for deploying and managing distributed systems. The user experience for Kubernetes is great, but is still not as simple as a full-on serverless implementation–at least, that has been a long-held assumption. Why would you manage your own infrastructure, even if it is Kubernetes? Why not use autoscaling Lambda functions and other infrastructure-as-a-service products? Matt Ward is a listener of the show and an engineer at Mux, a company that makes video streaming APIs. He sent me an email that said Mux has been having success with self-managed Kubernetes infrastructure, which they deliberately opted for over a serverless deployment. I wanted to know more about what shaped this decision to opt for self-managed infrastructure, and the costs and benefits that Mux has accrued as a result. Matt joins the show to talk through his work at Mux, and the architectural impact of opting for Kubernetes instead of fully managed serverless infrastructure.
#1423
May 28, 2020 · 51 min
Distributed Systems Research with Peter Alvaro
Every software company is a distributed system, and distributed systems fail in unexpected ways. This ever-present tendency for systems to fail has led to the rise of failure testing, otherwise known as chaos engineering. Chaos engineering involves the deliberate failure of subsystems within an overall system to ensure that the system itself can be resilient to these kinds of unexpected failures. Peter Alvaro is a distributed systems researcher who has published papers on a range of subjects, including debugging, failure testing, databases, and programming languages. He works with both academia and industry. Peter joins the show to discuss his research topics and goals.
#1422
May 27, 2020 · 49 min
Brex Engineering with Cosmin Nicolaescu
Brex is a credit card company that provides credit to startups, mostly companies which have raised money. Brex processes millions of transactions, and uses the data from those transactions to assess creditworthiness, prevent fraud, and surface insights for the users of their cards. Brex is full of interesting engineering problems. The high volume of transactions requires data infrastructure to support all those transactions coming through the platform. As a credit card company, Brex needs to integrate with credit card networks and banking systems. There are internal systems for applications such as dispute resolution. Cos Nicolaescu is the CTO at Brex. He joins the show to discuss engineering at Brex, the dynamics of a credit card company, and his strategies around management. It was an instructive look inside of a rapidly growing fintech company.
#1421
May 26, 2020 · 59 min
Edge Machine Learning with Zach Shelby
Devices on the edge are becoming more useful with improvements in the machine learning ecosystem. TensorFlow Lite allows machine learning models to run on microcontrollers and other devices with only kilobytes of memory. Microcontrollers are very low-cost, tiny computational devices. They are cheap, and they are everywhere. The low-energy embedded systems community and the machine learning community have come together with a collaborative effort called tinyML. tinyML represents the improvements of microcontrollers, lighter weight frameworks, better deployment mechanisms, and greater power efficiency. Zach Shelby is the CEO of EdgeImpulse, a company that makes a platform called Edge Impulse Studio. Edge Impulse Studio provides a UI for data collection, training, and device management. As someone creating a platform for edge machine learning usability, Zach was a great person to talk to the state of edge machine learning and his work building a company in the space.
#1420
May 23, 2020 · 9 min
Software Daily
For the last five months, we have been working on a new version of Software Daily, the platform we built to host and present our content. We are creating a platform that integrates the podcast with a set of other features that make it easier to learn from the audio interviews. Software Daily includes the following features: The world of software is large, and growing bigger every day. Software Daily is a place to explore this world of software companies and projects. If the podcast is a useful resource for you to learn about software, then Software Daily might also provide you with value. This post (and episode) is a brief description of the features that we have built into Software Daily. If you want to listen to Software Engineering Daily without ads, you can become a paid subscriber, paying $10/month or $100/year by going to softwaredaily.com/subscribe. We now have an RSS feed that paid customers can add to a podcast player like Overcast (on iOS) or Podcast Addict (on Android). You can also listen to the premium episodes using our apps for iOS or Android. Whether you are a listener who is fine with listening to ads, or you are a listener who pays to hear episodes without ads, we are happy to have you tuning in. Apple podcasts limits the number of episodes in an RSS feed to 300. The feed with the last 300 episodes is available by searching for Software Daily. In total, we have more than 1200 episodes in our back catalog. Listeners often want to find all our episodes on React, or Kubernetes, or serverless, or self-driving cars. We have been covering these topics for years, and much of the old content has retained its value. Software Daily allows you to easily find all the episodes relating to a subject that you are interested in. You can also find our most popular episodes, ranked by how people interact with them. Additionally, episode transcripts have interactive features with highlighting, commenting, and discussions. We want to create a Medium-like experience for the episodes. Software Daily is a place where listeners can write about the topics they are listening to. When you are listening to lots of episodes about a topic such as GraphQL, you may find it useful to write about that topic as a form of active learning. The topic pages also have a Q&A section. Post questions about a topic, or post an answer. Engage in the community dialogue surrounding a topic you are passionate or curious about. If there is a topic you want to write about, check out softwaredaily.com/write. We will be turning the best written content into short podcast episodes published on the weekends where we will read your contribution and mention your name. If you write something awesome, we want to turn it into audio for larger distribution. Every topic on Software Daily has a Q&A section. We have covered lots of niche software companies and open source projects, and on Software Daily we want to collect more information about the world of software with Q&A. If you want to write about a specific company or topic that you heard about on Software Daily, Q&A is also an option. Our goal with Q&A is to provide a companion experience to listening to the podcast. It is not always easy to retain what you hear in a podcast episode. Answering some questions after you listen to an episode can help with that retention. Are you looking to hire someone specific in the world of software? Post a job on the Software Daily jobs board. We will be announcing some of these jobs on the podcast, especially the more interesting postings, and ones that align with content we are producing. We appreciate you tuning into Software Daily. We would welcome your feedback, and hope you take the time to check out SoftwareDaily.com.
#1419
May 22, 2020 · 1 hr
RedwoodJS with Tom Preston-Werner
Over the last 5 years, web development has matured considerably. React has become a standard for frontend component development. GraphQL has seen massive growth in adoption as a data fetching middleware layer. The hosting platforms have expanded beyond AWS and Heroku, to newer environments like Netlify and Vercel. These changes are collectively known as the JAMStack. With the changes brought by the JAMStack, it raises the question: how should an app be built today? Can a framework offer guidance for how the different layers of a JAMStack app should fit together? RedwoodJS is a framework for building JAMStack applications. Tom Preston-Werner is one of the creators of RedwoodJS, as well as the founder of GitHub and Chatterbug, a language learning app. He joins the show to talk about the future of JAMStack development, and his goals for RedwoodJS.
#1418
May 21, 2020 · 53 min
ArcGIS: Geographic Information Software with Max Payson
Geospatial analytics tools are used to render visualizations for a vast array of applications. Data sources such as satellites and cellular data can gather location data, and that data can be superimposed over a map. A map-based visualization can allow the end user to make decisions based on what they see. ArcGIS is one of the most widely used geospatial analytics platforms. It is created by ESRI, the Environmental Systems Research Institute, which was started in 1969. Today, ESRI products have 40% of the global market share of geospatial analytics software. Max Payson is a solutions engineer at ESRI, and he joins the show to talk about applications of ArcGIS, and the landscape of GIS more broadly.
#1417
May 20, 2020 · 44 min
RudderStack: Open Source Customer Data Infrastructure with Soumyadeb Mitra
Customer data infrastructure is a type of tool for saving analytics and information about your customers. The company that is best known in this category is Segment, a very popular API company. This customer data is used for making all kinds of decisions around product roadmap, pricing, and design. RudderStack is a company built around open source customer data infrastructure. RudderStack can be self-hosted, allowing users to deploy it to their own servers and manage their data however they please. Soumyadeb Mitra is the creator of RudderStack, and he joins the show to talk about the space of customer data infrastructure, and his own company.
#1416
May 19, 2020 · 45 min
Matterport 3-D Imaging with Japjit Tulsi
Matterport is a company that builds 3-D imaging for the inside of buildings, construction sites, and other locations that require a “digital twin.” Generating digital images of the insides of buildings has a broad spectrum of applications, and there are considerable engineering challenges in building such a system. Matterport’s hardware stack involves a camera built in-house by the company. The camera can take 360 degree scans of a room, stitch the imagery together, and make the digital twin available on the cloud. Japjit Tulsi works at Matterport, and he joins the show to discuss 3-D imaging, and his role as CTO of the company.
#1415
May 18, 2020 · 48 min
Frontend Performance with Anycart’s Rafael Sanches
There are many bad recipe web sites. Every time I navigate to a recipe website, it feels like my browser is filling up with spyware. The page loads slowly, everything seems broken, I can feel the 25 different JavaScript adtech tags interrupting each other. Whether I am searching for banana bread or a spaghetti sauce recipe, recipe sites usually make me lose my appetite. Anycart is a recipe platform that allows users to buy all of the ingredients for the recipe and have those ingredients delivered. It’s a vertically integrated content site and delivery system. It is also beautifully designed and extremely performant. I learned about it from Zack Bloom, who works at Cloudflare, as he mentioned it as a case study in performance. Rafael Sanches is a founder of Anycart, and he joins the show to talk about building a recipe delivery service, and the innovations in performance that were necessary to building it.
#1414
May 16, 2020 · 9 min
Software Daily
For the last five months, we have been working on a new version of Software Daily, the platform we built to host and present our content. We are creating a platform that integrates the podcast with a set of other features that make it easier to learn from the audio interviews. Software Daily includes the following features: The world of software is large, and growing bigger every day. Software Daily is a place to explore this world of software companies and projects. If the podcast is a useful resource for you to learn about software, then Software Daily might also provide you with value. This post (and episode) is a brief description of the features that we have built into Software Daily. If you want to listen to Software Engineering Daily without ads, you can become a paid subscriber, paying $10/month or $100/year by going to softwaredaily.com/subscribe. We now have an RSS feed that paid customers can add to a podcast player like Overcast (on iOS) or Podcast Addict (on Android). You can also listen to the premium episodes using our apps for iOS or Android. Whether you are a listener who is fine with listening to ads, or you are a listener who pays to hear episodes without ads, we are happy to have you tuning in. Apple podcasts limits the number of episodes in an RSS feed to 300. The feed with the last 300 episodes is available by searching for Software Daily. In total, we have more than 1200 episodes in our back catalog. Listeners often want to find all our episodes on React, or Kubernetes, or serverless, or self-driving cars. We have been covering these topics for years, and much of the old content has retained its value. Software Daily allows you to easily find all the episodes relating to a subject that you are interested in. You can also find our most popular episodes, ranked by how people interact with them. Additionally, episode transcripts have interactive features with highlighting, commenting, and discussions. We want to create a Medium-like experience for the episodes. Software Daily is a place where listeners can write about the topics they are listening to. When you are listening to lots of episodes about a topic such as GraphQL, you may find it useful to write about that topic as a form of active learning. The topic pages also have a Q&A section. Post questions about a topic, or post an answer. Engage in the community dialogue surrounding a topic you are passionate or curious about. If there is a topic you want to write about, check out softwaredaily.com/write. We will be turning the best written content into short podcast episodes published on the weekends where we will read your contribution and mention your name. If you write something awesome, we want to turn it into audio for larger distribution. Every topic on Software Daily has a Q&A section. We have covered lots of niche software companies and open source projects, and on Software Daily we want to collect more information about the world of software with Q&A. If you want to write about a specific company or topic that you heard about on Software Daily, Q&A is also an option. Our goal with Q&A is to provide a companion experience to listening to the podcast. It is not always easy to retain what you hear in a podcast episode. Answering some questions after you listen to an episode can help with that retention. Are you looking to hire someone specific in the world of software? Post a job on the Software Daily jobs board. We will be announcing some of these jobs on the podcast, especially the more interesting postings, and ones that align with content we are producing. We appreciate you tuning into Software Daily. We would welcome your feedback, and hope you take the time to check out SoftwareDaily.com.
#1413
May 15, 2020 · 56 min
AWS Virtualization with Anthony Liguori
Amazon’s virtual server instances have come a long way since the early days of EC2. There are now a wide variety of available configuration options for spinning up an EC2 instance, which can be chosen from based on the workload that will be scheduled onto a virtual machine. There are also Fargate containers and AWS Lambda functions, creating even more options for someone who wants to deploy virtualized infrastructure. The high demand for virtual machines has led to Amazon moving down the stack, designing custom hardware such as the Nitro security chip, and low level software such as the Firecracker virtual machine monitor. AWS also has built Outposts, which allow for on-prem usage of AWS infrastructure. Anthony Liguori is an engineer at AWS who has worked on a range of virtualization infrastructure: software platforms, hypervisors, and hardware. Anthony joins the show to talk about virtualization at all levels of the stack.
#1411
May 14, 2020 · 41 min
International Consumer Credit Infrastructure with Brian Regan and Misha Esipov
A credit score is a rating that allows someone to qualify for a line of credit, which could be a loan such as a mortgage, or a credit card. We are assigned a credit score based on a credit history, which could be related to work history, rental payments, or loan repayments. One problem with the credit scoring system is that it is not internationalized. If I am coming from Brazil, I have a rental history of someone from Brazil. That information does not get naturally ported over to the United States. There needs to be a system for translating a foreign credit history to a US credit history. Nova Credit is a company that makes a credit passport–a system for allowing users in one geographic location to use the credit history that they have built up to have credit in another location, namely the United States. Brian Regan and Misha Esipov work at Nova Credit, and they join the show to talk about how the company works, and the problem it solves.

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