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#1454
Jul 7, 2020 · 59 min
The Good Parts of AWS with Daniel Vassallo
AWS has over 150 different services. Databases, log management, edge computing, and lots of others. Instead of being overwhelmed by all of these products, an engineering team can simplify their workflow by focusing on a small subset of AWS services–the defaults. Daniel Vassalo is the author of The Good Parts of AWS. An excerpt from the book: “The cost of acquiring new information is high and the consequence of deviating from a default choice is low, so sticking with the default will likely be the optimal choice. A default choice is any option that gives you very high confidence that it will work.” Having confidence in your workflow–even if it is a simple workflow–has advantages. S3, EC2, Elastic Load Balancers: for simple web applications, this is really all you need to build your business. Daniel Vassallo worked at AWS for more than 8 years before leaving to become an entrepreneur and author. He joins the show to talk about what the good parts of AWS are, and his strategy for building applications with that subset of services.
#1453
Jul 6, 2020 · 45 min
Pull Request Environments with Eric Silverman
The modern release workflow involves multiple stakeholders: engineers, management, designers, and product managers. It is a collaborative process that is often held together with brittle workflows. A developer deploys a new build to an ad hoc staging environment and pastes a link to that environment in Slack. Other stakeholders click on that link, then send messages to each other in Slack, or make comments on the pull request in GitHub. This workflow is far from ideal. Collaborating around pull requests can be made easier with a dedicated set of tools for sharing and discussing those pull requests. This is the goal of FeaturePeek, a system for spinning up dedicated pull request environments, creating screenshots and comments, and reimagining the lifecycle of the release workflow. Eric Silverman is a co-founder of FeaturePeek and he joins the show to discuss release management, the interactions between different stakeholders, and the development of his company. Much like the previous show about Postman, in which we explored how API management has become a ripe space for collaboration, the same is true of pull requests.
#1452
Jul 3, 2020 · 48 min
Deepgram: End-to-End Speech Recognition with Scott Stephenson
Deepgram is an end-to-end deep learning platform for speech recognition. Unlike the general purpose APIs from Google or Amazon, Deepgram models are custom-trained for each customer. Whether the customer is a call center, a podcasting company, or a sales department, Deepgram can work with them to build something specific to their use case. Sound data is incredibly rich. Consider all the features in a voice recording: volume, intonation, inflection. And once the speech is transcribed, there are many more features that can be discovered from the text transcription. Scott Stephenson is the CEO of Deepgram, and he joins the show to talk through end-to-end deep learning for speech, as well as the dynamics of the business and the deployment strategy for working with customers.
#1450
Jul 2, 2020 · 56 min
DynamoDB with Alex DeBrie
DynamoDB is a managed NoSQL database service from AWS. It is widely used as a transactional database to fulfill key-value and wide-column data models. In a previous show with Rick Houlihan, we explored how to build a data model and optimize the query patterns for a NoSQL database. Today’s show is about DynamoDB specifically: partitioning, indexing, query semantics, normalization, table design, and other subjects. We talk through how to be cost conscious, and how to integrate with event-based AWS Lambda triggers. Alex DeBrie is the author of The DynamoDB Book, a book whose title speaks for itself. Alex has comprehensive experience with DynamoDB, and he joins the show to share that experience through a detailed discussion of use cases and strategies related to DynamoDB.
#1449
Jul 1, 2020 · 53 min
Snowplow Analytics: Data Collection Platform with Alex Dean
As a user browses a webpage, that browser session generates events that need to be recorded, validated, enriched, and stored. This data is sometimes called customer data infrastructure, or CDI. This data requires a full stack of different tools: a system on the frontend to collect the data, middleware to transport the data, and backend systems for storing and loading that data into data warehouses and other analytical systems. Snowplow Analytics is a data collection platform for storing events. In Snowplow, modules called Trackers send data to Collectors. The data can then be validated and enriched, and then put into the user’s data warehouse via ETL. Alex Dean is the CEO of Snowplow, and he joins the show to talk through the business model, management, and engineering of Snowplow Analytics, as well as the overall data engineering landscape.
#1448
Jun 30, 2020 · 51 min
Postman: API Development with Abhinav Asthana
A software company manages and interacts with hundreds of APIs. These APIs require testing, performance analysis, authorization management, and release management. In a word, APIs require collaboration. Postman is a system for API collaboration. It allows users to test APIs with collections of requests, monitor the API responses, and visualize the query results. Users of Postman can collaborate with their team through Team Workspaces, sharing collections, environments, history, and more. Abhinav Asthana is the founder of Postman and he joins the show to talk about API management and collaboration. Abhinav started Postman as a hobby project, and it has grown into a large and successful business, far beyond the original product of API testing.
#1447
Jun 29, 2020 · 55 min
Cresta: Speech ML for Calls with Zayd Enam
At a customer service center, thousands of hours of audio are generated. This audio provides a wealth of information to transcribe and analyze. With the additional data of the most successful customer service representatives, machine learning models can be trained to identify which speech patterns are associated with a successful worker. By identifying these speaking patterns, a customer service center can continuously improve, with the different representatives learning the different patterns. The same is true for other speech-based tasks, such as sales calls. Cresta is a company that builds systems to ingest high volumes of speech data in order to discover features that correlate with high performance human workers. Zayd Enam is a co-founder of Cresta, and joins the show to talk about the domain of speech data and what he and his team are building at Cresta.
#1446
Jun 26, 2020 · 53 min
React Native Ecosystem with Nader Dabit (Summer Break Repeat)
Originally published July 6, 2017. We are taking a few weeks off. We’ll be back soon with new episodes. React Native allows developers to reuse components from one user interface on multiple platforms. React Native was introduced by Facebook to reduce the pain of teams who were rewriting their user interfaces for web, iOS, and Android. Nader Dabit hosts React Native Radio, a podcast about React Native. Nader also trains companies to use React Native through his company React Native Training. In this episode, we explore what a developer can and cannot do with React Native, when a developer needs to use native APIs, and some speculation on the future of React Native.
#1445
Jun 25, 2020 · 1 hr 3 min
Traces: Video Recognition with Veronica Yurchuk and Kostyantyn Shysh (Summer Break Repeat)
Originally published October 8, 2019. We are taking a few weeks off. We’ll be back soon with new episodes. Video surveillance impacts human lives every day. On most days, we do not feel the impact of video surveillance. But the effects of video surveillance have tremendous potential. It can be used to solve crimes and find missing children. It can be used to intimidate journalists and empower dictators. Like any piece of technology, video surveillance can be used for good or evil. Video recognition lets us make better use of video feeds. A stream of raw video doesn’t provide much utility if we can’t easily model its contents. Without video recognition, we must have a human sitting in front of the video to manually understand what is going on in that video. Veronica Yurchuk and Kosh Shysh are the founders of Traces.ai, a company building video recognition technology focused on safety, anonymity, and positive usage. They join the show to discuss the field of video analysis, and their vision for how video will shape our lives in the future.
#1444
Jun 24, 2020 · 57 min
Envoy Mobile with Matt Klein (Summer Break Repeat)
Originally published July 25, 2019. We are taking a few weeks off. We’ll be back soon with new episodes. Envoy is an open source edge and service proxy that was originally developed at Lyft. Envoy is often deployed as a sidecar application that runs alongside a service and helps that service by providing features such as routing, rate limiting, telemetry, and security policy. Envoy has gained significant traction in the open source community, and has formed the backbone of popular service mesh projects such as Istio. Envoy has been mostly used as a backend technology, but the potential applications of Envoy include frontend client applications as well. The goal of Envoy is to make the network easier to work with–and the network includes client applications such as mobile apps running on a phone. Envoy Mobile is a network proxy for mobile applications. Envoy Mobile brings many of the benefits of Envoy to the mobile client ecosystem. It provides mobile developers with a library that can simplify or abstract away many of the modern advances that have been made in networking in recent years, such as HTTP2, gRPC, and QUIC. Matt Klein is the creator of Envoy, and he joins the show to discuss Envoy Mobile. Matt describes how the networking challenges of mobile applications are similar to those of backend systems and cloud infrastructure. We discuss the advances in networking technology that Envoy Mobile helps bring to the mobile ecosystem, and also touch on the scalability challenges that Matt is seeing at Lyft.
#1443
Jun 23, 2020 · 1 hr 7 min
Data Intensive Applications with Martin Kleppman (Summer Break Repeat)
Originally published May 2, 2017. We are taking a few weeks off. We’ll be back soon with new episodes. 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 know how to store and cache large video files, and stream them to users quickly. Twitter needs to update user news feeds with a fanout of the president’s latest tweet. These operations are simple with small amounts of data, but become complicated with a high volume of users. Martin Kleppmann is the author of Data Intensive Applications, an O’Reilly book about how to use modern data tools to solve modern data problems. His book includes high-level discussions about architectural strategy, and lower level discussions like how leader election algorithms can create problems for a data intensive application.
#1442
Jun 22, 2020 · 2 hr 16 min
freeCodeCamp with Quincy Larson (Summer Break Repeat)
Originally published December 20, 2019. We are taking a few weeks off. We’ll be back soon with new episodes. freeCodeCamp was started five years ago with the goal of providing free coding education to anyone on the Internet. freeCodeCamp has become the best place to begin learning how to write software. There are many other places that a software engineer should visit on their educational journey, but freeCodeCamp is the best place to start, because it is free, and there are no advertisements. For most people learning to code, the price of that education is important, because they are learning to code to build a new career. It’s also important that a new programmer learns from an unbiased source of information, because an ad-supported environment will educate the new programmer towards products that they might not need. freeCodeCamp has not been easy to build. Building freeCodeCamp has required expertise in software engineering, business, media, and community development. The donation-based business model of freeCodeCamp doesn’t collect very much money. Why would somebody build a non-profit when they could spend their time building a highly profitable software company? Quincy Larson is the founder of freeCodeCamp, and he joins the show for a special episode about his backstory and the journey to building the best place on the Internet for a new programmer to begin.
#1441
Jun 19, 2020 · 1 hr 5 min
Facebook Open Source with Tom Occhino (Summer Break Repeat)
Originally published April 14, 2017. We are taking a few weeks off. We’ll be back soon with new episodes. Facebook’s open source projects include React, GraphQL, and Cassandra. These projects are key pieces of infrastructure used by thousands of developers–including engineers at Facebook itself. These projects are able to gain traction because Facebook takes time to decouple the projects from their internal infrastructure and clean up the code before releasing them into the wild. Facebook has high standards for what they are willing to release. Tom Occhino manages the React team at Facebook and works closely with engineers to determine what projects make sense to open source. In this episode, Preethi Kasireddy interviews Tom about how Facebook thinks about open source–what went right with React, why it makes sense for Facebook to continue to release new open source projects, and how full-time employees at Facebook interact with that open source codebase.
#1439
Jun 18, 2020 · 56 min
Redis with Alvin Richards (Summer Break Repeat)
Originally published October 24, 2019. We are taking a few weeks off. We’ll be back soon with new episodes. Redis is an in-memory database that persists to disk. Redis is commonly used as an object cache for web applications. Applications are composed of caches and databases. A cache typically stores the data in memory, and a database typically stores the data on disk. Memory has significantly faster access times, but is more expensive and is volatile, meaning that if the computer that is holding that piece of data in memory goes offline, the data will be lost. When a user makes a request to load their personal information, the server will try to load that data from a cache. If the cache does not contain the user’s information, the server will go to the database to find that information. Alvin Richards is chief product officer with Redis Labs, and he joins the show to discuss how Redis works. We explore different design patterns for making Redis high availability, or using it as a volatile cache, and we talk through the read and write path for Redis data. Full disclosure: Redis Labs is a sponsor of Software Engineering Daily.
#1438
Jun 17, 2020 · 1 hr 2 min
HTTP with Julia Evans (Summer Break Repeat)
Originally published November 21, 2019. We are taking a few weeks off. We’ll be back soon with new episodes. HTTP is a protocol that allows browsers and web applications to communicate across the Internet. Everyone knows that HTTP is doing some important work, because “HTTP” is at the beginning of most URLs that you enter into your browser. You might be familiar with the request/response model, and HTTP request methods such as GET, PUT, and POST. But unless you have had a reason to learn more about the details of HTTP, you probably don’t know much more than that. Julia Evans is a software engineer and writer who creates Wizard Zines, a series of easy-to-read online magazines that explain technical software topics. Julia’s zines include “Linux Debugging Tools”, “Help! I Have A Manager!”, and recently “HTTP: Learn your browser’s language”. Her zines are a creative, innovative format for describing the world of software engineering while also exploring her own artistic pursuits in writing, design, and illustration. Julia was previously on the show to discuss Ruby profiling, and she returns to the show to discuss HTTP, as well as her creative process and goals with Wizard Zines.
#1437
Jun 16, 2020 · 1 hr 5 min
Stripe Machine Learning Infrastructure with Rob Story and Kelley Rivoire (Summer Break Repeat)
Originally published June 13, 2019. We are taking a few weeks off. We’ll be back soon with new episodes. Machine learning allows software to improve as that software consumes more data. Machine learning is a tool that every software engineer wants to be able to use. Because machine learning is so broadly applicable, software companies want to make the tools more accessible to the developers across the organization. There are many steps that an engineer must go through to use machine learning, and each additional step inhibits the chances that the engineer will actually get their model into production. An engineer who wants to build machine learning into their application needs access to data sets. They need to join those data sets, and load them into a machine (or multiple machines) where their model can be trained. Once the model is trained, the model needs to test on additional data to ensure quality. If the initial model quality is insufficient, the engineer might need to tweak the training parameters. Once a model is accurate enough, the engineer needs to deploy that model. After deployment, the model might need to be updated with new data later on. If the model is processing sensitive or financially relevant data, a provenance process might be necessary to allow for an audit trail of decisions that have been made by the model. Rob Story and Kelley Rivoire are engineers working on machine learning infrastructure at Stripe. After recognizing the difficulties that engineers faced in creating and deploying machine learning models, Stripe engineers built out Railyard, an API for machine learning workloads within the company. Rob and Kelley join the show to discuss data engineering and machine learning at Stripe, and their work on Railyard.
#1436
Jun 15, 2020 · 59 min
Architects of Intelligence with Martin Ford Holiday Repeat
Originally published January 31, 2019 Artificial intelligence is reshaping every aspect of our lives, from transportation to agriculture to dating. Someday, we may even create a superintelligence–a computer system that is demonstrably smarter than humans. But there is widespread disagreement on how soon we could build a superintelligence. There is not even a broad consensus on how we can define the term “intelligence”. Information technology is improving so rapidly we are losing the ability to forecast the near future. Even the most well-informed politicians and business people are constantly surprised by technological changes, and the downstream impact on society. Today, the most accurate guidance on the pace of technology comes from the scientists and the engineers who are building the tools of our future. Martin Ford is a computer engineer and the author of Architects of Intelligence, a new book of interviews with the top researchers in artificial intelligence. His interviewees include Jeff Dean, Andrew Ng, Demis Hassabis, Ian Goodfellow, and Ray Kurzweil. Architects of Intelligence is a privileged look at how AI is developing. Martin Ford surveys these different AI experts with similar questions. How will China’s adoption of AI differ from that of the US? What is the difference between the human brain and that of a computer? What are the low-hanging fruit applications of AI that we have yet to build? Martin joins the show to talk about his new book. In our conversation, Martin synthesizes ideas from these different researchers, and describes the key areas of disagreement from across the field.
#1435
Jun 12, 2020 · 54 min
Cruise Simulation with Tom Boyd
Cruise is an autonomous car company with a development cycle that is highly dependent on testing its cars–both in the wild and in simulation. The testing cycle typically requires cars to drive around gathering data, and that data to subsequently be integrated into a simulated system called Matrix. With COVID-19, the ability to run tests in the wild has been severely dampened. Cruise cannot put so many cars on the road, and thus has had to shift much of its testing procedures to rely more heavily on the simulations. Therefore, the simulated environments must be made very accurate, including the autonomous agents such as pedestrians and cars. Tom Boyd is VP of Simulation at Cruise. He joins the show to talk about the testing workflow at Cruise, how the company builds simulation-based infrastructure, and his work managing simulation at the company.
#1434
Jun 11, 2020 · 48 min
Grafana with Torkel Ödegaard
Grafana is an open source visualization and monitoring tool that is used for creating dashboards and charting time series data. Grafana is used by thousands of companies to monitor their infrastructure. It is a popular component in monitoring stacks, and is often used together with Prometheus, ElasticSearch, MySQL, and other data sources. The engineering complexities around building Grafana involve the large number of integrations, the highly configurable ReactJS frontend, and the ability to query and display large data sets. Grafana also must be deployable to cloud and on-prem environments. Torkel Ödegaard is a co-founder of Grafana Labs, and joins the show to talk about his work on the open source project and the company he is building around it.
#1433
Jun 10, 2020 · 1 hr 1 min
Apache Airflow with Maxime Beauchemin, Vikram Koka, and Ash Berlin-Taylor
Apache Airflow was released in 2015, introducing the first popular open source solution to data pipeline orchestration. Since that time, Airflow has been widely adopted for dependency-based data workflows. A developer might orchestrate a pipeline with hundreds of tasks, with dependencies between jobs in Spark, Hadoop, and Snowflake. Since Airflow’s creation, it has powered the data infrastructure at companies like Airbnb, Netflix, and Lyft. It has also been at the center of Astronomer, a startup that helps enterprises build infrastructure around Airflow. Airflow is used to construct DAGs–directed acyclic graphs for managing data workflows. Maxime Beauchemin is the creator of Airflow. Vikram Koka and Ash Berlin-Taylor work at Astronomer. They join the show to talk about the state of Airflow–the purpose of the project, its use cases, and open source ecosystem.

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