Software Engineering Daily

Software Engineering Daily

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  • Typical duration

    54 min

    per episode

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Software Engineering Daily episodes

  • Remote Team Management with Ryan Chartrand
    Remote engineering work makes some elements of software development harder, and some elements easier. With Slack and email, communication becomes more clear cut. Project management tools lay out the responsibilities and deliverables of each person. GitHub centralizes and defines the roles of developers. On the other hand, remote work subtracts the role of nuanced conversation.
    59 min
  • Sorbet: Typed Ruby with Dmitry Petrashko
    Programming languages are dynamically typed or statically typed. In a dynamically typed language, the programmer does not need to declare if a variable is an integer, string, or other type. In a statically typed language, the developer must declare the type of the variable upfront, so that the compiler can take advantage of that information.
    57 min
  • Datomic Architecture with Marshall Thompson
    Datomic is a database system based on an append-only record keeping system. Datomic users can query the complete history of the database, and Datomic has ACID transactional support. The data within Datomic is stored in an underlying database system such as Cassandra or Postgres. The database is written in Clojure, and was co-authored by the
    1 hr 4 min
  • ClickUp Engineering with Zeb Evans and Alex Yurkowski
    Over the last fifteen years, there has been a massive increase in the number of new software tools. This is true at the infrastructure layer: there are more databases, more cloud providers, and more open-source projects. And it’s also true at a higher level: there are more APIs, project management systems, and productivity tools. ClickUp
    1 hr 6 min
  • Pulumi: Infrastructure as Code with Joe Duffy
    Infrastructure-as-code allows developers to use programming languages to define the architecture of their software deployments, including servers, load balancers, and databases.  There have been several generations of infrastructure-as-code tools. Systems such as Chef, Puppet, Salt, and Ansible provided a domain-specific imperative scripting language that became popular along with the early growth of Amazon Web Services.
    1 hr
  • Infrastructure Investing with Vivek Saraswat
    Software investing requires a deep understanding of the market, and an ability to predict what changes might occur in the near future. At the level of core infrastructure, software investing is particularly difficult. Databases, virtualization, and large scale data processing tools are all complicated, highly competitive areas. As the software world has matured, it has
    1 hr 23 min
  • Sisu Data with Peter Bailis
    A high volume of data can contain a high volume of useful information. That fact is well understood by the software world. Unfortunately, it is not a simple process to surface useful information from this high volume of data. A human analyst needs to understand the business, formulate a question, and determine what metrics could
    1 hr
  • Location Data with Ryan Fox Squire
    Physical places have a large amount of latent data. Pick any location on a map, and think about all of the questions you could ask about that location. What businesses are at that location? How many cars pass through it? What is the soil composition? How much is the land on that location worth? The
    57 min
  • Flyte: Lyft Data Processing Platform with Allyson Gale and Ketan Umare
    Lyft is a ridesharing company that generates a high volume of data every day.  This data includes ride history, pricing information, mapping, routing, and financial transactions. The data is stored across a variety of different databases, data lakes, and queueing systems, and is processed at scale in order to generate machine learning models, reports, and
    1 hr 2 min
  • Cloud Investing with Danel Dayan
    Cloud computing caused a fundamental economic shift in how software is built. Before the cloud, businesses needed to buy physical servers in order to operate. There was an up-front cost that often amounted to tens of thousands of dollars required to pay for these servers.  Cloud computing changed the up-front capital expense to an ongoing
    1 hr 15 min

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