Software Engineering Daily

A self-driving car needs to be able to quickly respond to changes in driving conditions. A factory needs to be able to quickly respond to changes in workplace safety. For these kinds of applications, we need processing power closer to the user of the application. If we put all of our application logic in the cloud, we will have to make a network round trip for every request. Servers inContinue reading...

A data-driven organization is more efficient because the company can learn what to focus on. In this episode, Edaena Salinas from The Women in Tech Show interviews Rya Sciban, Product Manager at Periscope Data, who explains the needs of data teams in an organization. We talked about what data analysis is and how this changes as the amount of data grows. Rya explained what analytics clusters are and effective ways ofContinue reading...

Deep learning allows engineers to build models that can make decisions based on training data. These models improve over time using stochastic gradient descent. When a model gets big enough, the training must be broken up across multiple machines. Two strategies for doing this are “model parallelism” which divides the model across machines and “data parallelism” which divides the data across multiple copies of the model. Distributed deep learning bringsContinue reading...

Modern architectures often consist of containers that run services. Those containers scale up and down depending on the demand for the services. These large software systems often use a technique known as event sourcing, where every change to the system is kept in an event log. When an event on the log is processed, several different data stores might be updated in response. In these architectures, containers are interacting withContinue reading...

Kubernetes is an orchestration system for managing containers. Since it was open sourced by Google, Kubernetes has created a wave of innovation in the infrastructure technology space. Another recent innovation has been the “serverless” execution tools–such as AWS Lambda and Google Cloud Functions. Serverless execution, otherwise known as functions-as-a-service, allows a developer to execute code against cloud servers without specifying which cloud servers they are executing on. Serverless execution isContinue reading...

Microsoft’s past is full of stories. It’s early period of corporate domination in the 1990s was followed by a period of government antitrust scrutiny, and a period of unsure product direction. Today, Microsoft’s focus on cloud has allowed the company to regain its footing with a clear trajectory for growth. Since 2002, Richard Campbell has chronicled the Microsoft developer community as co-host of .NET Rocks!, a podcast that was originallyContinue reading...

Kubernetes makes it easier for engineering teams to manage their distributed systems architecture. But it’s still not simple to deploy and operate a Kubernetes cluster. Google Container Engine (GKE) is a managed control plane for Kubernetes. Just as developers can use Google App Engine to easily deploy monolithic apps against a platform as a service, we can use Google Container Engine to deploy microservices against a platform as a service.Continue reading...

Engineers have plenty to be skeptical about. We look to data sets to give us something resembling objective truth. Some areas of research have so many variables that it is hard to isolate facts. Kyle Polich hosts the popular data science show Data Skeptic, where he examines problems and solutions around data, and he is one of the guests today in our round table discussion. There are some big unansweredContinue reading...

DNS stands for domain name system. This is the naming system that maps the entire internet. It associates information with domain names. More specifically, DNS specifies mappings between numerical IP addresses and domain names. Most engineers know these basic facts about DNS, but they may not know how much engineering a complex company like Etsy or Zappos puts into their DNS configuration. Dynamic DNS allows for intelligent response, so thatContinue reading...

Video object segmentation allows computer vision to identify objects as they move through space in a video. The DAVIS challenge is a contest among machine learning researchers working off of a shared dataset of annotated videos. The organizers of the DAVIS challenge join the show today to explain how video object segmentation models are trained and how different competitors take part in the DAVIS challenge. A good companion to thisContinue reading...