Software Engineering Daily

The incredible advances in machine learning research in recent years often take time to propagate out into usage in the field. One reason for this is that such “state-of-the-art” results for machine learning performance rely on the use of handwritten, idiosyncratic optimizations for specific hardware models or operating contexts. When developers are building ML-powered systems

A data-driven organization collects a wide variety of data to help in strategic decision-making. The cost of storing large amounts and variety of data has dropped dramatically in the last two decades, but too much unstructured data may not improve decision-making, and can even lead to “analysis paralysis.” Organizations react by extracting the most important,

Open source software is software distributed along with its source code, using a permissive license that allows anyone to view, use, or modify it. The term “open source” also refers more broadly to a philosophy of technology development which prioritizes transparency and community development of a project. Typically, development is managed by a governing body,

Video calling over the internet has experienced explosive growth in the last decade. In 2010, surveys estimated that around 1 in 5 Americans had tried online video calling for any reason. By May of 2020, that number had nearly tripled. A significant factor in the growth of video calling has been an open-source project called

Cilium is open-source software built to provide improved networking and security controls for Linux systems operating in containerized environments along with technologies like Kubernetes. In a containerized environment, traditional Layer 3 and Layer 4 networking and security controls based on IP addresses and ports, like firewalls, can be difficult to operate at scale because of

In a distributed application, observability is key to handling incidents and building better, more stable software. Legacy monitoring methods were built to respond to predictable failure modes, and to aggregate high-level data like access speed, connectivity, and downtime. Observability, on the other hand, is a measure of how well you can infer the internal state

Embedded Software Engineering is the practice of building software that controls embedded systems- that is, machines or devices other than standard computers. Embedded systems appear in a variety of applications, from small microcontrollers, to consumer electronics, to large-scale machines such as cars, airplanes, and machine tools.  iRobot is a consumer robotics company that applies embedded

Security is more important than ever, especially in regulated fields such as healthcare and financial services. Developers working in highly regulated industries often spend considerable time building tooling to help improve compliance and pass security audits. While the core of many security workflows is similar, each industry and each organization may have its own idiosyncratic

Microservices are built to scale. But as a microservices-based system grows, so does the operational overhead to manage it. Even the most senior engineers can’t be familiar with every detail of dozens- perhaps hundreds- of services. While smaller teams may track information about their microservices via spreadsheets, wikis, or other more traditional documentation, these methods

Reinforcement learning is a paradigm in machine learning that uses incentives- or “reinforcement”- to drive learning. The learner is conceptualized as an intelligent agent working within a system of rewards and penalties in order to solve a novel problem. The agent is designed to maximize rewards while pursuing a solution by trial-and-error.  Programming a system