News & Media

REST, or Representational State Transfer, is the ubiquitous architectural style that answers the pivotal question: how will web servers and clients communicate? Of all the acronyms floating around the world of software engineering, REST is one of the most common. It is also one of the most frequently misunderstood. This article offers a quick guide to REST in both theory and practice. In other words, we’ll look at both the theory of REST and how it is actually implemented, which is mostly in the form of RESTful APIs. REST in theory Building software to be distributed on the Internet entails an inherent degree of complexity. The TCP/IP and HTTP stack gives us a basic mechanism for exchanging data over the wire, but the protocols end there. Software developers have had to devise our own higher-level approaches for organizing how resources will be packaged and distributed via web applications. To read this article in full, please click here

Microsoft has introduced a while! keyword with its open source F# language, providing a refined approach to loops in computation expressions.This keyword, spoken as “while bang,” is intended to minimize boilerplate, boost clarity, and enhance expressiveness, Microsoft said in a blog post on September 20. With while!, specifying an asynchronous condition in loops now is feasible. Microsoft cites the elimination of a mutant variable, a reduction in total lines of code, and a decrease in overall cyclomatic complexity as a result of while!. The while! construct does not require a builder method but instead invokes .Bind in the same manner as let! does; so there is no additional work needed when authoring new computation expressions.  Constructs are composable and can be nested.To read this article in full, please click here

The rush to generative AI is driving unexpected spending. It’s no longer considered optional to have generative AI system development and deployment plans; it’s a priority for boards and executive leadership. Thus, the question comes up quickly of how to pay for it, cloud or no cloud.The numbers are scary to someone who has created these budgets in the past. IT executives now expect 2023 generative AI budgets to be 3.4 times greater than anticipated. However, only 15% of tech execs expect to fund this uptick with net-new spending.To read this article in full, please click here

An API gateway provides a mechanism through which the user interface components of an application can connect to back-end services to exchange data. This article introduces the concept of an API gateway, discusses the differences between an API gateway and a reverse proxy, and illustrates how you can implement an API gateway using YARP (Yet Another Reverse Proxy) in ASP.NET Core.In this article, we’ll make use of the microservices we created in my previous article. To use the code examples provided in this article, you should have Visual Studio 2022 installed in your system. If you don’t already have a copy, you can download Visual Studio 2022 here.To read this article in full, please click here

Java Development Kit (JDK) 21 officially arrived September 19, 2023. Next up is JDK 22, or Java 22, due March 19, 2024. A range of capabilities from structured concurrency to computed constants and a class-file API could make it into this future release.JDK 22 is set to be published as a short-term release by Oracle with six months of support, although other organizations could offer longer support if they choose. Although the OpenJDK webpage for JDK 22 doesn’t lists any features yet, obvious candidates include features previewed in JDK 21, such as structured concurrency for concurrent programming. Another possibility is a feature that was initially slotted for JDK 21 but was taken out: the Shenandoah garbage collector, a low-pause time collector. Early-access builds of JDK 22 are available at jdk.java.net. Other candidates for possible inclusion in JDK 22 include:To read this article in full, please click here

Microsoft has long intended to make Windows the place for developers. Its intention is shown in both software and hardware as the company aims to deliver tools that make it possible to build code wherever and for whatever.One recent example: the specifications of the second version of its flagship Surface Laptop Studio. Not only does this latest version include an Intel NPU for AI development, it also doubles the system memory from 32GB to 64GB for the top-end version of the laptop. That gives you plenty of resources for building end-to-end applications that cross from cloud to mobile and beyond.Having a lot of memory simplifies running multiple operating systems at the same time, allowing you to build cross-platform development toolchains that don’t leave your PC and take advantage of both the Windows Subsystem for Linux and the Windows Subsystem for Android. Running on top of Windows’ Krypton hypervisor, both subsystems offer a way to build and test code wherever you’re working without having to spin up additional resources or plug in extra hardware. They’re also both under continuous development, regularly adding new features and tools.To read this article in full, please click here

After adding vector search to its NoSQL Atlas database-as-a-service (DBaaS) in June, MongoDB is adding new generative AI features to a few tools in order to further boost developer productivity.The new features have been added to MongoDB’s Relational Migrator, Compass, Atlas Charts tools, and its Documentation interface.In its Documentation interface, MongoDB is adding an AI-powered chatbot that will allow developers to ask questions and receive answers about MongoDB’s products and services, in addition to providing troubleshooting support during software development.To read this article in full, please click here

Node.js went from an out-of-the-box idea to a mainstay in record time. Today, it’s a de facto standard for creating web applications, systems software, and more. Server-side Node frameworks like Express, build-chain tools like Webpack, and a host of utilities for every need make Node a hugely popular way to leverage the power and expressiveness of JavaScript on the back end. Although Node now has competition from Deno and Bun, it remains the flagship JavaScript platform on the server.To read this article in full, please click here

The current state of IDEs built for Python is an embarrassment of riches. Seven products made the cut for our big Python IDE rundown, but many more were worth noting. Available IDEs range from sophisticated efforts that provide a full-blown development system to modest projects suited to first-time Pythonistas. Here are four more Python IDEs, from the minimal to the maximal, that you probably want on your radar.Eric7 Like Python’s own native IDE IDLE, Eric7 is a Python IDE written in Python, although it uses the Qt6 UI framework to provide a far more sophisticated UI than IDLE. Because the source is all Python, that makes it quite hackable for Python developers who want control over their IDE from the inside out.To read this article in full, please click here

Vercel has released the Next.js 13.5 web framework, which features faster startups and refreshes and lower memory usage.Unveiled September 19, version 13.5 improves local server startup time by 22%, letting developers iterate faster with the App Router and Pages Router. Since Next.js 13.4 was announced in May, the Vercel team has been focused on improving the performance and reliability of App Router applications.Also featured in the Next.js 13.5 release is faster HMR (Hot Module Replacement, more commonly known as Fast Refresh). The new release is reported to yield 29% faster iterations when saving changes. Memory usage was reduced by 40 percent and more than 438 bugs were patched for this release. Version 13.5 also optimizes package imports, improving both local development performance and production cold starts when using large icon or component libraries, or other dependencies that re-export hundreds or thousands of modules.To read this article in full, please click here

Chatbots like ChatGPT, Claude.ai, and phind can be quite helpful, but you might not always want your questions or sensitive data handled by an external application. That’s especially true on platforms where your interactions may be reviewed by humans and otherwise used to help train future models.One solution is to download a large language model (LLM) and run it on your own machine. That way, an outside company never has access to your data. This is also a quick option to try some new specialty models such as Meta’s recently announced Code Llama family of models, which are tuned for coding, and SeamlessM4T, aimed at text-to-speech and language translations.To read this article in full, please click here

Managed Apache Kafka service provider Confluent has launched  a new initiative, dubbed Data Streaming for AI, in order to help enterprises develop applications based on real-time data, including generative AI  use cases.To read this article in full, please click here

Angular 17, an upgrade to Google’s popular TypeScript-based web development framework, is due in November with template features including a new built-in syntax for control flow and deferrable loading.A September 25 blog post from Alex Rickabaugh of the Angular team covered the planned capabilities, with declarative control flow set to add the functionality of the NgIf, NgFor, and NgSwitch directives into the framework itself. Deferrable loading, meanwhile, allows templates to load dependencies lazily in response to trigger conditions; the team described the change as the most significant made to Angular templates. Work continues on finishing up these features. Angular 17 will use a syntax dubbed @-syntax for control flow and deferrable views.To read this article in full, please click here

The serverless database continues to gain traction across the industry, generating a lot of hype along the way. And why not?The idea that an application developer starting on a new project can provision a database, not worry about sizing compute and storage, or fine-tuning database configurations, and really only needs a general sense of workload pattern and transaction volume to approximate cost is a very enticing proposition. Plus, some might even see very strong potential to reduce the TCO of the database system.As the theme around cloud cost management continues to percolate, the elastic pay-as-you-go model makes serverless even more attractive—if the app and customers behave.To read this article in full, please click here

You’re the CIO at ABC Inc., a fictional rapidly scaling tech startup. In 2023, you implemented a new cloud finops system to streamline the management of its extensive cloud infrastructures. In 2024, the system unveiled several previously unknown technical debts. You’ve been summoned to a meeting with the CEO to address these issues.The finops system has determined that this technical debt has led to more than $20 million in lost revenue to the business. This includes general inefficiencies, such as overprovisioning public cloud storage systems, as well as more strategic problems, such as the need for the system to provide the agility and scale to support moving into new markets and other innovations.To read this article in full, please click here

Deno runtime proponents are touting the simplification of software development via the use of Jupyter Notebook in Deno 1.37. This latest version of the runtime for JavaScript, TypeScript, and WebAssembly also features improved editor support for Visual Studio Code.To read this article in full, please click here

The first computer vision use cases in the 1950s analyzed typed versus handwritten text. Early commercial applications focused on single images, including optical character recognition, image segmentation, and object detection. Pioneering work on facial recognition began in the 1960s, and big tech companies began launching capabilities around 2010.The computer vision market size was estimated at $14 billion in 2022 and is expected to grow at a compound annual growth rate of 19.6% from 2023 to 2030. While there are many new computer vision breakthroughs and startups, its market size is small compared to other AI technologies. Generative AI, for example, is estimated to become a $1.3 trillion market by 2032.To read this article in full, please click here

In the technology world, the latter half of the 2010s was mostly about slight tweaks, not sweeping changes: Smartphones got slightly better, and computer processing somewhat improved. Then OpenAI unveiled its ChatGPT in 2022 to the public, and—seemingly all at once—we were in a qualitatively new era. The predictions have been inescapable in recent months. Futurists warn us that AI will radically overhaul everything from medicine to entertainment to education and beyond. In this instance, the futurists might be closer to the truth. Play with ChatGPT for just a few minutes, and it is impossible not to feel that something massive is on the horizon. To read this article in full, please click here

In yet another installment of “everyone is doing it, but no one knows how,” a recent NewVantage Partners survey found that while 93.9% of executives surveyed expect to increase their data investments in 2023, just 23.9% of organizations characterize themselves as data-driven. Where is all that investment going, if not to change the way their companies operate? What’s stopping these executives from imposing this vision of a glorious data future on their companies?People. The problem is always people. Of these same executives, 79% cite cultural issues as the biggest impediment to embracing a data-driven future. It turns out to be easy to say “data-driven” but much harder to implement because people ultimately animate a business, not data. The key, then, is to ensure that data enables and augments people rather than replaces them.To read this article in full, please click here

37Signals, led by CTO David Heinemeier Hansson, implemented a cloud repatriation plan that has already saved them $1 million. Previously, the company spent $3.2 million annually on cloud services. They viewed that as being too much. Their repatriation project invested $600,000 in eight servers hosted by Deft. Hansson now projects that the plan can save $10 million over five years. That’s money they can put back into the business directly, investing in innovations and digital transformation projects. As a result, their cloud spending has decreased by 60%, going from around $180,000 to less than $80,000 per month. Hansson expects another significant drop in expenditures. Despite managing their hardware, the ops team size has stayed the same.To read this article in full, please click here