Info World

In its latest The State of Cloud Cost in 2024 report, CloudZero illuminates the serious implications of cloud cost management and its effect on business stability and job security. The conclusions are interesting.

CloudZero’s survey, which drew insights from 1,000 finance and engineering professionals, underscored a crucial element in cloud cost management: the pivotal role of engineering teams. These are not just the “nerds” who operate the technology but key players who can significantly influence cost outcomes.

According to the survey, 81% of respondents indicated that cloud costs were effectively managed and predictable when engineers managed them. This shows a positive relationship between engineering ownership and better cloud cost management. This shift in perception has significant business implications for effective cloud cost management.

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Several online news outlets report that Google laid off its entire Python language team. However, Google denied that the layoffs were company-wide when asked about the fate of the team.

Reports of the Python team’s dismissal have shown up in Reddit, Hacker News, and social.coop. “Google’s Python team was a small team, most of which were also on the Python steering council or core Python developers,” one commenter said in Hacker News. “These people had decades of experience in Python. Their knowledge and community connections [are] irreplaceable.”

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GitHub is offering a technical preview of GitHub Copilot Workspace, which provides a developer environment based on the GitHub Copilot AI-powered programming assistant.

The GitHub Copilot Workspace preview was introduced April 29. Described as a Copilot-native development environment for everyday tasks, GitHub Copilot Workspace allows developers “to brainstorm, plan, build, test, and run code in natural language,” GitHub said. GitHub Copilot Chat, the natural language assistant, was introduced in November.

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At the end of March 2024, Mike Stonebraker announced in a blog post the release of DBOS Cloud, “a transactional serverless computing platform, made possible by a revolutionary new operating system, DBOS, that implements OS services on top of a distributed database.” That sounds odd, to put it mildly, but it makes more sense when you read the origin story:

The idea for DBOS (DataBase oriented Operating System) originated 3 years ago with my realization that the state an operating system must maintain (files, processes, threads, messages, etc.) has increased in size by about 6 orders of magnitude since I began using Unix on a PDP-11/40 in 1973. As such, storing OS state is a database problem. Also, Linux is legacy code at the present time and is having difficulty making forward progress. For example there is no multi-node version of Linux, requiring people to run an orchestrator such as Kubernetes. When I heard a talk by Matei Zaharia in which he said Databricks could not use traditional OS scheduling technology at the scale they were running and had turned to a DBMS solution instead, it was clear that it was time to move the DBMS into the kernel and build a new operating system.”

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In the rush to embrace coding assistants like Amazon CodeWhisperer to generate new code for developers, we haven’t spent much time asking if that code is any good. By some measures, the answer is clearly “no.” According to a GitClear analysis, “Code generated during 2023 … resembles [that of] an itinerant contributor,” likely caused by increased use of coding assistants.

This is not to say that coding assistants are bad. They can be incredibly helpful. The issue is we need to invest more time figuring out ways to apply generative AI to tasks like code refactoring now, as covered in a recent Thoughtworks interview. The good news? AI can help, but perhaps not always in the ways we expect.

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A few weeks ago, Redis changed its license from the Open Source Initiative (OSI)-approved BSD 3-Clause license to the Redis Source Available License (RSALv2). This move echoed Elastic’s earlier license change for Elasticsearch, which switched from the Apache License 2.0 to the Elastic License (ELv2). Then, just as OpenSearch was forked from open-source Elasticsearch, Valkey has been forked from open-source Redis.

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React 19, the latest version of Meta’s JavaScript library for rendering user interfaces, is now available in beta. The update introduces features such as async functions in transitions and the ability to access ref as a prop for function components.

The React 19 beta was unveiled April 25. A React 19 beta upgrade guide has been published.

React 19 adds support for using async functions in transitions to handle pending states, forms, errors, and optimistic updates automatically. Functions that use async transitions are called Actions. By building on top of Actions, React 19 introduces useOptimistic to manage optimistic updates and a new hook, React.useActionState, to handle common cases for Actions. Actions also are integrated with new <form> features for react-dom in React 19.

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TypeScript 5.5, the latest version of Microsoft’s strongly typed JavaScript variant, has arrived in beta with improvements ranging from performance and size optimizations to regular expression checking.

The TypeScript 5.5 beta was introduced April 25 and can be accessed through Nuget or the following command: npm -D typescript@beta. A release candidate is due June 4, and the final release is planned for June 18.

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In a breakthrough for the healthcare industry, researchers have unveiled Meditron, a suite of open-source large language models (LLMs), specifically designed to assist medical professionals.

Jointly developed by researchers from École Polytechnique Fédérale de Lausanne (EPFL) and Yale School of Medicine, and supported by the International Committee of the Red Cross (ICRC), the LLM is built upon the Meta Llama2 platform and trained on “carefully curated, high-quality medical data sources,” Meta said in a blog post.

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Back in the early days of the cloud, I had a nice little business taking enterprise applications and reengineering them so they could be delivered as software-as-a-service cloud assets. Many enterprises believed that their custom application, which provided value by addressing a niche need, could be resold as a SaaS service and become another source of income.

I saw a tire company, a healthcare company, a bank, and even a bail-bond management company attempt to become cloud players before infrastructure as a service was a thing. Sometimes it worked out.

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Canonical has released Ubuntu 24.04 LTS, aka “Noble Numbat,” a new Long Term Support release of the popular Linux distribution that brings performance enhancements and toolchain updates for developers.

Announced April 25 and downloadable from ubuntu.com, Ubuntu 24.04 LTS offers Linux 6.8 kernel capabilities with improved syscall performance, nested KVM (Kernel-based Virtual Machine) support on ppc64el (IBM PowerPC), and access to the new beachefs file system. Ubuntu 24.04 LTS has merged low-latency kernel features into the default kernel, reducing kernel task scheduling delays, Canonical said. The release also enables frame pointers by default on 64-bit architectures, giving performance engineers access to accurate flame graphs when systems are profiled for troubleshooting and optimization. Frame pointers offer more complete CPU profiling and off-CPU profiling, according to Intel.

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Microsoft has introduced version 8 of the .NET MAUI (Multi-platform App UI) Community Toolkit, featuring TouchBehavior, for interacting with visual elements in an application based on touch, mouse clicks, and hover events.

The update was introduced April 24. Instructions for getting started with the toolkit are available on GitHub.

With the new release, the TouchBehavior implementation enables customization of different visual properties on the VisualElement it is attached to, such as the background color, opacity, scale, and rotation. TouchBehavior also makes it possible to implement long-press touch gestures and enables invoking of code whenever a user presses any visual element in an app. TouchBehavior formerly was known as TouchEffect in the Xamarin Community Toolkit in the Xamarin.Forms app.

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Chatbots like ChatGPT, Claude.ai, and Meta.ai 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 new Llama 3, which is tuned for coding, and SeamlessM4T, aimed at text-to-speech and language translations.

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Platform engineering is becoming a compelling concept for enterprises, as they’re devoting increasingly large amounts of resources into cloud-native application development. It doesn’t matter if you’re using your own Kubernetes instances in your data centers, or working with managed environments in public clouds, you’re going to need to understand how they’re operating, taking advantage of a new generation of observability and security tools.

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Buzz is building around the idea that it’s time to claw back our cloud services and once more rebuild the company data center. Repatriation. It’s the act of moving work out of cloud and back to on-premises or self-managed hardware. And the primary justification for this movement is straightforward, especially in a time of economic downturn. Save money by not using AWS, Azure, or the other cloud hosting services. Save money by building and managing your own infrastructure.

Since an Andreesen Horowitz post catapulted this idea into the spotlight a couple of years ago, it seems to be gaining momentum. 37Signals, makers of Basecamp and Hey (a for-pay webmail service), blog regularly about how they repatriated. And a recent report suggested that of all those talking about a move back to self-hosting, the primary reason was financial: 45% said it’s because of cost.

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Node.js 22, the latest version of the popular JavaScript runtime, has arrived, featuring require() support for ECMAScript modules, an improved WebSocket client, and an updated version of the Google V8 JavaScript engine.

Announced April 24, version 22 of the event-driven, asynchronous runtime can be downloaded from Nodejs.org. The release adds require() support for synchronous ECMAScript module graphs under the flag: --experimental-require-module. If this flag is enabled and the ES module meets a couple of requirements, require() will load the requested module. Additionally, Node.js 22 includes an experimental feature for the execution of scripts from package.json with the CLI flag: node --run <script-in-package-json>.

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Java Development Kit (JDK) 23, the next planned version of standard Java, is off and running, with five features now scheduled for the release. The latest addition is making the generational mode of the Z Garbage Collector the default mode.

Due September 17, JDK 23 also will include a vector API, which will be incubated for the eighth time, a second preview of stream gatherers, a second preview of a class-file API, and a preview of primitive types in patterns, instanceof, and switch. Early access builds for JDK 23 can be accessed from jdk.java.net.

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Cloud-based data warehouse company Snowflake has developed an open-source large language model (LLM), Arctic, to take on the likes of Meta’s Llama 3, Mistral’s family of models, xAI’s Grok-1, and Databricks’ DBRX.

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OpenAI, known for its large language model ChatGPT, is making a strong push for the enterprise market. In what could intensify competition among enterprise AI players, the company announced a slew of new features designed to give businesses more control, enhance security, and offer cost-effective options when integrating OpenAI’s AI technologies in their operations.

“We’re deepening our support for enterprises with new features that are useful for both large businesses and any developers who are scaling quickly on our platform,” OpenAI said.

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WebAssembly runtime maker Wasmer has unveiled py2wasm, a Python-to-WebAssembly compiler that transforms Python programs to the WebAssembly (aka Wasm) binary instruction format.

Using a fork of the Nuitka Python compiler, py2wasm converts Python programs to Wasm, allowing them to run without interpreter overhead. Introduced April 18, py2wasm addresses a situation in which the performance of Python programs in WebAssembly has been less than ideal, Wasmer founder and CEO Syrus Akbary wrote in a blog post. Akbary said that py2wasm gets about 70% of native Python speed, and is about 2.5x to 3x faster than the Python interpreter.

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