# debugging Published articles for debugging. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Libreboot 20140729 release DevFeed: [Libreboot 20140729 release]() Original publisher: [Read original article]() Author: Leah Rowe Published: 2026-09-17T04:32:50.666044Z Content type: release Language: en Sources: [News about Libreboot releases and development]() Topics: [libreboot](), [Documentation](), [debugging]() Tags: [apple](), [article](), [bios](), [canoeboot](), [compatibility](), [coreboot](), [debugging](), [documentation](), [free-software](), [intel](), [libre](), [libreboot](), [opensource](), [release](), [uefi]() ### AI overview Libreboot 20140729 is a fourth beta release with improved security documentation, confirmed MacBook2,1 testing, a script and instructions for flashing while Apple EFI firmware is running, a smaller source archive, Italian QWERTY GRUB ROMs, and an Intel register utility for debugging LCD panel compatibility. ### Source excerpt Article: Libreboot 20140729 release Web link: https://libreboot.org/news/libreboot20140729.html ## Libreboot 20140309 release DevFeed: [Libreboot 20140309 release]() Original publisher: [Read original article]() Author: Leah Rowe Published: 2026-09-17T04:32:50.666044Z Content type: release Language: en Sources: [News about Libreboot releases and development]() Topics: [libreboot](), [boot]() Tags: [article](), [battery](), [bios](), [boot](), [canoeboot](), [coreboot](), [crypto](), [debugging](), [free-software](), [libre](), [libreboot](), [opensource](), [processor](), [release](), [uefi]() ### AI overview The Libreboot 20140309 release reduces boot time, adds cryptographic and cryptodisk modules to GRUB, includes cbfstool in binary archives, and provides separate ROM images for faster booting or debugging. It also describes changes intended to reduce battery impact. ### Source excerpt Article: Libreboot 20140309 release Web link: https://libreboot.org/news/libreboot20140309.html ## Logpoints Walkthrough DevFeed: [Logpoints Walkthrough]() Original publisher: [Read original article]() Author: Igor Kulakov Published: 2026-09-16T14:14:04Z Content type: tutorial Language: en Sources: [The JetBrains Blog]() Topics: [IntelliJ IDEA](), [debug](), [debugging](), [gRPC](), [Java](), [2026.2]() Tags: [2026-2](), [bug](), [client](), [command-line](), [debug](), [debugger](), [debugging](), [debugging-tools](), [idea](), [intellij](), [intellij-idea](), [java](), [kotlin](), [logpoints]() ### AI overview This walkthrough explains how to use logpoints in IntelliJ IDEA to investigate a bug in a gRPC client-server example that returns incorrect discount values. It covers reproducing the issue, attaching the debugger to the server, and observing program behavior without suspending execution, including improvements in IntelliJ IDEA 2026.2. ### Source excerpt Modern development tools, especially IntelliJ IDEA, have such comprehensive debugging support that for virtually any niche use case, there is a specialized tool for the job. This can make it hard to know where to begin. If you are new to debugging tools and want the biggest return on your learning investment, the best feature [...] ## New data pipeline management platform at Khan Academy DevFeed: [New data pipeline management platform at Khan Academy]() Original publisher: [Read original article]() Author: Khan Academy Published: 2018-04-30T22:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [data](), [DataOps](), [systems]() Tags: [batch](), [bigquery](), [cloud-dataflow](), [data](), [data-pipelines](), [debugging](), [engineering](), [infrastructure](), [news](), [pipeline](), [scheduling]() ### AI overview Khan Academy developed Khanalytics to manage its growing collection of data pipelines. The platform provides a sandboxed environment for batch jobs, a web interface, automatic parallelization, centralized logs, and pipeline scheduling with dependencies. ### Source excerpt By Ragini Gupta Data is very crucial to Khan Academy and is itself an internal product for the ... Read more ## How vagrant-libvirt Plugin Deals with Duplicate Subnets DevFeed: [How vagrant-libvirt Plugin Deals with Duplicate Subnets]() Original publisher: [Read original article]() Published: 2026-09-16T06:27:00Z Content type: tutorial Language: en Sources: [ipSpace.net blog]() Topics: [Vagrant](), [virtual machines](), [Linux](), [Ubuntu]() Tags: [debugging](), [linux](), [vagrant](), [virtual-machines](), [virtualization]() ### AI overview The article explains that vagrant-libvirt can fail when an existing libvirt virtual network has the same IP subnet as the desired management network but a different name. It identifies the resulting network-name mismatch and reports that correcting the network definition in the Vagrantfile resolves the problem. ### Source excerpt TL&DR: Badly. The vagrant-libvirt plugin mysteriously crashes when an existing virtual network (with a different libvirt name) uses the same IP subnet as the desired management network. Background: netlab is using the vagrant-libvirt plugin to manage libvirt/KVM virtual machines with Vagrant. As I already have that infrastructure, I use it to start standalone virtual machines (usually to test various Ubuntu releases) on my Linux server. Things work great... until they don't. Here's how I managed to waste half a day chasing imaginary gremlins caused by a simple error. Read more ... ## This Week in Spring - September 15th, 2026 DevFeed: [This Week in Spring - September 15th, 2026]() Original publisher: [Read original article]() Author: joshlong Published: 2026-09-15T00:00:00Z Content type: article Language: en Sources: [Spring]() Topics: [Spring AI](), [Java](), [Security](), [OAuth 2.0](), [Spring Boot](), [JavaFX](), [IntelliJ IDEA](), [debugging]() Tags: [batch](), [boot](), [cloud](), [debugging](), [event-driven](), [intellij-idea](), [java](), [learn](), [microservices](), [oauth-2-0](), [reactive](), [security](), [serverless](), [spring](), [spring-ai](), [web-applications]() ### AI overview A September 15, 2026 roundup of Spring-related developer content, covering Java memory management, Spring AI chat-memory summarization, JavaFX application security with Spring Security and OAuth 2.0, OAuth 2.1 with Spring Authorization Server, Spring and Gemini video understanding, Java AI libraries, Netflix's Java and Spring story, Spring Batch, and Spring Boot debugging. ### Source excerpt Hi, Spring fans! Welcome to another rip-roarin' installment of This Week in Spring! I'm writing this to you from sun-kissed San Francisco, CA, sipping some coffee and watching the bay from my breakfast nook. What a wonderful day! A wonderful day in which to learn about the latest and greatest in Spring, even! Let's dive right in! I really loved this presentation by Oracle's Ron Pressler on the principles of memory management in Java More Craig Walls Spring AI goodness! Here's a nice recipe on summarizing chat memory Over the last few weeks, I've done some content on securing JavaFX applications with Spring Security and OAuth 2.0. That work has landed, and our friends at JFX-central.com have taken that video and the resulting code and transcribed the content into this lovely tutorial - check it out! I loved this post on securing modern applications with OAuth 2.1 and Spring Authorization Server This is a really cool video on understanding video with Spring and Gemini I just learned about this amazing new Java library called Quixotic.ai (what a name! LOL) that provides all sorts of cool stuff that might make your Java-based AI workloads even better. I wonder if there are amazing integration possibilities for Spring AI, too... In last week's A Bootiful Podcast, I was delighted to sit down and chat with Netflix's Paul Bakker on their Java and Spring story, scaling the system, and more. Huh! There's a new Spring Batch IntelliJ IDEA plugin, but search me for what's new! No release notes. Either way, get it while it's hot! Speaking of Spring Batch, there's a nice post here on scaling to millions of rows with Spring Batch that just dropped Speaking of Spring and IntelliJ, there's a nice article over on Baeldung on debugging Spring Boot-based workloads with the Spring debugger ## C++ in the Age of AI: Visual Studio at CppCon 2026 DevFeed: [C++ in the Age of AI: Visual Studio at CppCon 2026]() Original publisher: [Read original article]() Author: Augustin Popa Published: 2026-09-14T19:34:43Z Content type: article Language: en Sources: [C++ Team Blog]() Topics: [C++](), [Visual Studio](), [GitHub Copilot](), [Visual Studio 2026](), [build performance](), [MSVC](), [debugging](), [Optimization](), [Refactoring](), [Artificial Intelligence]() Tags: [ai](), [build-optimization](), [build-performance](), [c-plus-plus](), [copilot](), [cppcon](), [debugging](), [github-copilot](), [msvc](), [visual-studio](), [visual-studio-2026]() ### AI overview This companion reading guide covers how Visual Studio 2026 is evolving C++ development with improved code navigation, build and runtime performance, language feature support, debugging, modernization, refactoring, and AI-assisted workflows using GitHub Copilot. ### Source excerpt At CppCon 2026, we shared how Visual Studio is evolving to help you work more effectively with large C++ codebases, improve build and runtime performance, adopt the latest language features, and incorporate AI into your existing workflows. This post is a companion reading guide for our session, C++ in the Age of AI: How Visual [...] The post C++ in the Age of AI: Visual Studio at CppCon 2026 appeared first on C++ Team Blog. ## ESP32 Bit Pirate: Bridging Modern Microcontrollers and Browser-Based Hardware Debugging DevFeed: [ESP32 Bit Pirate: Bridging Modern Microcontrollers and Browser-Based Hardware Debugging]() Original publisher: [Read original article]() Author: Olimpiu Pop Published: 2026-09-14T06:06:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [ESP32](), [HTML5](), [browsers](), [Hardware](), [C++](), [Tooling]() Tags: [browser](), [browsers](), [c-plus-plus](), [command-line](), [debugging](), [development](), [development-tools](), [embedded-devices](), [embedded-software-dev](), [esp32](), [esp32-bitpirate-web](), [html5](), [microcontrollers](), [news]() ### AI overview ESP32 Bit Pirate is a browser-based, multi-protocol debugging platform for ESP32-S3 boards. It uses HTML5 APIs such as Web Serial and WebUSB for firmware flashing, terminal access, documentation, and hardware analysis without requiring local development tools. ### Source excerpt ESP32 Bit Pirate project integrates multi-protocol debugging within a browser environment using HTML5 APIs. It enables users to install firmware and interact with microcontrollers like the ESP32-S3 directly from the browser. The platform supports various digital and wireless protocols while providing hands-on guidance through practical recipes for tasks such as memory dumping and signal analysis. By Olimpiu Pop ## The Thumb That Ran Ahead of the Finger: Anatomy of a Compose Slider Bug DevFeed: [The Thumb That Ran Ahead of the Finger: Anatomy of a Compose Slider Bug]() Original publisher: [Read original article]() Author: Vitaliy Gribko Published: 2026-09-14T04:19:34Z Content type: article Language: en Sources: [ProAndroidDev - Medium]() Topics: [bug](), [Compose](), [Android](), [Design system](), [Code]() Tags: [android](), [bug](), [code](), [compose](), [debugging](), [design-system](), [jetpack-compose](), [kotlin](), [qa](), [race-condition](), [ui]() ### AI overview This article examines a deterministic bug in a custom Compose slider where the thumb moves ahead of the user's finger during a drag. It traces the issue to a design-system slider forked from the AOSP Material implementation and discusses debugging and code simplification. ### Source excerpt A bug report sat in the backlog for seven months. The fix took a day, deleted a third of the slider's logic, and was almost shipped with a second bug inside -- until a machine read my diff better than I did. This is the whole story: the ported behavior that never made sense, the race nobody reported, and why the best fixes remove code. The report The bug report was seven months old when it reached me. A QA engineer had filed it in December, with a screen recording and three steps: Open the people search filters. Grab the right-hand thumb of the age range slider. Drag it slowly to the left. The recording showed the problem in two seconds. The thumb does not follow the finger. It sprints ahead -- you are still crossing the gap between two ticks, and the thumb is already standing on the next one, waiting for you, like a dog that runs to the park while you are still tying your shoes. Expected: the thumb moves with the finger. Actual: it escapes. On a budget phone, on two Android versions, every time. Not a race condition, not a flake -- a perfectly deterministic lie, filmed in December, assigned to a fix-day in July. Seven months is not negligence. It is the natural half-life of a visual glitch filed as minor against a screen nobody dies on. The age filter works. You tap a tick, the value applies. Only the drag -- the one gesture the slider exists for -- feels wrong in a way that is hard to screenshot and easy to deprioritize. When the ticket finally landed on my desk, a colleague glanced at it and asked whether it had already been fixed once. It had not. But I understood his confusion later, when I opened the slider's source and found a comment that explained everything -- including why this bug felt so old. The comment that confessed The slider is not the framework's slider. Our design system ships its own Compose slider, forked from the AOSP Material one, because design needed three knobs the framework does not expose: a custom thumb radius, a custom track height, a differ ## Open-Source Project Brings Full iOS 27 Virtualization to Apple Silicon DevFeed: [Open-Source Project Brings Full iOS 27 Virtualization to Apple Silicon]() Original publisher: [Read original article]() Author: Sergio De Simone Published: 2026-09-12T16:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [iOS](), [Tooling](), [Command-line interface](), [debugging](), [App]() Tags: [apple](), [cli](), [debugging](), [development](), [ios](), [ios-27-virtualization](), [iphone](), [kernel](), [macos](), [mobile](), [mobile-testing](), [news](), [open-source](), [research](), [reverse-engineering](), [security](), [ssh](), [testing](), [virtualization](), [xcode]() ### AI overview vphone-cli runs a full iOS 27 system as a virtual machine on Apple Silicon using Apple's Virtualization.framework. The article contrasts it with the Xcode iPhone Simulator and highlights uses in security research, reverse engineering, debugging, and automated testing. ### Source excerpt The open-Source project vphone-cli enables a full iOS 27 system to run as a virtual machine on Apple Silicon. Built on Apple's own Virtualization.framework rather than traditional emulation, the project opens up new possibilities for security research, reverse engineering, and automated iOS testing. By Sergio De Simone ## Quiz: Python Debugging With Pdb DevFeed: [Quiz: Python Debugging With Pdb]() Original publisher: [Read original article]() Author: Real Python Published: 2026-09-12T12:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [Python](), [debugging](), [debug]() Tags: [bugs](), [course](), [debugger](), [debugging](), [how-to](), [learn](), [python](), [resources](), [tool](), [tutorial]() ### AI overview An interactive 10-question quiz that tests practical knowledge of Python's built-in pdb debugger, including inspecting variables, stepping through code, using conditional breakpoints, watching expressions, and interpreting stack traces. ### Source excerpt Practice using pdb, Python's built-in debugger. Check variables, step through code, set conditional breakpoints, and read a stack trace. ## Knowledge Graph as context for LLMs: demonstrating decisive RCA and faster production performance DevFeed: [Knowledge Graph as context for LLMs: demonstrating decisive RCA and faster production performance]() Original publisher: [Read original article]() Author: Sarah Constant Published: 2026-09-12T11:22:06.456390Z Content type: article Language: en Sources: [Grafana Labs blog on Grafana Labs]() Topics: [Large Language Model](), [Grafana Cloud](), [debugging](), [incident](), [telemetry](), [observability ai agents]() Tags: [ai](), [ai-agents](), [analytics](), [debugging](), [grafana](), [grafana-cloud](), [incident](), [knowledge-graph](), [llms](), [logs](), [metrics](), [monitoring](), [observability](), [telemetry](), [traces]() ### AI overview The article reports Grafana Labs experiments testing whether providing AI agents with Grafana Cloud's Knowledge Graph improves incident debugging compared with raw telemetry alone. In one incident replayed 16 times per approach, Knowledge Graph context led to the correct root cause 15 times, versus once with raw telemetry. The article also describes challenges including misleading signals, unsupported confident answers, and inconsistent investigations, arguing that well-structured context matters more than context-window size alone. ### Source excerpt On the product team here at Grafana Labs, we consider AI agents our users, too. That's why we set out to test how well agents can debug incidents across the full stack, and how much better they perform with Grafana Cloud's Knowledge Graph vs. using raw telemetry alone. Our early results are promising. In one real incident we replayed 16 times each way, an agent with Knowledge Graph context found the correct root cause 15 times, compared with just once using raw telemetry alone. Along the way, we also uncovered some of the challenges that still stand in the way of reliable AI-assisted debugging, from chasing the wrong signals to confidently making things up and producing inconsistent answers. We're still early, but our findings point to an important idea. The industry's shorthand right now is that a bigger context window will lead to better outputs. Our findings suggest it's not just about more context; it's about structuring your data well enough to serve the right context. Here's a look at what we've learned so far, as we continue to experiment out in the open and bring you along, the Grafana Labs way. Giving an agent access to telemetry is just the beginning Give a current-generation model like Opus 4.8 access to your raw telemetry during a live incident, and it genuinely starts to figure things out: querying metrics and logs, forming a hypothesis, and checking it. We have watched it work on our own incidents, and it does it affordably. But if you run software at scale, where uptime is business-critical and large teams share the responsibility, a better model alone doesn't get you all the way there for debugging. From analyzing how LLMs do root-cause analysis on our own infrastructure, and from speaking to our customers, we've uncovered three problems that get in the way: The further the cause is from the alert, the more likely the model is to get it wrong. An agent may confidently make things up when it doesn't have the evidence it needs. The same investigation c ## A working incident response model for GPU clouds DevFeed: [A working incident response model for GPU clouds]() Original publisher: [Read original article]() Author: Sridhar Rajarao Published: 2026-09-12T00:00:00Z Content type: article Language: en Sources: [Sridhar Rajarao]() Topics: [incident](), [Incident response](), [GPU](), [Monitoring](), [Tooling]() Tags: [communication](), [debugging](), [gpu](), [gpu-cloud](), [grafana](), [incident](), [incident-management](), [incident-response](), [jira](), [management](), [on-call](), [operations](), [ownership](), [pagerduty](), [review](), [slack](), [sre]() ### AI overview This article presents an incident response model for GPU clouds and other customer-facing infrastructure businesses. It emphasizes preparation, named ownership, meaningful alert paths, incident command, separation of technical work from customer communication, and post-incident learning. It argues that tools such as PagerDuty, Jira, Grafana, and Slack are useful only within a clear operating model. ### Source excerpt The tools matter, but they only work when they sit inside a clear operating model: ownership, signal, command, communication, and learning. ## How to add Sentry monitoring to a Webflow Cloud app DevFeed: [How to add Sentry monitoring to a Webflow Cloud app]() Original publisher: [Read original article]() Author: Ismail Ajagbe Published: 2026-09-12T00:00:00Z Content type: tutorial Language: en Sources: [Webflow Blog]() Topics: [error tracking](), [Next.js](), [Workers](), [session replay](), [debugging](), [Traces](), [configuration](), [Instrumentation](), [Command-line interface]() Tags: [cloudflare-workers](), [debugging](), [error-tracking](), [guides](), [how-to](), [instrumentation](), [monitoring](), [next-js](), [session-replay](), [traces]() ### AI overview This tutorial explains how to manually add Sentry monitoring to a Webflow Cloud app running Next.js. It covers SDK installation, initialization files, environment variables, a Cloudflare-specific tunnel fix, verification, alerts, and common silent failure modes. The setup enables error grouping, stack traces, performance traces, and session replay. ### Source excerpt Learn how to add Sentry monitoring to a Webflow Cloud Next.js app. Get error grouping, stack traces, and session replay working. ## How we shipped 15 Tbps for OpenAI in 90 days (Session 2 of 3) DevFeed: [How we shipped 15 Tbps for OpenAI in 90 days (Session 2 of 3)]() Original publisher: [Read original article]() Author: Sridhar Rajarao Published: 2026-09-12T00:00:00Z Content type: article Language: en Sources: [Sridhar Rajarao]() Topics: [OpenAI](), [Network](), [GPU](), [Server](), [Cache](), [API](), [Oracle Database]() Tags: [api](), [architecture](), [build](), [cache](), [capacity](), [database](), [debugging](), [execution](), [gateway](), [gpu](), [network](), [object](), [openai](), [performance](), [platform-engineering](), [server](), [servers](), [sre](), [storage](), [testing](), [warp]() ### AI overview The second session describes turning an architecture for OpenAI's 15 Tbps system into a delivery plan. It covers coordinated capacity planning across network, gateway, server, storage, and database teams; caching object names through the Inventory API; delivery tracking; and performance validation. Early WARP testing found packet drops caused by an unsuitable MTU of 1500, which was changed to 9100. ### Source excerpt Architecture was only the first week. Session 2 is about the build: capacity, execution discipline, and the first signs that performance would be the real test. ## Module Tracking in Swift Debug Info DevFeed: [Module Tracking in Swift Debug Info]() Original publisher: [Read original article]() Author: Adrian Prantl Published: 2026-09-11T15:30:00Z Content type: tutorial Language: en Sources: [Swift.org]() Topics: [debugging](), [debug](), [toolchain](), [C++]() Tags: [cmake](), [debug](), [debugger](), [debugging](), [jit](), [swift]() ### AI overview Swift 6.3 and the upcoming Swift 6.4 improve how explicitly built Swift modules are referenced in debug information. The article explains how this helps LLDB locate modules for expression evaluation, improving debugging reliability and reducing build products, while noting that custom build systems may need adjustments. ### Source excerpt When your Swift program hits a breakpoint and stops so you can inspect it, the debugger's expression evaluator has to find the exact Swift module your code was built from. Until now, that lookup wasn't always precise. The upcoming Swift 6.4 release will include changes, begun in Swift 6.3, that address this by updating how the Swift compiler references explicitly-built Swift modules in debug info. The majority of developers will automatically benefit from faster, more reliable debugging and smaller build products, without any modifications to their SwiftPM or Xcode projects. For developers who maintain their own build systems using, for example, Bazel, Buck, or CMake, some adjustments may be necessary to take advantage of these changes. This article explains how the debugger uses Swift modules. Next, it describes how Swift 6.3 changes the way modules are tracked in debug info to solve several problems with the previous representation. Finally, it shows how to adjust build systems to take advantage of the new representation and eliminate some build steps that are no longer necessary. Swift modules and expression evaluation LLDB's standout feature is its powerful expression evaluator. Because LLDB embeds the Clang and Swift compilers, it can JIT-compile any valid source code and run it in the context of your application while stopped at a breakpoint. This includes not just calling code in your application, but also defining new data types, functions, and closures. Debugging features that are usually reserved for interpreted or JIT-compiled languages like JavaScript become available to ahead-of-time-compiled languages like C++ and, of course, Swift! In order to JIT-compile user expressions that make use of data types defined in the debugged program, LLDB's embedded Swift compiler needs to import the Swift modules defining those types. In a world before explicitly-built modules, LLDB would find the base name of the main module at the current breakpoint in the debug info ## Debugging our AI search assistant with agent tracing DevFeed: [Debugging our AI search assistant with agent tracing]() Original publisher: [Read original article]() Author: Dominik Buszowiecki; Shaun Kaasten Published: 2026-09-11T09:00:00Z Content type: article Language: en Sources: [Sentry Blog]() Topics: [AI search](), [agent observability](), [debugging](), [tracing](), [Large Language Model]() Tags: [agent](), [ai](), [api](), [debugging](), [errors](), [eval](), [llm](), [search](), [sentry](), [tracing]() ### AI overview Sentry engineers describe how they debugged the Search Query Assistant, which converts natural-language prompts into Sentry Syntax queries. They used evals for performance measurement and AI Conversation tracing to investigate failures, including a bug involving custom numerical attributes that caused queries to return no results. ### Source excerpt See how Sentry engineers used AI Conversations to debug a natural language search assistant and fix a tricky query generation bug. ## Session Traces and Cost Controls Help Diagnose AI Agent Failures DevFeed: [Session Traces and Cost Controls Help Diagnose AI Agent Failures]() Original publisher: [Read original article]() Author: Mark Silvester Published: 2026-09-11T08:14:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [ai observability](), [AI Bots](), [debugging]() Tags: [agents](), [ai](), [ai-agent](), [ai-ml-data-engineering](), [artificial-intelligence](), [cost](), [debugging](), [devops](), [llm](), [loops](), [ml-data-engineering](), [monitoring](), [news](), [observability](), [observability-ai-agents](), [opentelemetry](), [traces]() ### AI overview The article describes using nested session traces, execution metrics, and cost limits to investigate and contain AI agent failures such as repeated tool calls and runaway spending. ### Source excerpt Session traces and cost controls are emerging as key observability techniques for diagnosing AI agent failures, helping teams spot tool-call loops and runaway spend while preserving enough execution context for post-incident debugging. By Mark Silvester ## Cypress Ambassador Spotlight: Maksym Donets DevFeed: [Cypress Ambassador Spotlight: Maksym Donets]() Original publisher: [Read original article]() Published: 2026-09-10T16:12:22Z Content type: article Language: en Sources: [Cypress Blog]() Topics: [Cypress](), [Testing](), [Cloud](), [Automation]() Tags: [ambassador](), [automation](), [bugs](), [cloud](), [community](), [cypress](), [debugging](), [learning](), [qa](), [testing]() ### AI overview An ambassador spotlight featuring Maksym Donets, an Automation QA Engineer who discusses learning, sharing, helping developers debug failed pipelines with Cypress Cloud, and using cy.session() with cy.request() to simplify session handling and speed up tests. He also shares advice for getting started with Cypress and mentions catching bugs with end-to-end testing. ### Source excerpt Welcome back to another edition of our Ambassador Spotlight series, where we shine a light on the Cypress community members who make testing better for everyone through the blogs they write, the talks they give, and the day-to-day help they offer to fellow developers. Curious about the program? You can learn more about it here. This time, we're catching up with Maksym Donets, an Automation QA Engineer with a straightforward philosophy on testing and an even more straightforward philosophy on li ## What to expect at the Zephyr Project Meetup (September 17, 2026) - Zurich, Switzerland DevFeed: [What to expect at the Zephyr Project Meetup (September 17, 2026) - Zurich, Switzerland]() Original publisher: [Read original article]() Author: Susan Remmert Published: 2026-09-10T05:00:25Z Content type: news Language: en Sources: [Zephyr Project]() Topics: [Embedded Systems](), [Open Source](), [Embedded Software Dev](), [Tooling](), [Artificial Intelligence]() Tags: [2026](), [blog](), [community](), [debugging](), [developer-tools](), [developers](), [embedded](), [embedded-systems](), [event](), [events](), [meetup](), [modem](), [networking](), [open-source](), [practical](), [switzerland](), [technical]() ### AI overview An announcement for the September 17, 2026, Zephyr Project Meetup in Zurich, Switzerland, organized by Zoi TechCon GmbH. The event will include presentations on Zephyr modem support, embedded applications, developer tools, hardware, and practical implementation experiences. ### Source excerpt The Zephyr Project community is heading to Zurich, Switzerland! Join us on Thursday, September 17, 2026, for an in-person Zephyr Project Meetup organized by Zoi TechCon GmbH. The meetup will take place at Westhive Kitchen, Hardturmstrasse 161, 8005 Zürich, Switzerland. The event is open to developers, engineers, contributors, students, technology professionals, and anyone interested in open source and embedded systems. ## Troubleshoot Kafka issues across every layer of your stack with Kafka Console DevFeed: [Troubleshoot Kafka issues across every layer of your stack with Kafka Console]() Original publisher: [Read original article]() Author: Tori Engler; Shelly Matskel Published: 2026-09-10T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Kafka](), [configuration]() Tags: [apache](), [data-streams-monitoring](), [debugging](), [event-streaming](), [infrastructure](), [kafka](), [monitor](), [performance](), [root-cause-analysis]() ### AI overview An overview of Datadog Kafka Console for diagnosing Kafka health and performance issues, inspecting messages, and tuning configurations. ### Source excerpt Learn how Kafka Console helps you identify Kafka issues, inspect messages, and tune configurations with infrastructure and app context. ## Introducing Fast and Reliable Wireless Debugging with Android Debug Bridge (ADB) Wi-Fi 2.0 DevFeed: [Introducing Fast and Reliable Wireless Debugging with Android Debug Bridge (ADB) Wi-Fi 2.0]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-09-09T16:00:00Z Content type: release Language: en Sources: [Android Developers Blog](), [Android Developers Blog]() Topics: [Wireless Debugging](), [debugging]() Tags: [adb-wi-fi-2-0](), [android](), [android-studio](), [debugging](), [wireless-debugging]() ### AI overview ADB Wi-Fi 2.0 updates Android wireless debugging with a redesigned server stack, smarter network handling, and improved Android Studio discovery. The article reports higher automatic connection success rates and faster connections, and lists the required versions and pairing steps. ### Source excerpt Posted by Steven Jenkins, Product Manager, Sherif Eid, Senior Software Engineer, and Fabien Sanglard, Staff Software Engineer, Android Studio Wireless debugging on Android is now faster, more reliable, and easier to set up than ever. With ADB Wi-Fi 2.0, we've introduced a new server stack and smarter network handling to directly address developer feedback around usability gaps. How ADB Wi-Fi 2.0 Improves Wireless Debugging To ensure ADB Wi-Fi 2.0 is even more reliable, we reworked all three core components of the stack: the adb server, the adbd daemon, and Android Studio. Here are the new features: A new server stack (adb): Previously, wireless device connections would sever when network configurations changed or devices were turned off. This meant that connections would drop for common occurrences. With our new mDNS stack, we've replaced both Bonjour and legacy mDNS so that your wireless devices more reliably stay connected as you go about your day. Smarter network handling (adbd): Previously, the workstation's mDNS client would sporadically drop services. Now, the daemon automatically turns off ADB Wi-Fi when it detects an untrusted network and re-enables itself once running on a user-allowed network. Improved discoverability in Android Studio: Previously, Wi-Fi pairing was difficult to find. Now, you simply enable wireless debugging on your phone and it will show in Android Studio's Device Manager. With ADB Wi-Fi 2.0, auto-connection success rates improved by 32% and connection speeds increased by 66% for 90% of connections. Getting Started You can use ADB Wi-Fi 2.0 on your phone, tablet, Wear OS, and TV. Here's how to get started: Update to Android 17, Android SDK Platform-Tools 37.0.0, and Android Studio Quail 3 or later. Ensure your workstation and your Android device are connected to the same Wi-Fi network. On your device, navigate to Developer Options and enable Wireless debugging. Open the Android Studio Device Manager and click the pair over Wi-Fi icon. Sc ## Introducing Fast and Reliable Wireless Debugging with Android Debug Bridge (ADB) Wi-Fi 2.0 DevFeed: [Introducing Fast and Reliable Wireless Debugging with Android Debug Bridge (ADB) Wi-Fi 2.0]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-09-09T16:00:00Z Content type: release Language: en Sources: [Android Developers Blog]() Topics: [ADB Wi-Fi 2.0](), [Wireless Debugging](), [Android](), [Android Studio](), [Wi-Fi](), [SDK]() Tags: [adb](), [adb-wi-fi-2-0](), [android](), [android-studio](), [debugging](), [network](), [sdk](), [wi-fi](), [wireless-debugging]() ### AI overview Android introduces ADB Wi-Fi 2.0, a wireless debugging update that reworks the adb server, adbd daemon, and Android Studio integration. It adds a new mDNS-based server stack, smarter handling of untrusted networks, and improved device discoverability. The article reports a 32% improvement in auto-connection success rates and a 66% increase in connection speeds for 90% of connections. ### Source excerpt Posted by Steven Jenkins, Product Manager, Sherif Eid, Senior Software Engineer, and Fabien Sanglard, Staff Software Engineer, Android Studio Wireless debugging on Android is now faster, more reliable, and easier to set up than ever. With ADB Wi-Fi 2.0, we've introduced a new server stack and smarter network handling to directly address developer feedback around usability gaps. How ADB Wi-Fi 2.0 Improves Wireless Debugging To ensure ADB Wi-Fi 2.0 is even more reliable, we reworked all three core components of the stack: the adb server, the adbd daemon, and Android Studio. Here are the new features: A new server stack (adb): Previously, wireless device connections would sever when network configurations changed or devices were turned off. This meant that connections would drop for common occurrences. With our new mDNS stack, we've replaced both Bonjour and legacy mDNS so that your wireless devices more reliably stay connected as you go about your day. Smarter network handling (adbd): Previously, the workstation's mDNS client would sporadically drop services. Now, the daemon automatically turns off ADB Wi-Fi when it detects an untrusted network and re-enables itself once running on a user-allowed network. Improved discoverability in Android Studio: Previously, Wi-Fi pairing was difficult to find. Now, you simply enable wireless debugging on your phone and it will show in Android Studio's Device Manager. With ADB Wi-Fi 2.0, auto-connection success rates improved by 32% and connection speeds increased by 66% for 90% of connections. Getting Started You can use ADB Wi-Fi 2.0 on your phone, tablet, Wear OS, and TV. Here's how to get started: Update to Android 17, Android SDK Platform-Tools 37.0.0, and Android Studio Quail 3 or later. Ensure your workstation and your Android device are connected to the same Wi-Fi network. On your device, navigate to Developer Options and enable Wireless debugging. Open the Android Studio Device Manager and click the pair over Wi-Fi icon. Sc ## The Rider 2026.3 Early Access Program Is Open DevFeed: [The Rider 2026.3 Early Access Program Is Open]() Original publisher: [Read original article]() Author: Alexander Kurakin Published: 2026-09-07T09:35:21Z Content type: release Language: en Sources: [The JetBrains Blog]() Topics: [debugging](), [C++]() Tags: [c-plus-plus](), [code-completion](), [debugger](), [debugging](), [eap](), [game-development](), [gamedev](), [net-tools](), [rider](), [test-coverage](), [unreal-engine]() ### AI overview Rider 2026.3's first Early Access build adds rainbow brackets, streamlined data-breakpoint setup, a consolidated game-development plugin category, and code-completion filters. ### Source excerpt The first Early Access build for Rider 2026.3 is now available! It includes rainbow brackets, an easier way to set data breakpoints, a new Game Development plugin category, and filters in code completion. You can get the build from our website or through the Toolbox App. Here's a look at what's new. Rainbow brackets: You [...] [Next page]()