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Summaries are not the original full articles. ## Jemalloc 5.4 Released With Portability Improvements, Code Cleanups DevFeed: [Jemalloc 5.4 Released With Portability Improvements, Code Cleanups]() Original publisher: [Read original article]() Author: Michael Larabel Published: 2026-09-17T22:37:11Z Content type: release Language: en Sources: [Phoronix]() Topics: [Code](), [Refactoring](), [test-coverage](), [bug](), [cpu](), [gcc](), [configuration]() Tags: [bug](), [code](), [configuration](), [cpu](), [desktop-linux](), [error-handling](), [gcc](), [improvements](), [linux-benchmarking](), [linux-hardware-benchmarks](), [linux-hardware-reviews](), [linux-how-to](), [linux-performance](), [linux-server-benchmarks](), [open-source-graphics](), [phoronix](), [phoronix-test-suite](), [process](), [profiling](), [refactoring](), [synchronization](), [test-coverage](), [thread](), [ubuntu-benchmarks](), [ubuntu-hardware](), [yield]() ### AI overview Jemalloc 5.4 is released with portability improvements, code refactoring, bug fixes, expanded test coverage, new allocation features, optimizations, and GCC 16 warning fixes. The release adds an operating-system abstraction layer for platform-dependent operations. ### Source excerpt Earlier this year Meta announced a renewed investment into the jemalloc memory allocator that's been popular for server and HPC use among various desktop use-cases too. After stagnating a bit in recent years, Jemalloc has been off to seeing new developments since Meta's announcement and out today is Jemalloc 5.4 as the latest step forward... ## \[$\] Thread-identity switcheroo for io\_uring DevFeed: [\[$\] Thread-identity switcheroo for io\_uring]() Original publisher: [Read original article]() Author: corbet Published: 2026-09-17T13:49:59Z Content type: article Language: en Sources: [LWN.net]() Topics: [io\_uring](), [execution](), [Kernel]() Tags: [asynchronous](), [execution](), [io-uring](), [kernel](), [performance](), [rfc](), [thread]() ### AI overview An RFC patch set proposes a new approach to preserving io_uring's guarantee that applications do not block during asynchronous execution. The proposal addresses kernel paths not designed for asynchronous execution and the performance cost of existing workarounds. ### Source excerpt The io_uring subsystem is all about asynchronous execution; applications count on it to not block -- unless explicitly requested to. Within io_uring, maintaining the "never blocks" guarantee has sometimes been a challenge, given that many paths in the kernel were never designed for asynchronous execution. This problem has been worked around, but at a significant cost to performance. Now, io_uring maintainer Jens Axboe has posted an RFC patch set with a somewhat radical (and potentially scary) solution to the problem. ## Python 3.14 free-threaded build is now available in RHEL DevFeed: [Python 3.14 free-threaded build is now available in RHEL]() Original publisher: [Read original article]() Author: Lumír Balhar Published: 2026-09-14T13:01:41Z Content type: release Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [Python 3.14](), [Python](), [Concurrency](), [Linux](), [Concurrent Programming](), [cpu]() Tags: [cpu](), [developer-tools](), [developers](), [linux](), [performance](), [programming-languages-frameworks](), [python](), [python-3-14](), [red-hat](), [release](), [rhel](), [thread](), [upstream-release]() ### AI overview Red Hat Enterprise Linux 9.8 and 10.2 now provide a free-threaded Python 3.14 build through the Red Hat CodeReady Linux Builder repositories. With the GIL disabled, CPU-bound Python threads can execute in parallel across multiple CPU cores within a single process. The article explains expected performance benefits, installation, verification, and possible thread-safety issues in existing code. ### Source excerpt Developers on Red Hat Enterprise Linux 9.8 and 10.2 can now test full parallel CPU execution in Python using the new free-threaded Python 3.14 build. In addition to the regular Python 3.14 interpreter, we also provide the free-threaded variant in the Red Hat CodeReady Linux Builder repositories. Python 3.14 is the first upstream release where the free-threaded build is officially supported rather than experimental. The post Python 3.14 free-threaded build is now available in RHEL appeared first on Red Hat Developer. ## A quick overview of atomics in C DevFeed: [A quick overview of atomics in C]() Original publisher: [Read original article]() Author: Daniel Lemire Published: 2026-09-09T20:41:53Z Content type: tutorial Language: en Sources: [Daniel Lemire]() Topics: [C](), [Concurrency](), [Concurrent Programming](), [Programming]() Tags: [atomics](), [c](), [join](), [ordering](), [posix](), [programming-language](), [systems](), [thread](), [threads]() ### AI overview This tutorial introduces atomics in C, explaining data races on shared non-atomic variables, atomic accesses, instruction reordering, and memory-ordering models including relaxed, release, and acquire semantics. It also discusses C11 threads and platform support limitations. ### Source excerpt If you write in C, by default, you use a single thread. Extra cores do not help until you create more threads. However, if you include the header , you can pass a function to thrd_create, and wait for it with thrd_join. #include #include int worker(void *arg) { printf("hello from thread %d\n", *(int ... Continue reading A quick overview of atomics in C ## ESP32-C5 Pico board follows Raspberry Pi Pico form factor, ships with on-board or external antenna DevFeed: [ESP32-C5 Pico board follows Raspberry Pi Pico form factor, ships with on-board or external antenna]() Original publisher: [Read original article]() Author: Jean-Luc Aufranc (CNXSoft) Published: 2026-09-09T07:00:50Z Content type: news Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [ESP32-C5](), [Raspberry Pi](), [Espressif](), [cpu](), [RISC-V](), [SOC](), [Bluetooth](), [wifi 6](), [zigbee](), [Matter](), [Embedded Systems](), [ESP-IDF]() Tags: [802-15-4](), [arduino](), [battery](), [ble](), [bluetooth](), [bluetooth-le](), [boot](), [c-c-plus-plus](), [development-board](), [embedded-systems](), [esp-idf](), [esp32](), [esp32-c5](), [espressif](), [gpio](), [hardware](), [iot](), [matter](), [news](), [port](), [raspberry-pi](), [risc-v](), [thread](), [usb](), [waveshare](), [wifi-6](), [zigbee]() ### AI overview The Waveshare ESP32-C5 Pico is a development board in the Raspberry Pi Pico form factor. It uses an ESP32-C5-MINI-1 series module with a RISC-V processor, dual-band WiFi 6, Bluetooth LE, and 802.15.4 support for Zigbee, Thread, and Matter. The board includes GPIO headers, USB-C, buttons, LEDs, and Li-Ion battery support, with variants offering PCB or external antennas. ### Source excerpt Waveshare ESP32-C5 Pico board brings the ESP32-C5 dual-band WiFi 6, Bluetooth LE, and 802.15.4 (Zigbee/Thread) SoC to the Raspberry Pi Pico form factor. The board features an ESP32-C5-MINI-1 Series module with PCB or external antenna, two 20-pin GPIO headers, a USB-C port for power and programming, Reset and Boot buttons, and a few LEDs. It also supports Li-Ion battery charging and discharging. Waveshare ESP32-C5 Pico specifications: Wireless module - ESP32-C5-MINI-1 or ESP32-C5-MINI-1U Wireless MCU - Espressif Systems ESP32-C5HF4 CPU Single-core 32-bit RISC-V processor @ up to 240 MHz Low-power RISC-V core @ 48 MHz acting as the main processor for power-sensitive applications Memory - 384 KB SRAM on-chip Storage - 320 KB ROM, 4MB SPI flash Wireless Dual-band (2.4/5 GHz) 802.11ax WiFi 6, 802.11b/g/n WiFi 4 backward compatibility WiFi modes: Station mode, SoftAP mode, SoftAP + Station mode, and promiscuous mode Bluetooth 5.0 Low Energy (LE) with Mesh support, up [...] The post ESP32-C5 Pico board follows Raspberry Pi Pico form factor, ships with on-board or external antenna appeared first on CNX Software - Embedded Systems News. ## FREE-WILi 2 portable hacking multitool features two RP2350 MCUs, ESP32-C5, ICE40 FPGA, and Raspberry Pi CM0 DevFeed: [FREE-WILi 2 portable hacking multitool features two RP2350 MCUs, ESP32-C5, ICE40 FPGA, and Raspberry Pi CM0]() Original publisher: [Read original article]() Author: Debashis Das Published: 2026-09-09T00:00:02Z Content type: news Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [Embedded Systems](), [Raspberry Pi](), [ESP32-C5](), [Hardware](), [Hacking](), [Linux]() Tags: [802-15-4](), [ble](), [bluetooth](), [broadcom-bcmxxxx](), [c-c-plus-plus](), [can](), [electronics](), [embedded](), [esp32](), [esp32-c5](), [espressif](), [fpga](), [hack](), [hacking](), [hardware](), [lattice](), [linux](), [lora](), [meshtastic](), [nfc](), [open-hardware](), [python](), [raspberry-pi](), [raspberry-pi-rp2350](), [rfid](), [rust](), [security](), [som](), [stm32](), [stmicro-stm32](), [texas-instruments-simplelink](), [thread](), [tools](), [video](), [wi-fi](), [wifi-6](), [wireless](), [zigbee]() ### AI overview The FREE-WILi 2 Founder Edition is an open-hardware, portable multitool for hardware hackers, pentesters, and embedded-system developers. It combines two Raspberry Pi RP2350 MCUs, an ESP32-C5, a Lattice ICE40UP5K FPGA, and a Raspberry Pi CM0 capable of running a full Linux OS, along with touchscreen controls, expansion headers, and multiple wireless interfaces. ### Source excerpt The FREE-WILi 2 (Founder Edition) is an open-hardware, portable hacking multitool and lab designed for hardware hackers, pentesters, and embedded system developers. Designed as an "open electronics multitool," it combines a range of chips and modules into a handheld device, including two Raspberry Pi RP2350 MCUs, an ESP32-C5 for wireless connectivity, a Lattice ICE40UP5K FPGA, and a Raspberry Pi CM0 for running a full Linux OS. The device also features a 3.5-inch capacitive touchscreen, a 14-button physical interface, and modular "Orca" headers for hardware expansion. Its wireless features include 2.4/5GHz Wi-Fi, Bluetooth, LoRa, sub-GHz RF, NFC, 125kHz RFID, and IR. These features make it very suitable for wireless testing, embedded hardware debugging, real-time control, electronics development, and retro gaming, with support for Adafruit Fruit Jam, PICO-8, and Doom. FREE-WILi 2 specifications: Compute Main MCUs - 2x Raspberry Pi RP2350B (One for main controls, one dedicated to display) SoM - Raspberry [...] The post FREE-WILi 2 portable hacking multitool features two RP2350 MCUs, ESP32-C5, ICE40 FPGA, and Raspberry Pi CM0 appeared first on CNX Software - Embedded Systems News. ## Native Async/Coroutine Reads in RocksDB DevFeed: [Native Async/Coroutine Reads in RocksDB]() Original publisher: [Read original article]() Author: Josh Kang Published: 2026-08-24T00:00:00Z Content type: release Language: en Sources: [RocksDB]() Topics: [rocksdb](), [Coroutines](), [C++](), [IO](), [API]() Tags: [async](), [asynchronous](), [blog](), [c-plus-plus](), [coroutine](), [io](), [native](), [rocksdb](), [thread]() ### AI overview RocksDB introduces experimental asynchronous Get and MultiGet APIs backed by native C++ coroutines. The APIs can suspend storage-bound reads, allowing a small executor to run other ready tasks and maintain more storage queue depth without one blocked application thread per read. The feature targets throughput for I/O-bound point lookups rather than reducing individual device-read latency. ### Source excerpt A point lookup that misses RocksDB's block cache can spend most of its time waiting for storage. The traditional way to keep more reads in flight is to add threads. That works, but each outstanding read parks a thread, carries a stack, and adds context-switching overhead. RocksDB now has experimental asynchronous Get and MultiGet APIs backed by native C++ coroutines. When a read reaches storage, RocksDB can suspend the request, let its read-executor worker run another ready task, and resume the request when the filesystem reports completion. A small executor can therefore maintain more storage queue depth without requiring one blocked application thread per read. These APIs are available in RocksDB 11.10.0. This is primarily a throughput feature for I/O-bound point lookups. It does not make an individual device read faster. Its benefit comes from keeping the device busy and using CPU threads for runnable work. The API surface RocksDB exposes the new read path through two public interfaces: DB::GetAsync and DB::MultiGetAsync return immediately on the native path and report completion through AsyncCallback::OnComplete. CoroDB::CoGet and CoroDB::CoMultiGet return lazy folly::coro::Task objects. CoGet produces a Status; CoMultiGet fills the same per-key values and statuses as synchronous MultiGet. The callback APIs suit applications that do not expose Folly tasks at their boundaries. The CoroDB APIs let coroutine-based callers await RocksDB directly, avoiding an application-side callback-to-Baton adapter and its extra completion handoff. Native execution requires RocksDB to be built with Folly and USE_COROUTINES=1. Neither interface requires ReadOptions::async_io. That flag continues to control the older internal async-I/O optimizations for synchronous MultiGet and iterators. The task APIs are lazy: no read begins until a task is awaited or started. Both interfaces take pointer and reference parameters, so keep the DB, column-family handles, ReadOptions, keys and their ## Tips for Saving Game Data in Godot DevFeed: [Tips for Saving Game Data in Godot]() Original publisher: [Read original article]() Published: 2026-08-21T00:00:00Z Content type: tutorial Language: en Sources: [Robin Ward]() Topics: [Godot](), [saving](), [Concurrent Programming](), [data](), [JSON](), [Hardware](), [Testing]() Tags: [bug](), [code](), [disk-space](), [game](), [games](), [json](), [mutex](), [os](), [saving](), [testing](), [thread](), [tips]() ### AI overview This tutorial describes a save-data approach for Godot games, based on experience shipping two games. It compares custom binary and JSON formats, recommends frequent debounced saves on a separate thread, checks available disk space, and discusses temporary-file replacement to reduce corrupted save-game reports. ### Source excerpt Saving game data is easy. Making your save code survive every kind of hardware failure is not. A lot of these issues will never show up during testing, but if your game reaches a wide audience with many different kinds of hard drives in different states of degradation, you will start to get bug reports about save games not working. I decided to write up my approach, learned over the course of shipping two Godot games, that has reduced our corrupted save game bug reports to virtually nothing. ## C++29 -- начало. Встреча ISO C++ в Брно DevFeed: [C++29 -- начало. Встреча ISO C++ в Брно]() Original publisher: [Read original article]() Author: antoshkka (Яндекс) Published: 2026-08-17T07:01:31Z Content type: article Language: ru Sources: [Яндекс - Как мы делаем Яндекс / Статьи]() Topics: [C++](), [floating-point](), [implementation]() Tags: [c-plus-plus](), [c-plus-plus-29](), [floating-point](), [fmt](), [format](), [implementation](), [iso](), [standard](), [standard-library](), [tagged-pointers](), [thread](), [threads](), [undefined-behavior](), [undefined-behaviour]() ### AI overview A report on the ISO C++ committee meeting in Brno, where work on C++29 began. It describes plans to organize and clarify documented undefined behavior and ill-formed-no-diagnostic-required cases, along with changes involving constexpr floating-point evaluation and other language rules. ### Source excerpt Привет! На связи Антон Полухин из Техплатформы Городских сервисов Яндекса. Недавно в Брно состоялась встреча международного комитета по стандартизации языка программирования C++, в которой я принимал активное участие. В этот раз началась работа над C++29 и как раз о новинках и хочется рассказать. Читать далее ## How OpenAI Built a Reliable Data Agent with Context, Memory, and Evals DevFeed: [How OpenAI Built a Reliable Data Agent with Context, Memory, and Evals]() Original publisher: [Read original article]() Author: Nikki Siapno Published: 2026-08-02T13:14:27Z Content type: article Language: en Sources: [Level Up Coding System Design Newsletter]() Topics: [OpenAI](), [AI Engineering](), [AI Development](), [data](), [SQL](), [Slack]() Tags: [agents](), [ai](), [ai-agents](), [ai-engineering](), [data](), [evals](), [memory](), [openai](), [schema](), [sql](), [thread](), [verify]() ### AI overview The article examines how OpenAI built an internal data agent for more than 3,500 users working across 70,000 datasets and over 600 petabytes of data. It explains that trustworthy results require more than valid SQL: the agent needs relevant business context, safeguards for permissions, ways to detect subtle query errors, and transparency so users can inspect its work. ### Source excerpt How OpenAI built its data agent to work across 70,000 datasets. ## @MainActor in Swift explained with code examples DevFeed: [@MainActor in Swift explained with code examples]() Original publisher: [Read original article]() Author: Antoine van der Lee Published: 2026-08-02T12:04:47Z Content type: tutorial Language: en Sources: [SwiftLee]() Topics: [Swift](), [Concurrency](), [Code](), [Xcode]() Tags: [article](), [code](), [concurrency](), [dispatchqueue](), [examples](), [guide](), [how-to](), [main-thread](), [swift](), [thread](), [xcode]() ### AI overview This tutorial explains how Swift's @MainActor global actor ensures that properties, methods, instances, and closures execute on the main thread. It also covers compiler-enforced main-thread execution, global actor isolation, nonisolated methods, and changes to default actor isolation in Swift 6.2 and Xcode 26. ### Source excerpt @MainActor is a global actor that performs its tasks on the main thread. You can use it to dispatch to the main thread by marking properties, methods, instances, or closures with the attribute. Instead of manually dispatching using DispatchQueue.main.async, you let the compiler enforce main thread execution for you. If you're new to Actors in ... -> The post @MainActor in Swift explained with code examples appeared first on SwiftLee. ## When It Makes Sense To "Block" The Main Thread DevFeed: [When It Makes Sense To "Block" The Main Thread]() Original publisher: [Read original article]() Author: hello@smashingmagazine.com (Victor Ayomipo) Published: 2026-07-17T08:00:00Z Content type: article Language: en Sources: [Articles on Smashing Magazine -- For Web Designers And Developers]() Topics: [JavaScript](), [Chrome extension](), [Latency](), [modern web development](), [Chrome](), [Concurrency]() Tags: [architecture](), [browser](), [chrome](), [chrome-extension](), [coding](), [javascript](), [latency](), [main-thread](), [performance](), [techniques](), [thread]() ### AI overview This article examines when blocking the browser's main thread can be faster than transferring work to a background worker. Using a Chrome screenshot extension as an example, it explains how serialization, copying, and deserialization can introduce enough latency to outweigh the responsiveness benefits of offloading computation. ### Source excerpt The common rule of thumb is to never "block" the browser's main thread when running JavaScript tasks. But is this a hard rule? Victor Ayomipo describes a use case he encountered involving a screenshot extension where he made an exception to the rule and decided that blocking the main thread was absolutely the right thing to do. ## Chat SDK adds Dial support DevFeed: [Chat SDK adds Dial support]() Original publisher: [Read original article]() Author: Ben Sabic Published: 2026-07-08T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [SDKs](), [Bots]() Tags: [apis](), [bots](), [documentation](), [media](), [posts](), [sdk](), [subscriptions](), [thread](), [voice]() ### AI overview Chat SDK adds a vendor-official Dial adapter for building bots that communicate through SMS, MMS, and iMessage on real phone numbers. Conversations are represented as Chat SDK threads, with support for media, inbound voice-call transcripts, standard message APIs, HMAC-verified webhooks, subscriptions, handlers, posts, and per-thread state. ### Source excerpt Chat SDK now supports Dial with the new vendor-official adapter. Build bots that send and receive SMS, MMS, and iMessage on a real phone number, with bidirectional media and inbound voice-call transcripts. Replies use the standard Chat SDK thread and message APIs, with HMAC-verified webhooks and stable per-conversation threading. Each phone conversation becomes a Chat SDK thread. Texts and media arrive as messages on that thread, and when a voice call ends, its transcript appears there too. Subscriptions, handlers, posts, and per-thread state work the same as with any other Chat SDK adapter. Read the Dial documentation to get started. Read more ## The Matter upgrade you've been waiting for DevFeed: [The Matter upgrade you've been waiting for]() Original publisher: [Read original article]() Author: Ingo Fischer Published: 2026-06-23T00:00:00Z Content type: article Language: en Sources: [Home Assistant]() Topics: [Matter](), [Home Assistant](), [TypeScript](), [Open Source](), [Network](), [Homebridge]() Tags: [2026](), [announcements](), [border-router](), [bugs](), [hardware](), [homebridge](), [matter](), [open-source](), [recovery](), [speed](), [standards](), [thread](), [typescript](), [upgrade](), [visualization]() ### AI overview Home Assistant introduces a new Matter implementation built on matter.js, an open source TypeScript implementation of the Matter standard. After beta testing and community contributions, the update aims to improve stability, reduce bugs, and accelerate startup and recovery. It also adds network visualization, upgrades to Matter 1.5.1, and updates the OpenThread Border Router app for Thread 1.4 support. ### Source excerpt It started as a passion project. Yet in a few years matter.js has grown beyond my wildest expectations, becoming the backbone of the open source Matter ecosystem, and powering everything from Homebridge to openHAB, and even some commercial products. Ten months ago, I joined forces with the Open Home Foundation to work full time as Lead Developer of Matter. Shortly after, I donated matter.js to the foundation - giving it a new home where it would be safeguarded for the future. Together we announced our plans to take Matter support in Home Assistant in a completely new direction: we set out to rebuild the Open Home Foundation Matter Server - the engine that powers Matter in Home Assistant - on matter.js. After four months of beta testing, with our community fixing bugs and contributing new features along the way, today we're thrilled to present the newest version of Matter for Home Assistant! 🎉 The Open Home Foundation invests in important technology to make open alternatives possible, and our work is funded in part by everyone who subscribes to Home Assistant Cloud and buys official hardware from our commercial partners. The launch of a new Matter experience in Home Assistant shows what's possible with your support. 💪 Presenting the matter.js plans at the Connectivity Standards Alliance (CSA) Member Meeting in November 2025 (right), and returning in March 2026 as an Outstanding Contributor Award recipient (left). Serving up more with matter.js For those new to matter.js, it's an open source TypeScript implementation of the Matter standard. I built it to give developers and power users more speed and flexibility, and to make Matter better suited for open source development across the millions of homes that use Home Assistant. By running Matter in Home Assistant on matter.js, all of those benefits now flow directly into the platform. This major update brings greater stability for Matter in Home Assistant, fewer bugs, and faster start-up and recovery. It also comes with ## Chat SDK adds AgentPhone support DevFeed: [Chat SDK adds AgentPhone support]() Original publisher: [Read original article]() Author: Vishal Yathish Published: 2026-06-01T14:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [SDKs](), [Bot](), [Chat Bot]() Tags: [building](), [channel](), [documentation](), [guide](), [learn](), [platforms](), [sdk](), [support](), [thread](), [voice]() ### AI overview Chat SDK adds a vendor-official AgentPhone adapter that lets bots handle voice calls and text messages using existing handlers. Calls and messages share one webhook and one conversation thread, preserving context across channels; call transcripts can be delivered as messages for responses through SMS or iMessage. ### Source excerpt Chat SDK now supports AgentPhone with the new vendor-official adapter. Give your bot its own phone number so it can handle voice calls and text messages using the same handlers you already write. When a call ends, the transcript is delivered as a message, allowing your bot to respond via SMS or iMessage. Calls and messages to the same number arrive via a single webhook, so you handle both from a single endpoint rather than a separate pipeline for each channel. They also land in one thread, so your bot maintains context throughout the conversation. Read the AgentPhone documentation to get started. Read more ## Diagnosing a Deadlock in Trino's Hudi Connector That Stalled Blinkit's Inventory Pipeline DevFeed: [Diagnosing a Deadlock in Trino's Hudi Connector That Stalled Blinkit's Inventory Pipeline]() Original publisher: [Read original article]() Author: Ratul Dawar Published: 2026-05-29T09:26:27Z Content type: article Language: en Sources: [Grofers]() Topics: [Deadlock](), [Concurrent Programming](), [Amazon S3]() Tags: [apache-hudi](), [big-data](), [blinkit](), [bug](), [deadlock](), [open-source](), [s3](), [thread](), [trino](), [trinos](), [yield]() ### AI overview Blinkit describes how a deadlock in Trino's Hudi connector stalled inventory replenishment queries without errors or resource saturation. The issue involved one thread pool handling both file-split production and signalling; the reported fix used cooperative scheduling and was contributed upstream. ### Source excerpt A silent deadlock in our query engine was stalling inventory replenishment jobs with no error, no crash -- just infinite waiting. This is the story of how we found it, traced it to an open-source bug, and fixed it upstream. TL;DRTrino's Hudi connector used a single thread pool for both producing file splits and signalling when there was room for more. Under load, every thread ended up waiting for a signal that had no thread left to run it. The fix was to switch the producer side to a cooperative scheduling pattern: yield the thread when the buffer is full, and resume when space opens. Our inventory replenishment pipeline was frozen. CPU was idle. Memory was fine. There were no errors anywhere. Queries just... stopped moving. The first signal was a long queue on one of our analytics clusters. Queries were piling up. Inventory replenishment jobs -- the jobs that decide how much stock every warehouse and store needs to hold -- were delayed. Blinkit's supply chain was being impacted. Dashboards were turning amber, but nothing was crashing. That was the unsettling part. Investigation: Resources Doing Nothing The affected cluster runs analytical workloads on Trino, reading data stored in Apache Hudi tables on S3. The natural first instinct in a queue build-up is to look at resource saturation -- a CPU spike, memory pressure, network bottleneck. There was none of that. The cluster was sitting largely idle, with CPU barely above baseline and heap usage well within limits. Every new query touching a Hudi table joined the queue and stayed there indefinitely. Queries that were already mid-execution completed fine. Only freshly submitted ones were affected. And crucially, there were no errors. No timeouts, no exceptions in the logs -- just silence and a growing backlog. A thread dump -- a snapshot of what every thread in the process is doing right now -- was our next move. It showed dozens of producer threads all stuck in the same parked state, waiting on the exact same internal signal. ## Sensereo joins Works with Home Assistant DevFeed: [Sensereo joins Works with Home Assistant]() Original publisher: [Read original article]() Author: Miranda Bishop Published: 2026-05-28T00:00:01Z Content type: news Language: en Sources: [Home Assistant]() Topics: [Home Assistant](), [Matter](), [Network]() Tags: [2026](), [battery](), [ecosystem](), [matter](), [products](), [safety](), [sensors](), [smart-home](), [thread](), [wireless](), [works-with-home-assistant]() ### AI overview Sensereo has joined the Works with Home Assistant program with Matter-based MS-1 smoke alarms and MSC-1 smoke and carbon monoxide alarms. The article explains how Matter and Thread support open, interoperable, energy-efficient smart-home devices while the alarms continue operating as regular alarms if the Thread network fails. Sensereo also plans to develop air quality sensors and other environmental sensing devices. ### Source excerpt We're sensing a change in the air this month as we welcome Sensereo to the Works with Home Assistant program 🎉. Specialists in environmental sensing, Sensereo brings Matter smoke and carbon monoxide (CO) alarms into the Home Assistant ecosystem - meaning more ways to keep your home open, safe, and sound. Built from a burning question... What happens if your smoke alarm goes off, but you're not there to hear it? It's an unsettling question, and one that led Roy Chen to found Sensereo in 2024. Driven to create safety devices that were equal parts reliable and resilient, Sensereo built the Matter-based MS-1 Smoke Alarm and MSC-1 Smoke and Carbon Monoxide Alarm, because as they put it: "every home deserves a system that will not fall silent when it matters most." It's just good sense For anyone unfamiliar, Matter is an open standard that lets smart home devices from different brands work together, regardless of who made them - no lock-in, no closed ecosystems. It's exactly the kind of open, interoperable technology the Open Home Foundation exists to champion. Thread operates on the same principle: it's an energy-efficient, wireless mesh network that connects devices directly to one another and can automatically reroute around disruptions. And for battery-powered alarms like Sensereo's, Thread's low-power design means fewer battery changes for devices that are always on duty. While we're talking about safety, it's important to note that if your Thread network did for any reason drop out, Sensereo's smoke and CO alarms will keep working as a "regular" alarm would - no smart home required. That peace of mind is central to how Sensereo thinks about their products, and having caught up with the team at CES 2026 earlier this year, we can tell you it's just the beginning. Air quality sensors and more are on the horizon, all building toward the same vision: to build an environmental intelligence system for the home that helps users understand and respond to their surroundings. "J ## Concurrent, atomic MSI hash tables DevFeed: [Concurrent, atomic MSI hash tables]() Original publisher: [Read original article]() Published: 2026-05-06T02:01:17Z Content type: tutorial Language: en Sources: [Chris Wellons]() Topics: [Concurrency](), [Concurrent Programming](), [Code](), [gcc](), [Processes]() Tags: [article](), [c](), [code](), [concurrency](), [concurrent](), [gcc](), [processes](), [thread]() ### AI overview This article explains how to add atomic operations to Mask-Step-Index (MSI) hash tables so they can be accessed concurrently without data races. It covers single-producer and multiple-consumer designs, relaxed atomics, and acquire-release synchronization when published objects must be safely observed. ### Source excerpt Readers will be familiar with Mask-Step-Index (MSI) hash tables, a technique for building fast, open-addressed hash tables in a dozen lines of code. If multiple threads or processes access an MSI table with at least one still inserting elements, care must be taken to avoid data races. This article will show how to add atomic operations to MSI tables in order to support different concurrency constraints. Let's begin with the simplest case: An integer hash set, no deletions, only one insert thread (single producer), and consumers do not care about insert order. That is, the producer inserts A then B, but consumers may observe B in the table before A. Suppose this is the hash table in the single-threaded case: int32_t *lookup(int32_t key, int32_t *table, int exp) { uint64_t hash = ((uint64_t)key * 1111111111111111111u) >> 32; uint32_t mask = ((uint32_t)1 << exp) - 1; uint32_t step = (hash >> (32 - exp)) | 1; for (uint32_t index = hash;;) { index = (index + step) & mask; if (!table[index] || table[index]==key) { return table + index; } } } Keys must be non-zero, and tables are zero-initialized. Usage example: // Initialization enum { exp = 8 }; int32_t table[1<<8] = {}; // Producer for (int i = 0; i < nkeys; i++) { *lookup(keys[i], table, exp) = keys[i]; } // Consumer int32_t key = 1234; bool present = *lookup(key, table, exp); The only problem is the data race on table slots. Since consumers can tolerate out-of-order insertions, ordering does not matter and relaxed atomics eliminate the data race. Insert and query now have different requirements, so it makes sense to distinguish them. Starting with the latter: bool contains(int32_t key, int32_t *table, int exp) { uint64_t hash = ((uint64_t)key * 1111111111111111111u) >> 32; uint32_t mask = ((uint32_t)1 << exp) - 1; uint32_t step = (hash >> (32 - exp)) | 1; for (uint32_t index = hash;;) { index = (index + step) & mask; int32_t k = __atomic_load_n(table+index, __ATOMIC_RELAXED); if (!k) { return false; } else if (k == ke ## Safe Optimistic Lock Coupling DevFeed: [Safe Optimistic Lock Coupling]() Original publisher: [Read original article]() Author: Thomas Neumann (noreply@blogger.com) Published: 2026-04-29T10:22:56Z Content type: article Language: en Sources: [Database Architects]() Topics: [Concurrency](), [Concurrent Programming](), [Data structures](), [Scalability](), [race-condition]() Tags: [concurrent](), [cpu](), [data-structures](), [locking](), [locks](), [mutex](), [performance](), [race-condition](), [scalability](), [synchronization](), [thread](), [typesafety]() ### AI overview The article explains how lock coupling can limit the scalability of concurrent binary-tree lookups because readers contend on locks, especially at the root. It presents Optimistic Lock Coupling, in which readers validate version numbers without writes, and discusses the race-condition risk when values are used before validation. ### Source excerpt As the number of CPU cores keeps growing, the scalability of concurrent data structures becomes increasingly important. A data structure that works fine on 4 cores can become a bottleneck on 32, not because of algorithmic limitations, but because of how it synchronizes access. We illustrate that with a simple binary tree. Usually these data structures are protected by some kind of lock: struct Node { mutex lock; key_type key; value_type value; Node* left, *right; }; struct Tree { mutex lock; Node* root; }; When searching a value, we can traverse the data structure, lock the parts of the data we are currently touching, and release locks when we are done ("lock coupling"): option Tree::lookup(key_type key) { lock.lock_shared(); mutex* currentLock = &lock; Node* iter = root; option result; while (iter) { if (key == iter->key) { result = iter->value; break; } Node* next = (key < iter->key) ? iter->left : iter->right; if (next) next->lock.lock_shared(); currentLock->unlock(); currentLock = next ? &next->lock : nullptr; iter = next; } currentLock->unlock(); return result; } While conceptually simple, lock coupling has quite poor performance in practice. The problem is that it creates contention on the locks, in particular for the root node. Every lookup goes through the root node, thus the root node is constantly locked and unlocked. While there is no semantic contention between lookups, as all readers can read the root concurrently, there is physical contention on the lock itself, which limits scalability. This can be seen below, with concurrent lookups in a tree of 100,000 elements, executed on a 16-core / 32-thread 9950X3D. Lookup scalability: no locking vs lock coupling This contention problem can be solved by using Optimistic Lock Coupling, a synchronization technique where readers do not perform any writes. The key idea here is that writers lock as usual, and increase a version number when they are done updating. Readers read the version numb ## What does using AI for post-mortems actually mean? DevFeed: [What does using AI for post-mortems actually mean?]() Original publisher: [Read original article]() Author: incident.io Published: 2026-04-23T14:29:00Z Content type: opinion Language: en Sources: [The incident.io Blog]() Topics: [Artificial Intelligence](), [Post Mortem](), [Incident response](), [incident](), [Compression](), [Slack]() Tags: [ai](), [channel](), [compression](), [docs](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [outage](), [post](), [post-mortem](), [slack](), [slack-incident](), [thread]() ### AI overview The article argues that AI can make post-mortems faster by gathering Slack threads, timelines, pull requests, and custom fields into a useful starting point. However, it warns that polished AI-generated documents can become useless if they replace the team's work of understanding what happened, why it happened, and what was learned. It distinguishes compression, which AI can automate effectively, from synthesis, which requires genuine human reasoning. ### Source excerpt Everyone is using AI to help with post-mortems now. We've built AI into our own post-mortem experience, pulling your Slack thread, timeline, PRs, and custom fields together and giving your team a meaningful starting point in seconds. But "AI for post-mortems" can mean very different things. Post-mortems are just one stage of the broader incident response lifecycle, and AI's role varies across all of it. ## Don't Block Suspend Functions DevFeed: [Don't Block Suspend Functions]() Original publisher: [Read original article]() Author: Jesse Wilson Published: 2026-01-22T04:32:49Z Content type: tutorial Language: en Sources: [Public Object]() Topics: [Coroutines](), [Kotlin](), [Concurrent Programming](), [Concurrency](), [async](), [Job](), [IO]() Tags: [async](), [await](), [blocking](), [blog-post](), [concurrency](), [coroutines](), [dispatcher](), [kotlin](), [thread](), [threads]() ### AI overview This Kotlin tutorial explains why blocking calls inside suspend functions can prevent other coroutines from running. It contrasts preemptive thread concurrency with cooperative coroutine concurrency and recommends avoiding blocking functions in suspending code, using the I/O dispatcher when necessary, and avoiding runBlocking. ### Source excerpt Here's a program that launches 3 jobs. The first runs forever and the other two exchange a value. @Test fun test() = runTest { val channel = Channel() val deferredA = async { while (isActive) { delay(1_000) } } val deferredB = async { channel.send("hello") } val deferredC = async { channel.receive() } deferredB.await( ## Thread Network Credentials Sharing DevFeed: [Thread Network Credentials Sharing]() Original publisher: [Read original article]() Author: John Lee Published: 2026-01-06T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [Protocol (disambiguation)](), [interoperability](), [Matter](), [migration](), [User Experience](), [m5stack]() Tags: [blog](), [border-router](), [connectivity](), [demo](), [fragmentation](), [interoperability](), [m5stack](), [matter](), [migration](), [network](), [onboarding](), [thread](), [user-experience]() ### AI overview This article introduces Thread Credentials Sharing, a Thread 1.4 feature for securely sharing administrative access and network credentials with new Thread Border Routers and devices. It explains Operational Dataset credentials, deployment benefits, usage scenarios, and a demonstration using an M5Stack Thread Border Router and the SmartThings app. ### Source excerpt This article introduces the Thread Credentials Sharing feature, explains why it is important, how it works, and provides a demo using M5Stack Thread Border Router and SmartThings app. ## Inside our effort to improve the Mintlify assistant DevFeed: [Inside our effort to improve the Mintlify assistant]() Original publisher: [Read original article]() Author: Patrick Foster Published: 2025-12-12T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Artificial Intelligence](), [clickhouse](), [data](), [Large Language Model](), [Software]() Tags: [ai](), [analysis](), [clickhouse](), [customer](), [data](), [engineering](), [llm](), [model](), [pipeline](), [quality](), [query](), [responses](), [script](), [server](), [thread](), [trends]() ### AI overview This article explains how Mintlify analyzed and improved its assistant by rebuilding the feedback pipeline, moving conversation data into ClickHouse, and classifying negative interactions with an LLM. The analysis identified documentation search quality as the assistant's main weakness, while other responses were generally strong. ### Source excerpt A data-driven look at improving the assistant, powered by ClickHouse and deeper feedback analysis. ## Promise based Web Worker Messaging DevFeed: [Promise based Web Worker Messaging]() Original publisher: [Read original article]() Author: Stanko Published: 2025-11-03T00:00:00Z Content type: tutorial Language: en Sources: [Stanko Tadić]() Topics: [Promise](), [Messaging](), [Web](), [async/await](), [Code](), [Error Handling]() Tags: [async](), [await](), [code](), [error-handling](), [event](), [implementation](), [messaging](), [thread](), [web](), [worker]() ### AI overview This tutorial presents a Promise-based wrapper for Web Worker messaging. It explains how unique message identifiers map worker responses to stored promises, allowing the main thread to resolve or reject the corresponding promise and use async/await with simpler error handling. The same pattern can also be applied to Service Workers. ### Source excerpt If you've ever used Web Workers (or any other event-based communication), you probably noticed that this kind of code can be hard to read and reason about. You also have to implement some kind of identifier for each message to recognize which worker response corresponds to which request. To simplify that, we can write a small wrapper that lets us use Promises to communicate with Workers. I'll show you an example for Web Workers, but the same pattern can be applied to Service Workers as well. The resulting API looks like this: const workerResponse = await sendToWorker(data); I first used this approach in Pulsar, because I wanted to parse and execute the user's code in a Web Worker, but also wait for the worker to finish before providing data for the next frame. Implementation # The idea is fairly simple - before sending a message to the worker, we create a unique id and a promise. We store the promise in a map using the id as the key. Then we send an event to the worker, including both the data and the id, and return the promise to the caller. When the worker finishes its calculation, it sends back a message that includes the result and the same id. In the main thread, we listen for these messages. When one arrives, we use the id to find the corresponding promise in our map. Finally, based on the worker's result, we resolve or reject that promise. It might sound like a lot, but the code is actually quite straightforward: send-to-worker.jsCopy // Worker initialization const worker = new Worker("./path-to-your-worker.js"); // Map of promises const promises = {}; worker.addEventListener("message", (e) => { // Listen to worker messages and find the correct promise matching the id // Then resolve or reject it depending on the response if (e.data.error) { promises[e.data.id].reject(e.data.error); } else { promises[e.data.id].resolve(e.data.data); } // Remove the resolver reference delete promises[e.data.id]; }); // For identifiers it is safe to use a simple integer // whic [Next page]()