# node Published articles for node. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Kubernetes Architecture: Control Plane, Scheduler, and Kubelet DevFeed: [Kubernetes Architecture: Control Plane, Scheduler, and Kubelet]() Original publisher: [Read original article]() Author: Nimesha Jinarajadasa Published: 2026-09-17T06:25:02Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [Kubernetes](), [control-plane](), [api server](), [Containers](), [etcd](), [kubectl]() Tags: [api](), [api-server](), [containers](), [control-plane](), [controllers](), [etcd](), [kubectl](), [kubernetes](), [kubernetes-architecture](), [kubernetes-networking](), [node](), [scheduler]() ### AI overview A beginner-friendly tutorial explaining how Kubernetes maintains the desired state of containerized applications. It covers the control plane, API server, etcd, controllers, scheduler, and kubelet. ### Source excerpt Learn how Kubernetes works, from the control plane and scheduler to kubelet, pods, and Services, with simple answers to interview questions. ## Node.js 26.9.0 (Current) DevFeed: [Node.js 26.9.0 (Current)]() Original publisher: [Read original article]() Published: 2026-09-16T18:17:42Z Content type: release Language: en Sources: [Node.js Blog]() Topics: [Node.js](), [JavaScript](), [Open Source]() Tags: [crypto](), [javascript](), [node](), [node-js](), [open-source](), [openssl](), [version]() ### AI overview Node.js 26.9.0 is a current release with semver-minor additions and fixes across cryptography, module loading, Web Workers, benchmarking, builds, and diagnostics. ### Source excerpt Node.js® is a free, open-source, cross-platform JavaScript runtime environment that lets developers create servers, web apps, command line tools and scripts. ## How to Connect to HMRC's Making Tax Digital API: A Beginner's Guide DevFeed: [How to Connect to HMRC's Making Tax Digital API: A Beginner's Guide]() Original publisher: [Read original article]() Author: Solomon Amos Published: 2026-09-11T22:10:33Z Content type: tutorial Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [API](), [Security, Privacy and Abuse Prevention]() Tags: [api](), [apis](), [code](), [guide](), [hmrc](), [hmrc-tax-filing](), [hmrc-tax-returns](), [how-to](), [integration](), [mtd](), [node](), [oauth](), [tax](), [tax-return](), [typescript]() ### AI overview A beginner-friendly guide to connecting software to HMRC's Making Tax Digital API. It explains the MTD context, sandbox setup, OAuth 2.0 authentication, fraud prevention headers, and authenticated API calls using Node and TypeScript. ### Source excerpt If you write software for anyone who pays UK tax, sooner or later you'll need to talk to HMRC. Making Tax Digital (MTD) for Income Tax went live on 6 April 2026, and it's already mandatory for self-em ## How to Build an AI Chat App Interface With the Vercel AI SDK and Shadcn/ui DevFeed: [How to Build an AI Chat App Interface With the Vercel AI SDK and Shadcn/ui]() Original publisher: [Read original article]() Author: Vaibhav Gupta Published: 2026-09-11T16:21:29Z Content type: tutorial Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [vercel ai sdk](), [AI Chat](), [SDKs](), [Node.js]() Tags: [ai](), [app](), [how-to](), [llm](), [mcp](), [next-js](), [node](), [openai](), [react](), [shadcn-ai-chat-app](), [shadcn-ui](), [streaming](), [tailwind](), [typescript](), [ui](), [vercel](), [vercel-ai-sdk]() ### AI overview Tutorial for building a streaming AI chat interface in Next.js with the Vercel AI SDK and shadcn/ui. ### Source excerpt Every other AI product you open today has the same screen: a message list, a text box at the bottom, and words that stream in one token at a time. It looks simple, but it's not simple to build well. Y ## NVIDIA Personal AI Router Distributes AI Tasks across Local Compute DevFeed: [NVIDIA Personal AI Router Distributes AI Tasks across Local Compute]() Original publisher: [Read original article]() Author: Sergio De Simone Published: 2026-09-11T15:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [Local AI](), [Inference](), [GPU](), [Hardware]() Tags: [agent](), [agents](), [ai](), [ai-ml-data-engineering](), [architecture-design](), [compute](), [demo](), [development](), [gpu](), [inference](), [large-language-models](), [local](), [ml-data-engineering](), [news](), [node](), [nvidia](), [nvidia-pair-ai-task-router](), [open-source](), [orchestration](), [performance]() ### AI overview NVIDIA has introduced PAIR in beta, a local router that distributes inference requests across compatible computers for multi-agent AI workloads. It works with local inference services such as Ollama and LM Studio and selects a node based on model and engine requirements. ### Source excerpt NVIDIA Personal AI Router (PAIR), now available in beta, lets you combine the inference capacity of multiple computers on your local network and automatically distribute AI requests among them. It is primarily designed for local multi-agent AI workloads, where multiple independent model calls can otherwise overwhelm one GPU. By Sergio De Simone ## Kubernetes v1.37: Scheduler Preemption for In-Place Pod Resize (Alpha) DevFeed: [Kubernetes v1.37: Scheduler Preemption for In-Place Pod Resize (Alpha)]() Original publisher: [Read original article]() Author: Natasha Sarkar Published: 2026-09-10T18:30:00Z Content type: article Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [Containers]() Tags: [containers](), [cpu](), [feature](), [kubernetes](), [memory](), [node](), [resource](), [scale]() ### AI overview Kubernetes v1.37 adds an alpha scheduler-preemption feature for in-place Pod resizes. It can preempt lower-priority workloads to make capacity available for valid, higher-priority resize requests that are deferred on full nodes. ### Source excerpt In Kubernetes, resource allocation has historically been a static decision made during a Pod's initial scheduling and placement. With the graduation of the core in-Place Pod resize feature to General Availability in v1.35, application developers and cluster operators gained the powerful ability to dynamically adjust CPU and memory allocations of running containers without incurring disruptive restarts or application downtime. However, in-place resizing introduced a unique resource scheduling gap: if a running Pod requested a resource scale-up that exceeded the host node's allocatable headroom, the Kubelet was forced to mark the request as Deferred. The Pod would remain parked in this state indefinitely, waiting for resources on the node to naturally free up. To bridge this scheduling gap, Kubernetes v1.37 introduces scheduler preemption for in-place Pod resize (Alpha), behind the InPlacePodVerticalScalingSchedulerPreemption feature gate. This feature allows the Kubernetes scheduler to actively free up capacity on a fully-utilized node by preempting lower-priority workloads, enabling the pending in-place resizes of critical, higher-priority applications to succeed. The "deferred" resize challenge To understand why this preemption mechanism is needed, it is helpful to look at how Kubernetes handles running Pod resizing. When a user or controller (such as the Vertical Pod Autoscaler) updates the resource requests of an active container, the Kubelet evaluates whether the underlying node has enough spare allocatable capacity to fulfill the increase. If the node's resources are fully utilized and cannot satisfy the new limits, the Kubelet sets the container's resizeStatus (reported in the Pod's status.containerStatuses[]) to Deferred. Unlike an Infeasible resize request (which is immediately rejected because it exceeds physical machine boundaries, namespace limit ranges, or admission quotas) a Deferred status indicates that the request is valid but is temporarily unable t ## High-Throughput Structure Prediction with BioNeMo Inference Runtime DevFeed: [High-Throughput Structure Prediction with BioNeMo Inference Runtime]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-10T15:00:00Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [AI, ML & Data Engineering]() Tags: [bionemo](), [cuda](), [cuda-graphs](), [data-center-cloud](), [data-science](), [drug-discovery](), [gpu](), [healthcare-life-sciences](), [how-to](), [hpc-scientific-computing](), [inference](), [integration](), [kernels](), [model](), [models](), [node](), [nvidia](), [python](), [pytorch](), [resource](), [scale](), [simulation-modeling-design](), [tokenization](), [torch](), [tutorial](), [workflow]() ### AI overview A tutorial on using NVIDIA BioNeMo Inference Runtime to accelerate biomolecular structure-prediction models on GPUs. It covers the end-to-end Boltz2 workflow, PyTorch integration, input requirements, and Ray-based single-node throughput scaling. ### Source excerpt Biomolecular structure prediction is now often run at proteome scale, where the goal is to move an entire worklist through the pipeline efficiently. NVIDIA... ## The Machine With Many Faces: Post-Exploitation Identity Misuse in SPIFFE/SPIRE DevFeed: [The Machine With Many Faces: Post-Exploitation Identity Misuse in SPIFFE/SPIRE]() Original publisher: [Read original article]() Author: Eviatar Garzi Published: 2026-09-10T10:00:43Z Content type: article Language: en Sources: [Unit 42]() Topics: [Kubernetes]() Tags: [api](), [containers](), [cryptographic](), [identity](), [json](), [kubernetes](), [linux](), [malware](), [node](), [open-source](), [research](), [secrets](), [spiffe](), [spire](), [spoof](), [spoofing](), [threat-research](), [tool]() ### AI overview Research on a post-exploitation technique in which root access to a Kubernetes node can let an attacker spoof cgroup metadata used by SPIRE workload attestation, impersonate co-located workloads, and obtain SVIDs. ### Source excerpt Learn how root access on a compromised K8s node allows attackers to utilize SPIFFE/SPIRE metadata to spoof and harvest co-located workload identities. The post The Machine With Many Faces: Post-Exploitation Identity Misuse in SPIFFE/SPIRE appeared first on Unit 42. ## Kubernetes v1.37: Introducing Node Lifecycle Conditions DevFeed: [Kubernetes v1.37: Introducing Node Lifecycle Conditions]() Original publisher: [Read original article]() Author: Ryan Hallisey Published: 2026-09-09T18:30:00Z Content type: release Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [releases]() Tags: [apis](), [automation](), [feature](), [kubernetes](), [node](), [release](), [releases]() ### AI overview Kubernetes v1.37 introduces well-known Node lifecycle conditions for communicating drain, maintenance, and graceful shutdown status. The alpha feature gate is disabled by default and currently does not cause core components to consume or enforce these conditions. ### Source excerpt Kubernetes has many ways to describe what is happening on a Node. Readiness, taints, Pod state, labels, annotations, and provider-specific APIs each expose part of the picture. What has been missing is a shared, Kubernetes-owned way to say that a Node is draining, undergoing maintenance, or undergoing Graceful Node Shutdown. Kubernetes v1.37 introduces five well-known Node conditions that provide that description: DrainInProgress Drained MaintenancePlanned MaintenanceInProgress GracefulNodeShutdownInProgress The new Node lifecycle conditions Condition What it reports DrainInProgress The Node is actively being drained according to the administrator's chosen drain criteria. Drained The Node has reached the drain criteria selected by the administrator. MaintenancePlanned The Node is expected to undergo a change in the future. MaintenanceInProgress The Node is actively undergoing maintenance. GracefulNodeShutdownInProgress Graceful Node Shutdown is determined to be in progress on the Node. Maintenance can include hardware or software rollout, remediation, decommissioning, or debugging. Whether maintenance requires a drain depends on its impact. A Kubernetes upgrade usually should follow a drain, while a kernel live patch might not need one. Like other Node conditions, each lifecycle condition uses status to report whether the observation is active: True: the lifecycle state is currently observed. False: the lifecycle state is not currently observed. Unknown: Kubernetes cannot determine whether the lifecycle state is active. The reason provides a stable, machine-readable cause for the current status, and message can provide additional human-readable detail. For example, an authorized maintenance controller could publish: # Node .status excerpt status: conditions: - type: MaintenancePlanned status: "True" reason: MaintenanceWindow lastTransitionTime: "2026-12-09T12:00:00Z" message: "Hardware maintenance is scheduled for this Node" What changes in Kubernetes v1.37 The v1.3 ## Integrate Deepgram Flux with Twilio's Conversation Relay DevFeed: [Integrate Deepgram Flux with Twilio's Conversation Relay]() Original publisher: [Read original article]() Author: Dhruv Patel Published: 2026-09-08T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [flux](), [asr](), [Tutorial](), [Latency](), [Node.js](), [WebSocket](), [Streaming]() Tags: [developer-insights](), [flux](), [latency](), [node](), [speech](), [streaming](), [transcription](), [tutorial](), [websocket]() ### AI overview This tutorial shows how to integrate Deepgram Flux with Twilio's Conversation Relay in Node.js. Flux combines speech transcription and turn detection, with configurable end-of-turn confidence, and is described as reducing response latency and false interruptions. ### Source excerpt Integrate Deepgram Flux with Twilio ConversationRelay in Node.js for faster turn detectio, and tunable end-of-turn control. ## Build a real-time market data app with ClickHouse and Massive DevFeed: [Build a real-time market data app with ClickHouse and Massive]() Original publisher: [Read original article]() Author: Lionel Palacin Published: 2026-09-04T00:00:00Z Content type: tutorial Language: en Sources: [ClickHouse Blog]() Topics: [App](), [data](), [Node.js](), [Back end](), [API keys]() Tags: [analytics](), [api](), [app](), [backend](), [clickhouse](), [compression](), [data](), [demo](), [events](), [how-to](), [latency](), [low-latency](), [node](), [node-js](), [react](), [real-time](), [rest-api](), [storage](), [streams](), [visualization]() ### AI overview A tutorial for building a real-time market-data application that ingests, stores, and queries trade and quote ticks with Massive and ClickHouse, using Node.js for backend work and React for live visualization. ### Source excerpt Learn how to build a real-time financial analytics application with Massive and ClickHouse that scales to thousands of events per second. ## Build a Video API with Twilio Programmable Video, Node.js, TypeScript, and Express DevFeed: [Build a Video API with Twilio Programmable Video, Node.js, TypeScript, and Express]() Original publisher: [Read original article]() Author: Mia Adjei Published: 2026-08-31T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [API](), [Node.js](), [Express](), [TypeScript](), [SDKs]() Tags: [api](), [api-js](), [api-keys](), [api-node](), [api-nodejs](), [api-twilio](), [build](), [build-api](), [developer-insights](), [env-file-security](), [express](), [how-to](), [javascript-api](), [node](), [node-js](), [nodejs](), [nodejs-api](), [tutorial](), [twilio-api](), [twilio-programmable-video](), [typescript](), [use-api-with-javascript](), [video](), [video-api](), [video-javascript](), [video-js]() ### AI overview A tutorial showing how to build an API that creates and manages video rooms programmatically using Twilio Programmable Video, Node.js, TypeScript, and Express. ### Source excerpt Learn how to create and manage video chat rooms programmatically using Twilio Programmable Video and Node.js. ## How to verify WorkOS access tokens in your own API DevFeed: [How to verify WorkOS access tokens in your own API]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-08-28T00:00:00Z Content type: tutorial Language: en Sources: [WorkOS Blog]() Topics: [API](), [Android](), [SDKs](), [servers](), [client]() Tags: [android](), [api](), [how-to](), [http](), [jwks](), [node]() ### AI overview This tutorial explains how to verify WorkOS access tokens in a Node API, using an Android client as the example. It covers bearer-token handling, JWKS-based signature verification, claim extraction, caller identity, and distinct responses for invalid tokens, temporary verification failures, and expired tokens. ### Source excerpt Using an Android client and a Node API, including the JWKS failure mode that quietly returns the wrong status code ## Bun 1.4 lands on Appwrite: the first Bun written in Rust DevFeed: [Bun 1.4 lands on Appwrite: the first Bun written in Rust]() Original publisher: [Read original article]() Author: Atharva Deosthale Published: 2026-08-21T00:00:00Z Content type: release Language: en Sources: [Appwrite Blog]() Topics: [Bun](), [Appwrite](), [Rust](), [OpenTelemetry](), [Playwright]() Tags: [announcements](), [build](), [bun](), [node](), [npm](), [opentelemetry](), [playwright](), [release](), [rust]() ### AI overview Bun 1.4 is available on Appwrite Cloud for Appwrite Functions and Sites. The release is the first Bun version written in Rust and includes improved Node.js 26 compatibility, faster startup and installs, lower memory and idle CPU use, native Web Streams, and new built-in APIs. The article also describes upgrade considerations and benchmarks against Bun 1.3 and Node 26. ### Source excerpt Bun 1.4 is now available as a runtime for Appwrite Functions and as a build runtime for Appwrite Sites. We benchmarked it against Bun 1.3 and Node 26. ## Bun 1.4 is now available in Vercel Functions DevFeed: [Bun 1.4 is now available in Vercel Functions]() Original publisher: [Read original article]() Author: Tom Lienard Published: 2026-08-20T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Bun](), [Vercel](), [Rust](), [Node.js](), [WebSocket](), [Zig](), [Hono](), [Next.js]() Tags: [2](), [bun](), [compatibility](), [compute](), [cpu](), [features](), [frameworks](), [next-js](), [node](), [node-js](), [performance](), [release](), [rust](), [support](), [update](), [vercel](), [zig]() ### AI overview Vercel Functions now support Bun 1.4, which rewrites Bun from Zig to Rust and includes resolved issues, additional Node.js compatibility tests, new features, and performance improvements. Bun runs on Fluid compute, supports Active CPU pricing and WebSockets, and works with frameworks including Next.js and Hono. Upgrading is an explicit opt-in because of breaking changes. ### Source excerpt Vercel Functions now support the new Bun 1.4 release, a rewrite of Bun from Zig to Rust, with over 2,900 issues resolved, more than 1,500 additional Node.js compatibility tests passing, and new features and performance improvements. Bun on Vercel Functions: Runs on Fluid compute with Active CPU pricing Supports WebSockets and Bun.serve() Supports common frameworks such as Next.js, Elysia, and Hono To update from the previous Bun version, set bunVersion to 1.4.x in vercel.json. Upgrading is an explicit opt-in because Bun 1.4 has several breaking changes. Review the breaking changes and update your application before upgrading. Learn more about using Bun on Vercel in the runtime documentation. Read more ## Query Neon backend logs DevFeed: [Query Neon backend logs]() Original publisher: [Read original article]() Author: Andre Landgraf Published: 2026-08-18T12:00:00Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Back end](), [observability](), [log management](), [Command-line interface](), [MCP Server](), [Serverless](), [Server](), [Node.js](), [Amazon S3](), [SDKs]() Tags: [api](), [backend](), [cli](), [logs](), [mcp-server](), [node](), [observability](), [product](), [s3](), [tool]() ### AI overview Neon adds branch-scoped access to backend logs from Neon Functions and Object Storage outside the Console. The logs can be queried through the CLI, MCP server, Logs API, SDK, or Loki endpoints, with filters and raw LogQL support. ### Source excerpt We keep expanding our backend observability - the most recent addition: you can now query backend logs outside the Console! neon logs reads what Neon Functions and Object Storage emit on a branch, with filters for source, severity, and message text. ## On Rails -- Joanna Wang: Code Is Cheap Now; Developers Still Valuable DevFeed: [On Rails -- Joanna Wang: Code Is Cheap Now; Developers Still Valuable]() Original publisher: [Read original article]() Author: Rails Foundation Published: 2026-08-18T00:00:00Z Content type: article Language: en Sources: [Ruby on Rails: Compress the complexity of modern web apps]() Topics: [AI-assisted coding](), [AI Bots]() Tags: [agent](), [agentic](), [ai](), [code](), [data](), [developers](), [go](), [java](), [node](), [orchestration](), [podcast](), [python](), [ruby](), [software](), [tools]() ### AI overview A podcast episode with Joanna Wang of Sixfold about AI underwriting tools, workflow orchestration, agentic development, and the continuing value of developers. ### Source excerpt Joanna Wang is a senior software engineer at Sixfold, where the team builds AI underwriting tools that help insurance companies gather data and assess risk. She came to Ruby on Rails after working across Java, Go, Python, and Node. Robby and Joanna get into why the homegrown orchestration they built on state machines and callbacks turned brittle, what moving to Hatchet changed, and the tradeoffs of leaning on a gem that is no longer maintained. They also talk about what happened when the team went fully agentic, and why Rails magic is easier to understand when an agent can trace it for you. ## Custom MFA factor: send a second factor through any channel DevFeed: [Custom MFA factor: send a second factor through any channel]() Original publisher: [Read original article]() Author: Atharva Deosthale Published: 2026-08-14T00:00:00Z Content type: release Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [MFA](), [Authentication](), [API](), [Node.js](), [Rust]() Tags: [announcements](), [api](), [authentication](), [backend](), [console](), [mfa](), [node](), [rust](), [security](), [voice](), [whatsapp]() ### AI overview Appwrite introduces a custom MFA factor that generates and verifies authentication codes while allowing applications to deliver them through channels such as WhatsApp, voice calls, or internal providers. The article explains how to retrieve the code through a server-side function and deliver it securely. ### Source excerpt Appwrite now supports a custom MFA factor. Appwrite generates and verifies the code, and your function delivers it through WhatsApp, a voice call, or any provider you choose. ## One-click upgrade for deprecated Node.js versions DevFeed: [One-click upgrade for deprecated Node.js versions]() Original publisher: [Read original article]() Author: Ali Smesseim Published: 2026-08-13T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Node.js](), [Vercel]() Tags: [node](), [node-js](), [update](), [upgrade](), [vercel]() ### AI overview Vercel now provides a one-click option to upgrade all team projects running Node.js 20 or earlier to Node.js 24 from the Vercel Dashboard. ### Source excerpt Team owners and members can now upgrade all projects using Node.js 20 or earlier to Node.js 24 with one click from the Vercel Dashboard. This updates the Node.js version in project settings. If your project also defines a version in package.json, you'll need to update it manually. Existing deployments are not affected. View and upgrade deprecated Node.js projects now. Read more ## Neon Functions: backend logic next to your data DevFeed: [Neon Functions: backend logic next to your data]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2026-08-12T12:00:00Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Back end](), [Node.js](), [Database](), [Serverless](), [WebSocket](), [Cloud]() Tags: [backend](), [database](), [hosting](), [network](), [node](), [node-js](), [product](), [serverless](), [vpc]() ### AI overview Neon Functions provide long-running Node.js 24 backend compute deployed beside a Neon Postgres branch. They automatically receive database and related Neon service credentials, reducing network hops and supporting streaming, WebSockets, SSE, and persistent connection pools. ### Source excerpt Neon Functions are Node.js 24 compute you deploy onto a Neon branch, in the same region as your Lakebase Postgres database, with DATABASE_URL injected automatically. They're long-running enough that agents can stream for minutes and WebSockets or SSE can stay open while data flows. ## Instrument serverless apps with agentic onboarding DevFeed: [Instrument serverless apps with agentic onboarding]() Original publisher: [Read original article]() Author: Rohan Agarwal; Piyali Banerjee Published: 2026-08-10T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Serverless](), [AWS Lambda](), [azure container apps](), [Cloud Run](), [Command-line interface](), [MCP Server](), [Artificial Intelligence](), [Claude Code](), [cursor](), [Node.js](), [Terraform]() Tags: [agentic](), [ai](), [aws](), [aws-lambda](), [azure](), [azure-container-apps](), [claude-code](), [cli](), [cursor](), [google-cloud](), [google-cloud-run](), [mcp-server](), [node](), [serverless](), [serverless-monitoring](), [terraform]() ### AI overview Datadog's agentic onboarding helps instrument serverless applications across AWS Lambda, Google Cloud Run, and Azure Container Apps. Developers can use an AI assistant connected through the Datadog MCP Server or run the AI Setup CLI to inspect projects, adapt setup to existing deployment tools and runtimes, and prepare configuration changes for review. ### Source excerpt Use Datadog agentic onboarding to instrument AWS Lambda, Google Cloud Run, and Azure Container Apps from an AI assistant or CLI. ## Geometry Nodes Physics DevFeed: [Geometry Nodes Physics]() Original publisher: [Read original article]() Author: Jacques Lucke Published: 2026-07-30T14:52:49Z Content type: article Language: en Sources: [Blender]() Topics: [Simulation](), [Framework](), [systems]() Tags: [blender](), [collection](), [experimental](), [features](), [general-development](), [geometry-nodes](), [gravity](), [lts](), [mesh](), [node](), [physics](), [procedural](), [systems](), [vectors](), [workflow]() ### AI overview This article describes Blender 5.2 LTS's new experimental hair and cloth dynamics system built with Geometry Nodes. It explains the declarative XPBD simulation framework, cloth and hair workflows, geometry bundles, and customizable effectors such as colliders, custom forces, and custom behavior closures. ### Source excerpt Geometry Nodes Physics in Blender 5.2 LTS and beyond. ## How Yandex Cloud built and open-sourced Farm for preview environments DevFeed: [How Yandex Cloud built and open-sourced Farm for preview environments]() Original publisher: [Read original article]() Author: DakEnviy0 (Яндекс, Yandex Cloud & Yandex Infrastructure) Published: 2026-07-30T07:29:36Z Content type: article Language: ru Sources: [Яндекс - Как мы делаем Яндекс / Статьи]() Topics: [Docker](), [Kubernetes](), [Self-hosted](), [Development](), [Node.js]() Tags: [dev](), [docker](), [farm](), [frontend](), [js](), [kubernetes](), [node](), [node-js](), [preview](), [preview-87a227230297](), [self-hosted](), [tag-4004cf5948d3](), [tag-92292b2c626f](), [tag-e6d9cc1f0757]() ### AI overview The article describes how Yandex Cloud developed Farm, a service that creates preview environments for pull requests. It traces the system's evolution from a self-hosted script on one virtual machine to an orchestrator using Docker and Kubernetes, and explains the motivation for open-sourcing it. ### Source excerpt Каждый пул-реквест хочется не просто проверить тестами, а показать вживую -- дизайнеру, менеджеру, соседней команде, чтобы все они смогли потыкаться в UI -- порадоваться, понаходить баги -- порасстраиваться. Казалось бы, что сложного: поднял окружение и дал ссылку. Но когда пул-реквесты сыпятся десятками в день, а команд целое множество, "просто поднять окружение" превращается в отдельный инфраструктурный проект. Привет, Хабр! Меня зовут Михаил Гольбах, я ведущий разработчик интерфейсов Yandex Cloud. Уже несколько лет мы с командой развиваем Ферму -- сервис, который поднимает preview-окружение под каждый пулл-реквест. В этой статье расскажу, как Ферма выросла из простого self-hosted-скрипта на одной виртуальной машине в оркестратор на Docker и Kubernetes и почему в итоге мы открыли её код. Читать далее ## How to build an invoice generator app in Webflow Cloud with Next.js and SQLite DevFeed: [How to build an invoice generator app in Webflow Cloud with Next.js and SQLite]() Original publisher: [Read original article]() Author: Ismail Ajagbe Published: 2026-07-25T00:00:00Z Content type: tutorial Language: en Sources: [Webflow Blog]() Topics: [webflow](), [Next.js](), [SQLite](), [CRUD](), [Workers](), [JavaScript](), [Node.js](), [npm](), [GitHub]() Tags: [app](), [cloud](), [code](), [data](), [github](), [guides](), [how-to](), [infrastructure](), [javascript](), [next-js](), [node](), [node-js](), [sqlite](), [webflow](), [workers]() ### AI overview A tutorial for building an invoice generator in Webflow Cloud with Next.js and SQLite. It covers storing invoice records, creating and listing them through route handlers, generating downloadable PDFs at the edge with a pure-JavaScript library, building the form, and deploying the app. ### Source excerpt Learn how to build an invoice generator app in Webflow Cloud with a Next.js project, a SQLite database, and edge-compatible PDF generation using pdf-lib. [Next page]()