# monitor A computer display that connects through interfaces such as HDMI, DisplayPort, USB-C, or VGA. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## HKC reveals an ultra-wide curved monitor with split-screen modes for multitasking and gaming DevFeed: [HKC reveals an ultra-wide curved monitor with split-screen modes for multitasking and gaming]() Original publisher: [Read original article]() Author: Gaurav Sood Published: 2026-09-15T15:20:17Z Content type: news Language: en Sources: [Yanko Design]() Topics: [monitor](), [cpu](), [dell]() Tags: [4k](), [accessories](), [accessories-technology-curved-monitors](), [curved](), [display](), [kvm](), [monitor](), [monitors](), [multitasking](), [port](), [technology](), [ultra-wide](), [usb]() ### AI overview HKC has revealed the Tianqi 43H180C ultra-wide curved monitor, featuring a 24:9 aspect ratio, 5,760 x 2,160 resolution, and a 180 Hz refresh rate. It can operate as one large display, split into two zones, or divided into three zones. ### Source excerpt HKC debuts a 48.3-inch 4K curved monitor that splits into two or three sections for power users There are no limits as to how wide you can go with a desktop monitor, especially for power users and pro gamers. You can have... ## Redefining Digital Resilience in the AI Era DevFeed: [Redefining Digital Resilience in the AI Era]() Original publisher: [Read original article]() Author: Kamal Hathi Published: 2026-09-10T17:00:15Z Content type: news Language: en Sources: [Cisco Blogs]() Topics: [Resilience](), [Artificial Intelligence](), [data](), [Architecture & Design](), [Security](), [SOC](), [monitor]() Tags: [agentic-ai-security](), [agentic-ops](), [agentic-security](), [ai](), [ai-agents](), [autonomous](), [cost](), [digital-resilience](), [executive-platform](), [governance](), [monitor](), [observability](), [resilience](), [scale](), [security](), [soc](), [speed](), [workflows]() ### AI overview Splunk is evolving its data platform for the AI era, focusing on digital resilience, trusted autonomous agents, machine-speed security operations, and economically governed AI workflows. ### Source excerpt Splunk is evolving for the AI era - removing constraints to help customers achieve digital resilience and leverage AI with speed, scale and trust. ## KDE Plasma 6.8 Beta Released With Many Great Improvements, Kup Backup Scheduler DevFeed: [KDE Plasma 6.8 Beta Released With Many Great Improvements, Kup Backup Scheduler]() Original publisher: [Read original article]() Author: Michael Larabel Published: 2026-09-10T16:39:24Z Content type: release Language: en Sources: [Phoronix]() Topics: [Wayland](), [Multi-GPU](), [GPU](), [monitor]() Tags: [backup](), [desktop](), [desktop-linux](), [gpu](), [linux-benchmarking](), [linux-hardware-benchmarks](), [linux-hardware-reviews](), [linux-how-to](), [linux-performance](), [linux-server-benchmarks](), [monitor](), [multi-gpu](), [open-source-graphics](), [phoronix](), [phoronix-test-suite](), [release](), [remote](), [server](), [tool](), [ubuntu-benchmarks](), [ubuntu-hardware]() ### AI overview KDE Plasma 6.8 Beta introduces improvements to Wayland support, vRAM usage, remote desktops, multi-GPU and multi-monitor handling, theming, and other desktop functionality. It also includes Kup as the Plasma desktop backup scheduler. ### Source excerpt Ahead of the stable release of Plasma 6.8 due out on 14 October that also marks the 30th anniversary of the KDE project, out today is the much anticipated beta release... ## DIY ESP32-P4 weather station & air quality monitor connects to LoRa and ESP-NOW sensors, various weather APIs DevFeed: [DIY ESP32-P4 weather station & air quality monitor connects to LoRa and ESP-NOW sensors, various weather APIs]() Original publisher: [Read original article]() Author: Jean-Luc Aufranc (CNXSoft) Published: 2026-09-03T04:55:46Z Content type: article Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [ESP32-P4](), [ESP32](), [ESP-NOW](), [lora](), [Hardware](), [monitor](), [Embedded Systems](), [dashboards]() Tags: [arduino](), [ble](), [c-c-plus-plus](), [display](), [diy](), [esp-now](), [esp32](), [esp32-p4](), [espressif](), [hardware](), [iot](), [lora](), [monitor](), [sensors](), [touchscreen](), [waveshare](), [wifi](), [wifi-6](), [wireless]() ### AI overview This article describes an ESP32-P4 weather station and air quality monitor built from off-the-shelf boards. It uses a 10.1-inch dashboard, a Sensirion SEN66 multisensor, and LoRa and ESP-NOW sensor nodes, with optional weather data from several APIs and no required cloud account. ### Source excerpt Harald Kreuzer has built an ESP32-P4 weather station and air quality monitor that features a 10.1-inch dashboard display and a built-in Sensirion SEN66 sensor for particulate matter, CO2, VOC, and NOX, and connects to wireless LoRa and ESP-NOW sensors. The project is entirely made of off-the-shelf boards, so no custom hardware is used, and it should be relatively easy to reproduce. It doesn't require any cloud or user account, although it can connect to a choice of weather APIs (Open-Meteo, OpenWeatherMap or Visual Crossing) to display weather forecasts. The build is fully documented in a long blog post, so we'll highlight the key features of the project in this article. Hardware specifications for the main unit: Based on ESP32-P4-Module-DEV-KIT-C Credit card-sized ESP32-P4-Module-DEV-KIT SBC based on an ESP32-P4NRW32 module with ESP32-P4 with 32MB PSRAM and ESP32-C6 for WiFi and BLE 10.1-inch IPS panel with 1280 x 800 resolution, 800:1 contrast ratio, [...] The post DIY ESP32-P4 weather station & air quality monitor connects to LoRa and ESP-NOW sensors, various weather APIs appeared first on CNX Software - Embedded Systems News. ## The prompts only the Postman AI Engineer can answer DevFeed: [The prompts only the Postman AI Engineer can answer]() Original publisher: [Read original article]() Author: Talia Kohan Published: 2026-08-20T16:00:00Z Content type: article Language: en Sources: [Postman Blog]() Topics: [Claude](), [Postman](), [Graphs](), [API](), [OpenAPI Specification](), [monitor](), [React]() Tags: [ai](), [ai-agents](), [api](), [apis](), [general](), [monitor](), [openapi](), [postman-ai-engineer](), [react]() ### AI overview This Postman Blog article presents the Postman AI Engineer as a natural-language interface over the Postman Context Graph. It describes prompts that trace identifiers across APIs, collections, runtime monitor results, repositories, and React dashboards, as well as prompts that expose specification-versus-code drift and three-way discrepancies involving live server responses. ### Source excerpt The Postman AI Engineer prompts that trace an ID across your APIs, catch three-way drift, and auto-write a PR review from the graph. The post The prompts only the Postman AI Engineer can answer appeared first on Postman Blog. ## \[CVE\] \[URGENT\] Squid v19.2.6 and Tentacle v20.2.4 released DevFeed: [\[CVE\] \[URGENT\] Squid v19.2.6 and Tentacle v20.2.4 released]() Original publisher: [Read original article]() Author: Patrick Donnelly Published: 2026-08-19T00:00:00Z Content type: release Language: en Sources: [Ceph Blog]() Topics: [releases](), [Authentication](), [Linux](), [client](), [monitor]() Tags: [authentication](), [blog-post](), [cve](), [cves](), [en-article](), [en-blog-post](), [errors](), [linux](), [process](), [release](), [releases](), [rest](), [rgw](), [squid](), [tentacle](), [upgrade]() ### AI overview The Ceph project released Tentacle 20.2.4 and Squid 19.2.6 as hotfixes addressing four CVEs. The article urgently recommends upgrading and explains changes to CephX key types, daemon-key rotation, authentication controls, recovery procedures, and multisite RGW request signing. ### Source excerpt The Ceph project has released Tentacle 20.2.4 and Squid 19.2.6 hotfixes for four CVEs across several components. This is the sixth backport release in the Squid series. This is the fourth backport release in the Tentacle series. We strongly recommend that all Ceph operators upgrade to one of these releases as soon as possible. Release Date ¶ August 19, 2026 Critical Upgrade Steps ¶ The fix for CVE-2025-30156 introduces a new CephX key type, aes256k. This is the first time Ceph has introduced a new key type for CephX credentials. Therefore, a new procedure exists for upgrading and rotating Ceph daemon keys as part of this CVE. Before upgrading a Ceph cluster, the operator should familiarize themselves with the procedure to upgrade CephX keys. These steps are for package-based deployments of Ceph. In other sections, the document also includes new information about key rotation procedures, monitor authentication controls, and emergency recovery procedures. Deployments using cephadm will automate the process except for client keys. You may notice that Cephadm spends more time than normal on the upgrade after updating all daemon images. This is due to a new process rotating the OSD and MDS keys. Please be patient. There are plans to improve this in the future. Deployments using Rook will also automate rotation of some client keys with some exclusions. Look to the Rook project's announcement for more details. Client and kernel upgrades are recommended to support aes256k. Note that upstream Linux kernel client support began in kernel 7.0 and has been backported to CentOS Stream 9 and 10. Check with your distribution vendor for backported key support before rotating client keys used by the kernel. As part of upgrading a Ceph cluster, six new health warnings and errors will be generated. This is normal. As part of the process to upgrade/rotate entity keys, you will address the warnings and errors as you go. These are documented beginning here. The CephX documentation has bee ## powa-archivist 5.3.0 is out! DevFeed: [powa-archivist 5.3.0 is out!]() Original publisher: [Read original article]() Published: 2026-08-17T00:00:00Z Content type: release Language: en Sources: [PostgreSQL news]() Topics: [PostgreSQL](), [releases](), [benchmarking](), [monitor](), [Graphs](), [real-time](), [GitHub]() Tags: [bugs](), [changelog](), [contributors](), [documentation](), [github](), [graphs](), [metrics](), [monitor](), [performance](), [postgresql](), [real-time](), [release](), [releases]() ### AI overview The PoWA team announces powa-archivist 5.3.0, a PostgreSQL Workload Analyzer extension that collects and aggregates metrics from multiple PostgreSQL instances, provides real-time charts and graphs for monitoring and tuning servers, and suggests index optimizations. The release also includes a fix for PostgreSQL 19 compatibility. ### Source excerpt Tainan, Taiwan - Sun 16 Aug 2026 powa-archivist 5.3.0 The PoWA team is pleased to announce the release of the version 5.3.0 of powa-archivist, the core extension of the PoWA project. PoWA (PostgreSQL Workload Analyzer) is a performance tool, compatible with all supported PostgreSQL versions. It allows to collect and aggregate metrics gathered from multiple PostgreSQL instances using various extensions covering all parts of PostgreSQL and provides real-time charts and graphs to help monitor and tune your servers. It also suggest optimizations, like global or per-query index suggestions, to easily improve performances. Misc Fix pg19 compatibility with pg19beta2 pg_stat_lock.wait_time datatype change (Julien Rouhaud) Links & Credits Thank to the users who reported bugs or submitted patches, they are all cited in the CHANGELOG file and the CONTRIBUTORS file. powa-archivist is an open project. Any contribution to build a better tool is welcome. You just have to send your ideas, features requests or patches using the github repository at github.com/powa-team/powa-archivist. Links Documentation: powa.readthedocs.io/ Download: github.com/powa-team/powa-archivist/releases Bug tracker: github.com/powa-team/powa-archivist/issues ## AI SRE: Cut MTTR in Half with Autonomous Incident Resolution DevFeed: [AI SRE: Cut MTTR in Half with Autonomous Incident Resolution]() Original publisher: [Read original article]() Author: Matar Peles Published: 2026-08-10T11:34:38Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [site-reliability-engineering](), [incident](), [Artificial Intelligence](), [monitor](), [dashboards](), [Traces](), [archive search](), [Pull Request](), [codex](), [cursor]() Tags: [agent](), [ai](), [codex](), [cursor](), [dashboards](), [datadog](), [incident](), [monitor](), [monitoring](), [on-call](), [sre](), [traces](), [workflow]() ### AI overview This developer article describes an autonomous incident-resolution workflow built in Port. It argues that incident response time is largely spent reconstructing context from alerts, logs, dashboards, traces, ownership data, recent changes, and runbooks. The proposed agent-based workflow aims to use that full context to triage, diagnose, and fix production incidents, with a reported 50% reduction in MTTR. The supplied text ends during a discussion of why simply routing alerts to coding agents can fail. ### Source excerpt See how an SRE agent workflow cuts MTTR in half, using full context to triage, diagnose, and fix incidents autonomously, all the way to a RCA. ## btop: monitoriza tu sistema en terminal DevFeed: [btop: monitoriza tu sistema en terminal]() Original publisher: [Read original article]() Author: Antonio Pérez Published: 2026-08-01T10:00:00Z Content type: tutorial Language: es Sources: [tengoping.com]() Topics: [monitor](), [Terminal](), [Command-line interface](), [Linux](), [C++]() Tags: [c-plus-plus](), [linux](), [monitor](), [terminal]() ### AI overview A practical Spanish-language guide to btop, a terminal resource monitor for Linux. It covers installation, real-time CPU, memory, disk, and network monitoring, process management, interface customization, and essential keyboard shortcuts. ### Source excerpt Guía práctica de btop, el monitor de recursos para terminal: instalación, atajos de teclado esenciales y personalización básica. ## You Don't Need to Buy a Raspberry Pi Monitor DevFeed: [You Don't Need to Buy a Raspberry Pi Monitor]() Original publisher: [Read original article]() Author: Patrick Fromaget Published: 2026-07-07T06:13:46Z Content type: article Language: en Sources: [RaspberryTips]() Topics: [monitor](), [ssh](), [GUI](), [servers](), [Virtual Private Network](), [browser](), [Jellyfin]() Tags: [android](), [browser](), [gui](), [jellyfin](), [monitor](), [nas](), [quick-tips](), [raspberry-pi](), [server](), [ssh]() ### AI overview A dedicated monitor is unnecessary for most Raspberry Pi projects. The article explains that Raspberry Pi Imager can automate initial setup and that users can connect remotely through SSH, VNC, or Raspberry Pi Connect. A monitor is mainly useful for desktop use, dashboards, or as a convenience for a dedicated project space. ### Source excerpt Raspberry Pi starter kits are already getting pretty expensive these days, and it's easy to think you need everything to get started: a case, keyboard, mouse, and... a dedicated monitor. Well, in most cases you don't really need any of that stuff. You'll only need a Raspberry Pi monitor in a few specific situations, like... ## Recover the Ceph Monitor Store Using OSDs DevFeed: [Recover the Ceph Monitor Store Using OSDs]() Original publisher: [Read original article]() Author: Eugen Block, crossposted by Anthony D'Atri Published: 2026-07-04T00:00:00Z Content type: article Language: en Sources: [Ceph Blog]() Topics: [ceph](), [monitor](), [Script](), [Containers](), [log management]() Tags: [blog](), [blog-post](), [ceph](), [containers](), [en-article](), [en-blog-post](), [how-to](), [logging](), [logs](), [mon](), [monitor](), [recovery]() ### AI overview This blog post presents a general procedure for recovering a failed Ceph Monitor store by collecting osdmaps from existing OSDs, with additional considerations for cephadm-managed container deployments. It automates osdmap collection and basic logging while leaving the store rebuild and client authentication steps for careful manual inspection. The procedure applies only to non-encrypted OSDs, and the article emphasizes the importance of backing up dmcrypt/LUKS keys and reviewing host logs. ### Source excerpt Introduction ¶ A few weeks ago I helped a Ceph user to recover his broken cluster (see this thread). Basically, after his Monitors stopped working he re-deployed a new cluster with the same Ceph FSID and attached the existing OSDs to the re-deployed hosts. But it's not that easy to re-activate those OSDs because the new Monitors don't have the old osdmap, hence they don't know anything about the existing OSDs. So how did we fix that? This scenario can be considered a total Monitor store failure. There's a documented procedure in the upstream docs, unfortunately it's written for non-cephadm clusters and doesn't contain many details about subsequent steps. When Ceph daemons run within containers there are more things to consider. So I decided to write this blog post and add some more details to the procedure, targeting mainly clusters managed by cephadm. But the recovery procedure doesn't specifically require cephadm-specific commands, so it can be considered as a general guideline how to recover from a Monitor store loss, just with some extra details about cephadm deployments. This procedure only works for non-encrypted OSDs. If you are using dmcrypt (LUKS) OSDs, make sure you have a backup of the keys, otherwise your data is lost forever! But there is some development, a user in Slack pointed me to this PR which adds a backup mechanism for Monitors, probably available in the upcoming Umbrella release. Note that the PR also contains this statement: Monitor backups complement, but do not replace, the existing Monitor recovery procedures The procedure covered by said docs is already written in script form, so I used that as a template and extended it for cephadm usage and included some very basic logging. It collects the osdmaps from all OSDs and contains the necessary considerations regarding containers. I decided to automate only the osdmap collection, not all required steps of the store rebuild procedure (e. g. Monitor store rebuild, client auth, etc.) because the r ## How the Usage app uses Sentry to detect crashes, silent errors, and build regressions DevFeed: [How the Usage app uses Sentry to detect crashes, silent errors, and build regressions]() Original publisher: [Read original article]() Author: Dan Mindru; Oleh Stasula Published: 2026-07-02T09:00:00Z Content type: article Language: en Sources: [Sentry Blog]() Topics: [App](), [monitor](), [Processes](), [iphone](), [data]() Tags: [app](), [apple](), [dependency](), [errors](), [guest-post](), [iphone](), [mac](), [memory](), [monitor](), [network](), [process](), [sentry]() ### AI overview This guest post explains how the Usage system activity monitor uses Sentry to detect crashes, silent errors, build issues, and user feedback problems. The app runs across iPhone, iPad, and Mac and depends partly on undocumented APIs, so OS updates can change data structures without notice. Separate Sentry projects track the app's cooperating components and their failure modes. ### Source excerpt How the Usage app uses Sentry to catch crashes, silent errors, and build regressions before 1.6 million users notice. ## Automated Schema Evolution in Pinterest's Next-Generation DB Ingestion Framework DevFeed: [Automated Schema Evolution in Pinterest's Next-Generation DB Ingestion Framework]() Original publisher: [Read original article]() Author: Pinterest Engineering Published: 2026-06-24T18:01:01Z Content type: article Language: en Sources: [Pinterest Engineering Blog - Medium]() Topics: [schema-evolution](), [Apache Iceberg](), [Automation](), [Databases](), [Apache Spark](), [Kafka](), [Pull Request](), [Code generation](), [datasets](), [monitor](), [Provisioning]() Tags: [automation](), [code-generation](), [datasets](), [engineering](), [icebergs](), [kafka](), [monitor](), [pinterest](), [process](), [schema-evolution](), [software](), [spark](), [storage]() ### AI overview Pinterest describes an automated schema-evolution framework for its CDC-based database ingestion platform, which uses Kafka, Flink, Spark, and Iceberg. The framework propagates supported schema changes across the stack, uses pull-request-based versioning and auditing, targets SLA-based consistency between online and offline schemas, and provides recovery paths for unsupported or ambiguous changes. ### Source excerpt Yisheng Zhou | Software Engineer II Liang Mou | Sr Staff Software Engineer Gabriel Raphael Garcia Montoya | Staff Software Engineer Istvan Podor | Staff Software Engineer Introduction In the first post of this series, we introduced Pinterest's next-generation CDC-based ingestion platform built on Kafka, Flink, Spark, and Iceberg. In production, upstream schemas are constantly evolving, and in a distributed CDC pipeline, schema is not just metadata -- it is a cross-system contract spanning ingestion, transformation, storage, and historical backfill. A schema change that is not handled carefully can break Flink jobs, block Spark upserts, or create inconsistencies between online and offline representations. This post walks through how we make schema evolution safe in practice: the onboarding model it builds on, the changes we support and the tradeoffs we accept, how updates propagate across the stack, and how we monitor and recover when things go wrong. We end with where we're heading next -- zero-gap schema evolution. Background & Motivation Schema evolution was particularly challenging in our environment because our ingestion pipeline is composed of multiple tightly related stages, each of which depends on schema in a different way. A single table onboarding flow spans CDC source configuration, Kafka provisioning, Flink and Spark code generation, Iceberg CDC and base table creation, and historical bootstrap -- all driven by the same schema. Once a source schema changes, that change must be reflected across code, metadata, and storage in a controlled and auditable way. Without a unified automation framework, manual updates across these layers increase the risk of drift, failed deployments, and inconsistent datasets. We therefore needed a way to make schema evolution safe, repeatable, and scalable. Our Solution: SLA-Based Automated Schema Evolution To address this problem, we built an automated schema evolution framework on top of our CDC ingestion platform, providing: au ## watch Command in Linux: Real-Time Monitoring with Examples DevFeed: [watch Command in Linux: Real-Time Monitoring with Examples]() Original publisher: [Read original article]() Author: Hayden James Published: 2026-06-22T12:52:45Z Content type: tutorial Language: en Sources: [Hayden James]() Topics: [Linux](), [Monitoring](), [real-time](), [monitor]() Tags: [blog](), [commands](), [examples](), [guide](), [linux](), [monitor](), [monitoring](), [real-time](), [server](), [sysadmins]() ### AI overview A practical guide to the Linux watch command, which repeatedly runs a command at a chosen interval and displays its output full-screen. It explains default and custom refresh intervals, highlighting output changes, exiting on changes or errors, and monitoring tasks such as disk usage, processes, memory, and network activity. ### Source excerpt The watch command runs any Linux command repeatedly at a set interval and displays the output full-screen, making it one of the quickest ways to monitor live system activity without writing a script. This guide covers all the key options with practical examples for real sysadmin use cases. Continue reading... ## Workflow SDK now runs natively in Nitro v3 DevFeed: [Workflow SDK now runs natively in Nitro v3]() Original publisher: [Read original article]() Author: Rihan Arfan Published: 2026-06-13T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [SDKs](), [Web](), [debug](), [monitor](), [browser]() Tags: [browser](), [code](), [debug](), [dev](), [monitor](), [sdk](), [web](), [workflow]() ### AI overview Workflow SDK now has a beta native integration with Nitro v3. Workflow steps run in the same bundled runtime as the application, can use Nitro server-side APIs and storage directly, and are served with a workflow web UI for inspecting, monitoring, and debugging runs. Nitro also bundles workflow routes, traces dependencies, tree-shakes unused code, and produces faster builds with smaller bundles. ### Source excerpt Workflow SDK's native Nitro v3 integration is now in beta. Steps run inside the same bundled runtime as the rest of your app, instead of a separate bundle. Nitro's useStorage() and other server-side APIs work directly inside "use step" functions. The Nitro dev server also serves the workflow web UI at /_workflow. Open it in your browser to inspect, monitor, and debug workflow runs. Workflow routes are now bundled by Nitro as part of the app build. Dependencies are traced, and unused code is tree-shaken, so the output includes only what runs, with faster builds and smaller bundles. Get started with Workflow SDK on Nitro. Read more ## Monitor SLAs and scale ClickHouse Cloud with clickhousectl and agents DevFeed: [Monitor SLAs and scale ClickHouse Cloud with clickhousectl and agents]() Original publisher: [Read original article]() Author: Al Brown Published: 2026-06-05T14:58:29Z Content type: tutorial Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Cloud](), [monitor](), [Latency](), [Deadlock](), [dashboards](), [Front end]() Tags: [agents](), [clickhouse](), [cloud](), [concurrency](), [cpu](), [frontend](), [guide](), [how-to](), [latency](), [memory](), [monitor](), [resource](), [scale](), [workflow]() ### AI overview This guide shows how to monitor per-workload SLAs in ClickHouse Cloud, investigate latency breaches, scale infrastructure, and delegate remediation to an agent. ### Source excerpt Tag queries to track per-workload SLAs, then use clickhousectl to investigate breaches and scale ClickHouse Cloud, with an agent to remediate. ## EU DORA compliance for engineering teams DevFeed: [EU DORA compliance for engineering teams]() Original publisher: [Read original article]() Author: John Crowley Published: 2026-06-02T13:42:24Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Resilience](), [Incident response](), [systems](), [monitor](), [Software](), [incident]() Tags: [ciso](), [compliance](), [engineering](), [eu](), [incident-response](), [infrastructure](), [monitor](), [operational](), [operations](), [real-time](), [resilience](), [software](), [systems](), [third-party](), [workflows]() ### AI overview This article explains how the EU Digital Operational Resilience Act (DORA) affects engineering teams supporting financial services in the EU. It outlines requirements for ICT asset inventories, incident reporting, operational resilience testing, and third-party risk management, and describes the need for accurate software ecosystem information and automated workflows. ### Source excerpt Understand how the EU Digital Operational Resilience Act (DORA) affects engineering teams, the four core compliance pillars, and how to streamline audit readiness. ## Elastic Build Machines now protect against out of memory builds DevFeed: [Elastic Build Machines now protect against out of memory builds]() Original publisher: [Read original article]() Author: Mehul Kar Published: 2026-06-01T18:30:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Deployment](), [monitor]() Tags: [cost](), [deployment](), [infrastructure](), [monitor](), [vercel]() ### AI overview Vercel's elastic build machines monitor build memory usage and automatically adjust machine tiers to reduce out-of-memory failures. Fast but memory-intensive builds remain on appropriately sized machines, while builds nearing or encountering memory limits can trigger an automatic upgrade for the next deployment. ### Source excerpt Elastic build machines now monitor your build's memory usage and automatically adjust to prevent out-of-memory (OOM) failures: If your build is fast but memory-intensive, we will no longer downgrade you to a smaller machine If your build is close to running out of memory, we will automatically upgrade to a higher tier If your build fails due to an out-of-memory error, the next deployment will automatically run on a higher tier Thresholds are set conservatively to balance deployment reliability and cost. Vercel only considers your build's memory usage, not the memory used by Vercel's own build infrastructure. Enable elastic builds in your team settings or project settings, or read the docs. Read more ## Temporal Cloud and Datadog integration adds pre-built metrics dashboards and standard-metrics monitoring DevFeed: [Temporal Cloud and Datadog integration adds pre-built metrics dashboards and standard-metrics monitoring]() Original publisher: [Read original article]() Author: Dustin Cote Published: 2026-05-19T00:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [datadog](), [observability](), [dashboards](), [monitor](), [Cloud](), [reliability](), [API](), [API keys](), [Latency](), [Replication]() Tags: [announcements](), [api](), [cloud](), [cost](), [dashboard](), [datadog](), [latency](), [metrics](), [monitoring](), [observability](), [reliability](), [replication](), [setup]() ### AI overview Temporal Cloud and Datadog now offer an integration with a pre-built metrics dashboard, simplified setup, and more than 30 metrics for monitoring workflow performance, system health, and reliability. The metrics are classified as standard metrics in Datadog, which may reduce costs compared with custom metrics ingestion. ### Source excerpt Monitor Temporal Cloud with Datadog metrics. Gain deeper visibility into workflow performance and reliability. ## AI threats in the wild: The current state of prompt injections on the web DevFeed: [AI threats in the wild: The current state of prompt injections on the web]() Original publisher: [Read original article]() Author: Moni Pande Published: 2026-04-23T12:48:00Z Content type: article Language: en Sources: [Security]() Topics: [prompt injection](), [Security](), [Threat Research](), [Artificial Intelligence](), [Google](), [monitor](), [Web](), [AI Bots]() Tags: [agents](), [ai](), [ai-agents](), [attacks](), [google](), [monitor](), [none](), [prompt-injection](), [research](), [security](), [web]() ### AI overview Google Threat Intelligence teams investigate whether real-world adversaries are exploiting indirect prompt injection attacks on the public web. The article describes how malicious instructions embedded in websites, emails, or documents can manipulate AI systems and outlines a broad Common Crawl-based effort to monitor known attack patterns. ### Source excerpt We initiated a broad sweep of the public web to monitor for known indirect prompt injection patterns. This is what we found. ## v20.2.1 Tentacle released DevFeed: [v20.2.1 Tentacle released]() Original publisher: [Read original article]() Author: Yuri Weinstein Published: 2026-04-06T00:00:00Z Content type: release Language: en Sources: [Ceph Blog]() Topics: [bug](), [configuration](), [monitor](), [Command-line interface](), [API](), [dashboards](), [JSON]() Tags: [2026](), [api](), [blog-post](), [bug](), [cli](), [en-article](), [en-blog-post](), [json](), [monitor](), [nvme](), [osd](), [peering](), [policy](), [recovery](), [reef](), [release](), [rgw](), [tentacle](), [ui](), [workflows]() ### AI overview Ceph v20.2.1, the first minor release in the Tentacle series, is recommended for all users. The release fixes storage, recovery, peering, validation, and dashboard issues; restricts unsafe fast EC configurations; improves NVMeoF Gateway failover; adds listener and subsystem CLI commands; introduces a transient exclusive RBD lock policy; and updates dashboard navigation and forms. ### Source excerpt This is the first minor release in the Tentacle series. We recommend that all users update to this release. Release Date ¶ April 06, 2026 Notable Changes ¶ OSD / BlueStore ¶ EC Recovery: Fixed a length calculation bug in erase_after_ro_offset() that caused empty shards to retain data, leading to shard_size >= tobj_size assertion failures when recovering small objects in EC pools. BlueFS Volume Selector: Updated the BlueFS volume selector to properly account for file size changes when recovering the WAL in envelope mode. BlueFS: Fixed a bug where stat() missed the actual file size update after indexing WAL envelope files. Monitor (mon) ¶ Fast EC Restrictions: Denied the ability to enable EC optimizations ("fast EC") for non-4K-aligned chunk sizes. Unaligned chunk sizes handled by fast EC perform poorly and suffer from bugs, so attempts to force this configuration are now rejected. Peering: Ensured ceph pg repeer proposes a correctly sized pg temp, as optimized EC cannot cope with mismatched sizes. NVMeoF Gateway: Added a new nvme-gw listeners command to display all existing listeners (including auto-listeners) inside a pool/group. NVMeoF Failover: Overhauled the NVMeoF Gateway fast-failover logic. Beacon timeouts are now evaluated within prepare_beacon to support shorter intervals, and the mechanism for detecting monitor slowness was improved. librbd & rbd-mirror ¶ RBD: Introduced a new RBD_LOCK_MODE_EXCLUSIVE_TRANSIENT policy for rbd_lock_acquire(). This is a low-level interface intended to allow a peer to grab exclusive lock manually for short periods of time with other peers pausing their activity and waiting for the lock to be released rather than instantly aborting I/O and returning an error. It's possible to switch from RBD_LOCK_MODE_EXCLUSIVE to RBD_LOCK_MODE_EXCLUSIVE_TRANSIENT policy and vice versa even if the lock is already held. Ceph Object Gateway (RGW) ¶ Multi-Part Operations: Fixed conditional validation handling in MultiWrite, Delete, and MultiDelete ## 10 scripts Bash útiles para sysadmins DevFeed: [10 scripts Bash útiles para sysadmins]() Original publisher: [Read original article]() Author: Alois Published: 2026-01-14T00:00:00Z Content type: tutorial Language: es Sources: [tengoping.com]() Topics: [Scripting, bash](), [Bash](), [backups](), [monitor](), [rsync]() Tags: [backups](), [bash](), [logs](), [rsync](), [script](), [scripts](), [shell](), [sysadmin](), [sysadmins]() ### AI overview A Spanish-language tutorial presents ten practical Bash scripts for system administrators, including disk monitoring, rotating backups, log cleanup, and other routine tasks. It notes that Bash scripts suit focused tasks on individual machines but are not a replacement for configuration-management tools when managing many servers. ### Source excerpt Colección de scripts Bash prácticos para monitorización, backups, limpieza de logs y tareas comunes de administración de sistemas. ## How to use Gremlin's Reliability Report DevFeed: [How to use Gremlin's Reliability Report]() Original publisher: [Read original article]() Author: Gavin Cahill Published: 2025-12-12T00:00:00Z Content type: article Language: en Sources: [Gremlin Blog]() Topics: [dashboards](), [monitor](), [systems](), [Cloud](), [Kubernetes](), [configuration]() Tags: [blog](), [cloud](), [configuration](), [gremlin](), [how-to](), [kubernetes](), [leadership](), [monitor](), [organizational](), [reliability-management]() ### AI overview Gremlin's Reliability Report provides organization-wide visibility into system reliability through reliability scores, detected risks, test-run counts, and service-level impacts. The article explains the report's dashboard sections, including six-month reliability trends and automatically detected Kubernetes and cloud risks, and describes how leadership can use the information to monitor and improve reliability. ### Source excerpt Find out how our Reliability Report gives you visibility into your system's reliability--and how Gremlin uses it to improve reliability. ## GPU Observability: Get Deeper Insights into Your Droplets and DOKS Clusters DevFeed: [GPU Observability: Get Deeper Insights into Your Droplets and DOKS Clusters]() Original publisher: [Read original article]() Author: Waverly Swinton Published: 2025-11-12T20:56:52Z Content type: release Language: en Sources: [DigitalOcean]() Topics: [GPU](), [observability](), [Digital Ocean](), [monitor](), [Artificial Intelligence]() Tags: [ai](), [ai-ml](), [amd](), [clusters](), [data](), [droplets](), [efficiency](), [gpu](), [inference](), [metrics](), [monitor](), [network](), [nvidia](), [observability](), [performance](), [product-updates](), [real-time](), [training]() ### AI overview DigitalOcean introduces basic observability metrics for GPU Droplets and DOKS clusters. The metrics cover GPU utilization, memory, temperature, power consumption, throttling, and interconnect performance, and are available through the DigitalOcean Insights UI. ### Source excerpt We're introducing a new set of basic observability metrics for all GPU Droplets and DOKS clusters, giving you a powerful, simple way to monitor and optimize your AI workloads. Why GPU Observability Matters When running large-scale training, inference, and complex data processing--cluster performance and stability are paramount. Our new observability features are designed to give you the visibility you need to ensure effective utilization of your resources and quickly debug any performance bottlenecks. Get real-time, individual metrics from your NVIDIA and AMD GPUs and their network interfaces on critical factors like utilization, temperature, power consumption, and more--all directly within the DigitalOcean Insights UI, and with zero setup required. What's Included: New Metric Categories We've grouped the new metrics into five intuitive categories to provide a comprehensive view of your GPU and DOKS cluster health and performance: Utilization: Understand how busy your GPU cores and memory are. This includes key metrics like GPU Occupancy and Memory Utilization, allowing you to optimize your setup for peak performance live. Temperature: Monitor thermal conditions to prevent overheating and ensure stable operation under heavy load. Power: Track power consumption, which is essential for understanding GPU performance and efficiency. Throttle: Identify if your GPU is limiting its performance due to thermal, power, or voltage constraints. This is crucial for debugging sudden performance degradations. Interconnect: Gain insights into the network interface performance connecting your GPU resources. Zero Setup, No Extra Cost Observability shouldn't be a hurdle. That's why we've made this feature as seamless as possible: Default on: Observability will be enabled by default the moment you create a GPU Droplet. There is no configuration or effort required on your part. Free: These essential observability metrics are included with the AI/ML Ready images for GPU Droplets. We're com [Next page]()