# Performance Metrics Published articles for Performance Metrics. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers DevFeed: [Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers]() Original publisher: [Read original article]() Author: Josh Parker Published: 2026-09-16T13:00:33Z Content type: news Language: en Sources: [NVIDIA Blog]() Topics: [data centers](), [AI Infrastructure](), [Google](), [Nvidia](), [Artificial Intelligence](), [datacenter](), [benchmarking](), [Requirements]() Tags: [ai](), [ai-data-centers](), [ai-infrastructure](), [capacity](), [corporate](), [data-centers](), [energy](), [google](), [infrastructure](), [launch](), [metrics](), [nvidia](), [performance-metrics](), [requirements](), [resource](), [systems]() ### AI overview Emerald AI, Google and NVIDIA announced the AI Energy Management Alliance, a coalition focused on flexible AI data centers that can dynamically adjust electricity use in response to grid conditions. The article describes technology-neutral, performance-based requirements covering response speed, duration, predictability and emergency behavior. ### Source excerpt AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA announced the launch of the AI Energy Management Alliance (AEMA), a first-of-its-kind coalition advancing data centers that can dynamically manage their electricity use [...] ## Monitor Your Drive Health with Performance Co-Pilot on Fedora DevFeed: [Monitor Your Drive Health with Performance Co-Pilot on Fedora]() Original publisher: [Read original article]() Author: Paul Evans Published: 2026-08-10T08:00:00Z Content type: article Language: en Sources: [Fedora Magazine]() Topics: [Fedora](), [Monitoring](), [Grafana](), [telemetry]() Tags: [data](), [diagnostics](), [drive](), [farm](), [fedora-project-community](), [grafana](), [hdd](), [health](), [home-server](), [metrics](), [monitor](), [monitoring](), [nvme](), [open-source](), [performance](), [performance-metrics](), [self-hosted](), [server](), [smart](), [ssd](), [telemetry](), [wwid]() ### AI overview This article explains how to monitor drive health on Fedora using Performance Co-Pilot (PCP). It covers SMART metric collection for HDDs, SSDs, and NVMe drives, NVMe error-log decoding, WWID-based tracking, Seagate FARM telemetry, continuous metric collection, and Grafana dashboards for viewing drive-health trends. ### Source excerpt You wake up one morning to find your home server unresponsive, after some investigation you discover a failed NVMe drive taking your self-hosted services and data with it. Perhaps you're a system administrator and a workstation's SSD has been silently accumulating errors for months, and now a user is reporting corrupted files. Drive failures are [...] ## Top System Design Performance Metrics DevFeed: [Top System Design Performance Metrics]() Original publisher: [Read original article]() Author: Saurabh Dashora Published: 2026-07-14T08:36:41Z Content type: tutorial Language: en Sources: [System Design Codex]() Topics: [benchmarking](), [Availability](), [Architecture & Design](), [Scalability](), [Load Balancing](), [health checks](), [Concurrency](), [Disaster Recovery](), [Database](), [sharding](), [IO](), [API]() Tags: [api](), [availability](), [blocking](), [concurrency](), [database](), [disaster-recovery](), [health-checks](), [load-balancing](), [performance](), [performance-metrics](), [scalability](), [sharding](), [system-design]() ### AI overview A tutorial on system design performance metrics, focusing on availability and throughput. It explains how these metrics are measured and outlines techniques such as load balancing, health checks, failover, redundancy, disaster recovery, query optimization, sharding, and asynchronous processing. ### Source excerpt Must Know Metrics ## Query Speed Insights from the Vercel CLI DevFeed: [Query Speed Insights from the Vercel CLI]() Original publisher: [Read original article]() Author: Ergün Erdoğmuş Published: 2026-06-29T08:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Command-line interface](), [Core Web Vitals](), [benchmarking](), [Web]() Tags: [cli](), [core-web-vitals](), [insights](), [measurements](), [metrics](), [performance](), [performance-metrics](), [vercel](), [web]() ### AI overview Vercel CLI can now query Speed Insights datapoints, including Core Web Vitals and other page performance metrics collected from real user traffic. The feature supports investigating regressions and comparing performance across pages, regions, and device types. ### Source excerpt You can now query Speed Insights datapoints directly through the Vercel CLI. Using the vercel metrics command, you can pull core Web Vitals (LCP, INP, CLS) and other page performance metrics (FCP, TTFB) based on client-side measurements from real user traffic. By providing a coding agent access to the CLI, an agent can answer questions such as: Which pages' INP have regressed since last week? How is the perceived speed of my home page in Asia? Compare the CLS of the dashboard between mobile and desktop. For more details on how to use the CLI command and a complete list of supported metrics, dimensions, filters, and query options, explore the documentation. Read more ## Exploring wireless communication protocols on ESP32 platform for outdoor applications DevFeed: [Exploring wireless communication protocols on ESP32 platform for outdoor applications]() Original publisher: [Read original article]() Author: John Lee Published: 2024-12-20T00:00:00Z Content type: article Language: en Sources: [Blog on Developer Portal]() Topics: [ESP-NOW](), [ESP32-C6](), [Wi-Fi](), [benchmarking](), [Internet of things](), [Protocol (disambiguation)]() Tags: [benchmarking](), [blog](), [esp-idf](), [esp-now](), [esp32-c6](), [espressif](), [iot](), [performance](), [performance-metrics](), [protocol](), [wi-fi](), [wireless]() ### AI overview The article evaluates Wi-Fi, ESP-NOW, and ESP-NOW-LR outdoors using ESP32-C6-DevKitM-1 boards as transmitters and receivers. It describes the board's Wi-Fi 6, 2.4 GHz, low-power, and PCB antenna characteristics, including the limitation that it lacks external antenna support. ### Source excerpt Introduction# The ESP32-C6-DevKitM-1 was chosen for testing Wi-Fi, ESP-NOW, and ESP-NOW-LR due to its cutting-edge features and suitability for real-world evaluations. While its compact design and integrated capabilities make it an excellent choice, it should be noted that the board does not natively support external antennas. Instead, it features a high-quality PCB antenna optimized for typical IoT applications. ## Figma on Figma: Our approach to designing UI3 DevFeed: [Figma on Figma: Our approach to designing UI3]() Original publisher: [Read original article]() Author: Jenny Xie Published: 2024-10-01T00:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [Figma](), [benchmarking]() Tags: [design](), [ecosystem](), [experiment](), [feature](), [figma](), [metrics](), [performance-metrics](), [product](), [ui]() ### AI overview Figma describes how its team designed UI3, a redesigned interface intended to give the canvas more space and create a streamlined, adaptable experience. The process combined user feedback, product vision, experimentation, feature adoption, performance metrics, and feedback from an open beta. ### Source excerpt Overhauling Figma's interface meant reimagining how designers work. From docked panels to a new labeling system, here's how we shaped UI3 by balancing user feedback with our vision for the future. ## A Journey from Monolith to Micro frontends at Udemy -- Part 3 of 3 DevFeed: [A Journey from Monolith to Micro frontends at Udemy -- Part 3 of 3]() Original publisher: [Read original article]() Author: Hamza ERBAY Published: 2024-01-16T18:23:06Z Content type: article Language: en Sources: [Udemy Engineering]() Topics: [Front end](), [migration](), [Design system](), [GitHub Actions](), [Monitoring](), [npm packages](), [Hackathon]() Tags: [architecture](), [design-system](), [development](), [development-process](), [frontend](), [github-actions](), [micro-frontends](), [migration](), [monitoring](), [npm-packages](), [overcoming-obstacles](), [performance-metrics]() ### AI overview Part 3 of Udemy's series describes implementing a migration from a monolithic frontend to a more modular micro-frontend architecture. It covers migration guidance, shared design-system npm packages, team education, monitoring with Datadog and Sentry, simplified local development, and GitHub Actions-based releases. ### Source excerpt Transforming Frontend Architecture: A Journey from Monolith to Micro Frontends at Udemy -- Part 3 of 3 By: Chris Nienhuis, Hamza Erbay, Matthew Bise, Nathan Chapman, Seth Hodgson, Trey Briggs, Charles Pham Photo by Venti Views on UnsplashIntroduction In the previous section, we walked through the Udemy Hackathon event, and the decisions and preparations made that laid the foundation for our move toward a more modular frontend architecture. In this section, we will focus on the implementation of our vision post-Hackathon, how we are planning to execute the migration, and the impact it has had so far. If you missed Part 1 and Part 2 of this series, you can find them here: Transforming frontend Architecture: A Journey from Monolith to Micro frontends at Udemy -- Part 1... Transforming frontend Architecture: A Journey from Monolith to Micro frontends at Udemy -- Part 2... Post-Hackathon: Implementing the Vision Following the green light from the Shark Tank jury, we've taken decisive steps to translate our hackathon prototype into a scalable and robust frontend architecture. A dedicated frontend team has been formed at Udemy with the express purpose of driving this evolution. "Where the journey began... A throwback to the spark that ignited our incredible voyage. Thanks to Gregg (our former CEO) for recognizing the hard work! #Milestone #Hackathon #OriginStory" Our commitment to this new direction is reflected in a series of strategic actions: Migration Guidance: We've laid out clear guidelines for transitioning (transitioning implies migration) from the monolithic application, ensuring a smooth and structured shift to the new architecture. Collaboration with Design Systems: By partnering with the design system team, we've begun decoupling foundational components and design tokens, packaging them into shared npm packages. This initiative is critical for consistency and efficiency across all applications. Education and Alignment: Recognizing the importance of knowledge sharing, we ## User-Centric Mobile Performance DevFeed: [User-Centric Mobile Performance]() Original publisher: [Read original article]() Author: Pierre-Yves Ricau Published: 2023-07-06T20:15:44Z Content type: article Language: en Sources: [Py's blog]() Topics: [User Experience](), [Mobile](), [benchmarking](), [Development]() Tags: [android](), [app-performance](), [article](), [cpu](), [customer-experience](), [gpu](), [metrics](), [mobile](), [performance](), [performance-metrics](), [user-experience]() ### AI overview An approach to mobile performance that prioritizes user-centric metrics over technical resource and workload metrics. It distinguishes smoothness and responsiveness measures while treating CPU, memory, database, and similar technical metrics as secondary diagnostic signals. ### Source excerpt 👋 Hi, this is P-Y, over the last three years I've been steering Square's focus on mobile performance and building a framework for thinking about it and prioritizing work. In this article I share my approach, let me know what you think! Useful metri... ## What are DORA metrics and why should you care about them? DevFeed: [What are DORA metrics and why should you care about them?]() Original publisher: [Read original article]() Author: Luis Gonzalez Published: 2023-05-03T00:00:00Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [dora metrics](), [DevOps](), [Google](), [Deployment](), [Resilience]() Tags: [deployment](), [devops](), [dora-metrics](), [google](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [metrics](), [outage](), [performance-metrics](), [post-mortem](), [resilience](), [slack-incident](), [software-delivery]() ### AI overview This article explains DORA metrics, a framework developed by Google Cloud's DevOps Research and Assessments team to evaluate how effectively and efficiently teams deploy, deliver, and maintain software. It introduces deployment frequency and lead time for changes, while noting that organizations may define deployment and software delivery differently. ### Source excerpt Google's DORA metrics can help organizations create better products, build stronger teams, and improve resilience long-term. ## Vite 4.3 is out! DevFeed: [Vite 4.3 is out!]() Original publisher: [Read original article]() Author: The Vite Team Published: 2023-04-20T00:00:00Z Content type: release Language: en Sources: [Vite]() Topics: [Vite](), [Caching](), [React](), [Benchmark](), [benchmarking](), [Node.js]() Tags: [benchmark](), [blog-post](), [caching](), [changelog](), [cpu](), [metrics](), [node-js](), [nvme](), [performance](), [performance-metrics](), [profiling](), [pull-request](), [react](), [speed](), [windows]() ### AI overview Vite 4.3 is a minor release focused on improving development server performance. It streamlines module resolution and adds smarter caching, with reported improvements over Vite 4.2 in startup and HMR benchmarks, including tests using React applications. The article also describes profiling tools and previews a future major release that will drop Node.js 14 and 16 support. ### Source excerpt Vite 4.3 is out! April 20, 2023 Quick links: Docs: English, 简体中文, 日本語, Español, Português Vite 4.3 Changelog Performance Improvements In this minor, we focused on improving the dev server performance. The resolve logic got streamlined, improving hot paths and implementing smarter caching for finding package.json, TS config files, and resolved URL in general. You can read a detailed walkthrough of the performance work done in this blog post by one of Vite Contributors: How we made Vite 4.3 faaaaster 🚀. This sprint resulted in speed improvements across the board compared to Vite 4.2. These are the performance improvements as measured by sapphi-red/performance-compare, which tests an app with 1000 React Components cold and warm dev server startup time as well as HMR times for a root and a leaf component: | Vite (babel) | Vite 4.2 | Vite 4.3 | Improvement | | : ## Unlocking your app's best experience with Firebase Performance Monitoring DevFeed: [Unlocking your app's best experience with Firebase Performance Monitoring]() Original publisher: [Read original article]() Author: Nitin Kaushik Published: 2021-08-02T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Monitoring](), [Mobile](), [Development]() Tags: [app-performance](), [app-quality](), [best-practices](), [crashlytics](), [firebase](), [monitoring](), [performance-metrics](), [performance-monitoring](), [releases](), [test-lab]() ### AI overview This article explains how Firebase Performance Monitoring helps developers understand app performance from users' perspectives. It covers real-time performance metrics, monitoring releases during development and after launch, and analyzing screen-rendering and network-request data across user segments. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Introducing PySurvival DevFeed: [Introducing PySurvival]() Original publisher: [Read original article]() Author: sfotso Published: 2019-04-12T21:06:21Z Content type: article Language: en Sources: [Square Corner Blog - Medium]() Topics: [Python](), [Data analysis](), [NumPy](), [PyTorch](), [SciPy](), [Open Source]() Tags: [api](), [article](), [data-analysis](), [data-science](), [deep-learning](), [machine-learning](), [open-source](), [performance-metrics](), [python](), [pytorch](), [survival-analysis](), [tutorials]() ### AI overview Square introduces PySurvival, an open source Python package for survival analysis modeling. The article describes its models, theory summaries, API documentation, examples, tutorials, performance metrics, and model loading and saving features. ### Source excerpt Heads up, we've moved! If you'd like to continue keeping up with the latest technical content from Square please visit us at our new home https://developer.squareup.com/blogPySurvival is an open source python package for Survival Analysis modeling. Today, we're excited to introduce PySurvival, a python package for Survival Analysis modeling. This article is the first installment in a four part series, which will include tutorials designed to demonstrate how to easily make the most of the package. You can also find these tutorials on the official website: Churn modeling Predictive maintenance Credit risk PySurvival LogoWhat is PySurvival ? PySurvival is an open source python package for Survival Analysis modeling -- the modeling concept used to analyze or predict when an event is likely to happen. It is built on top the most commonly used machine learning packages: NumPy, SciPy, and PyTorch. PySurvival provides a very easy way to navigate between theoretical knowledge on Survival Analysis and detailed tutorials on how to conduct a full analysis, as well as build and use a model. The package contains: 10+ models ranging from the Cox Proportional Hazard model and the Neural Multi-Task Logistic Regression, to Random Survival Forest Summaries of the theory behind each model as well as API descriptions and examples Detailed tutorials on how to perform exploratory data analysis, survival modeling, cross-validation and prediction, for churn modeling and credit risk, for example Performance metrics to assess the models' abilities like c-index or brier score Simple ways to load and save models Installation If you have already installed a working version of gcc, the easiest way to install Pysurvival is using pip. pip install pysurvival The complete installation steps can be found here. Introduction to Survival analysisWhat is Survival Analysis ? Survival analysis is used to analyze or predict when an event is likely to happen. It originated in medical research, but its use has ## The Idle Until Urgent Strategy for Improving First Input Delay DevFeed: [The Idle Until Urgent Strategy for Improving First Input Delay]() Original publisher: [Read original article]() Published: 2018-09-20T07:25:36Z Content type: tutorial Language: en Sources: [Philip Walton]() Topics: [benchmarking](), [modern web development](), [JavaScript](), [Webpack](), [Babel]() Tags: [analytics](), [babel](), [blog](), [browser](), [cpu](), [javascript](), [main-thread](), [network](), [performance](), [performance-metrics](), [trace](), [webpack]() ### AI overview This tutorial examines a blog's unexpectedly high first input delay and explains how to diagnose the cause with performance traces. It introduces the idle until urgent strategy as a way to improve responsiveness without removing site functionality. ### Source excerpt A few weeks ago I was looking at some of the performance metrics for my site. Specifically, I wanted to see how I was doing on our newest metric, first input delay (FID). My site is just a blog (and doesn't run much JavaScript), so I expected to see pretty good results. ## The new Trace view in Apollo Engine DevFeed: [The new Trace view in Apollo Engine]() Original publisher: [Read original article]() Author: Danielle Man Published: 2017-10-31T23:26:00Z Content type: article Language: en Sources: [Apollo Blog]() Topics: [GraphQL](), [tracing](), [Monitoring](), [gateway]() Tags: [announcement](), [apollo](), [gateway](), [graphql](), [metrics](), [monitoring](), [network](), [performance](), [performance-metrics](), [product](), [render](), [server](), [trace](), [tracing]() ### AI overview This article describes the new Trace view in Apollo Engine, a GraphQL gateway and successor to Apollo Optics. The updated view helps developers inspect query critical paths, distinguish resolver time from network, queueing, parsing, and validation time, and identify when resolver execution starts and ends. ### Source excerpt Last week we announced our new GraphQL gateway product and successor to Apollo Optics, Apollo Engine. It has the essential GraphQL monitoring features like request tracing and performance metrics over time that Optics did, and adds new functionality like error reporting and whole query caching. ## Website performance monitoring tool DevFeed: [Website performance monitoring tool]() Original publisher: [Read original article]() Author: Federico Published: 2016-08-01T16:54:00Z Content type: article Language: en Sources: [Federico Cargnelutti]() Topics: [Monitoring](), [Website](), [dashboards](), [Open Source](), [Self-hosted](), [GitHub]() Tags: [dashboards](), [github](), [javascript](), [monitoring](), [node-js](), [open-source](), [performance-metrics](), [performance-monitoring](), [self-hosted](), [slack](), [tool](), [tools](), [web](), [web-apps](), [web-services]() ### AI overview The article introduces SpeedTracker, an open-source, MIT-licensed, self-hosted tool that runs on WebPageTest to periodically test website performance. It visualizes performance metrics over time, supports performance budgets, and can send alerts by email or Slack. ### Source excerpt Monitoring systems allow you to monitor changes to your front-end code base over time, catching any regression issues and monitoring the ongoing effects of any performance optimisation changes. Easy to use dashboards are a must when it comes to monitoring the state of your web apps. Companies like Calibre or SpeedCurve offer this as a [...]