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title: Best InfoQ posts — February 2026 | daily.dev
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# Best of InfoQ — February 2026

1. 1  
[](https://daily.dev/posts/shadcn-releases-visual-project-builder-1ptkzmoeh "Shadcn Releases Visual Project Builder")  
Article  
![Avatar of infoq](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/afc3bced3e1e4b188dd9127017a60e0c)InfoQ · 31w  
Shadcn Releases Visual Project Builder  
Shadcn launched a visual project builder accessible via \`npx shadcn create\` that lets developers customize their entire project setup—including themes, component libraries, icon sets, and design systems—before writing any code. The tool supports Next.js, Vite, and TanStack Start frameworks, offers real-time design previews with options for Radix UI or Base UI foundations, and generates a custom command with all selected parameters. This design-first approach eliminates repetitive manual setup work and aligns with shadcn's philosophy of giving developers complete code ownership by copying components directly into projects rather than distributing them as npm packages.  
73  
1
2. 2  
[](https://daily.dev/posts/warper-rust-powered-react-virtualisation-library-svl1jwjlf "Warper: Rust Powered React Virtualisation Library")  
Article  
![Avatar of infoq](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/afc3bced3e1e4b188dd9127017a60e0c)InfoQ · 29w  
Warper: Rust Powered React Virtualisation Library  
Warper 7.2 is an open-source React virtualization library that offloads scroll calculations to a Rust-compiled WebAssembly module. Key v7 changes include zero-allocation hot paths using TypedArrays, O(1) circular buffer operations for frame timing, and universal bundler support (Vite, Webpack, Rollup, esbuild, Parcel, Next.js). The library uses a Fenwick tree for item height tracking, enabling O(log n) prefix sum queries. Benchmarks claim 120 FPS with 100,000 items versus react-window's \~40 FPS. At 8.7KB gzipped, it sits between react-window (\~6KB) and TanStack Virtual (\~12KB). Community reception is mixed, with enthusiasm for the approach but questions about practical necessity and reported Firefox compatibility issues.  
63  
1
3. 3  
[](https://daily.dev/posts/reducing-onboarding-from-48-hours-to-4-inside-amazon-key-s-event-driven-platform-vwaza59ha "Reducing Onboarding From 48 Hours to 4: Inside Amazon Key’s Event-Driven Platform")  
Article  
![Avatar of infoq](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/afc3bced3e1e4b188dd9127017a60e0c)InfoQ · 30w  
Reducing Onboarding From 48 Hours to 4: Inside Amazon Key’s Event-Driven Platform  
Amazon Key's engineering team overhauled its event platform from a tightly coupled monolithic architecture to a centralized event-driven system built on Amazon EventBridge. The redesign uses a single bus, multi-account pattern where a core EventBridge bus routes domain events to isolated subscriber accounts. A centralized schema repository with a custom client library enforces consistent data contracts across producers and consumers. Infrastructure provisioning is automated via reusable AWS CDK constructs. The results: \~2,000 events/second processed at p90 latency of \~80ms, 99.99% success rate, service onboarding reduced from 48 hours to 4, and integration time cut from \~40 hours to \~8.  
54
4. 4  
[](https://daily.dev/posts/openai-scales-single-primary-postgresql-to-millions-of-queries-per-second-for-chatgpt-wcyldtady "OpenAI Scales Single Primary Postgresql to Millions of Queries per Second for ChatGPT")  
Article  
![Avatar of infoq](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/afc3bced3e1e4b188dd9127017a60e0c)InfoQ · 31w  
OpenAI Scales Single Primary Postgresql to Millions of Queries per Second for ChatGPT  
OpenAI scaled a single-primary PostgreSQL instance to handle millions of queries per second for ChatGPT's 800 million users by deploying nearly 50 geo-distributed read replicas on Azure, optimizing query patterns, and offloading write-heavy workloads to sharded systems like Azure Cosmos DB. Key strategies included connection pooling with PgBouncer, reducing write pressure through application-level tuning, implementing cascading replication to reduce primary load, and isolating critical workloads to maintain low-latency performance under global traffic spikes.  
31

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