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InfoWorld

AWS boosts CloudWatch Logs query limits by 10x to ease debugging for developers, SREs 21 LLMs tuned for special domains AWS adds Advanced Prompt Optimization tool to Bedrock Capacity markets could reshape cloud computing Four cutting-edge tools for spec-driven development Anthropic puts Claude agents on a meter across its subscriptions Notion courts developers with a platform for AI agents and workflow automation Using continuous purple teaming to protect fast-paced enterprise environments A better way to work with SQL Server Evidence-driven workflows: Rethinking enterprise process design AWS debuts Graviton-powered Redshift RG instances to cut analytics costs SAP’s AI promises last year? Most are still rolling out First look: Lemonade serves up local AI with limitations GitLab CEO sees developer tool bill increasing 100-fold Red Hat adds support for agentic AI development What’s new and exciting in JDK 26 Kill the loading spinner with local-first data and reactive SQL A networking revolution at AWS Tokenmaxxing is super dumb Hands-on with React, Supabase, and PowerSync How to add AI to an existing product (without annoying users) Your AI doesn’t need another database What happens when engineering teams reorganize around AI agents Python isn’t always easy When cloud giants meddle in markets 12 model-level deep cuts to slash AI training costs The best new features in Python 3.15 Teradata launches platform for enterprise AI agents moving beyond pilots Three skills that matter when AI handles the coding MongoDB targets AI’s retrieval problem Building AI apps and agents with Microsoft Foundry Designing front-end systems for cloud failure No, AI won’t destroy software development jobs Diskless databases: What happens when storage isn’t the bottleneck Vibe coding or spec-driven development? The agentic AI distraction Vibe coding or spec-driven development? How to choose Cloud providers are blinded by agentic AI SAP to acquire data lakehouse vendor Dremio Small language models: Rethinking enterprise AI architecture Making AI work through eval hygiene Improving AI agents through better evaluations AI in the cloud is easy but expensive Running AI in the cloud is easy – and expensive Making AI work for databases Harness teams of agentic coders with Squad Harness teams of coding agents with Squad Oracle NetSuite announces AI coding skills for SuiteCloud developers Why it’s so hard to create stand-alone Python apps A new challenge for software product managers The hidden cost of front-end complexity GitHub shifts Copilot to usage-based billing, signaling a new cost model for enterprise AI tools OpenAI’s Symphony spec pushes coding agents from prompts to orchestration The front-end architecture trilemma: Reactivity vs. hypermedia vs. local-first apps Enterprise AI is missing the business core The best JavaScript certifications for getting hired Google begins putting the guardrails on agentic AI Why world models are AI’s next frontier Where to begin a cloud career Google pitches Agentic Data Cloud to help enterprises turn data into context for AI agents How open source ideals must expand for AI Is your Node.js project really secure? 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Plunge into Python profiling
by Serdar Yegulalp Senior Writer · 2026-05-29 · via InfoWorld

Explore the new sampling profiler in Python 3.15, dive into no-impact Python profiling with the tprof library, see how Mojo 1.0 is taking shape, and more in our latest Python Report.

The first beta release of Python 3.15 has arrived. That means it’s time to discover all the best new features in Python, and especially its low-to-no impact profiling tools. Plus, with the recent debut of Mojo 1.0, you can see for yourself how the one-time Python challenger has set out on a path of its very own.

Top picks for Python readers on InfoWorld

First look: Mojo 1.0 mixes Python and Rust
What was once pitched as a potential Python replacement is evolving into a synthesis of Python’s easy syntax and package ecosystem and Rust’s native speed and memory safety.

PyWry: Webview rendering in Python
A “build once, render anywhere” library for Python, PyWry lets you “prototype in Jupyter, deploy via FastAPI, and compile to a stand-alone desktop executable”, using PyTauri instead of Electron.

Flet Studio
Flet Studio is an interactive, in-browser dev tool for writing Python programs that run in-browser using the Flet framework. Although you can’t download a stand-alone, compiled Flet package from the studio, just the source code, the interactivity alone is worth the effort.