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ExternalCloud
Cloudflare Changelog

Workers, Durable Objects - Track memory usage for Workers and Durable Objects in the dashboard

You can now monitor how much memory your Workers and Durable Objects consume across invocations with the new Memory Usage chart in the Workers Metrics tab, broken down by P50, P90, P99, and P999 percentiles. Memory usage measures the V8 isolate memory at the time of each invocation, subject to the 128 MB per-isolate limit — a single isolate can handle many concurrent requests and shares memory across them. Use the Memory Usage chart to: Track memory trends — Spot gradual increases that may indi

WorkersDurable Objects
Cloudflare ChangelogRead original
ExternalObservability
Elastic Blog

Elastic Stack 9.3.7 released

Version 9.3.7 of the Elastic Stack was released today. We recommend you upgrade to this latest version. We recommend 9.3.7 over the previous versions 9.3.6 For details of the issues that have been fixed and a full list of changes for each product in this version, please refer to the release notes.

Elastic BlogRead original
ExternalObservability
Elastic Blog

Elastic Stack 8.19.18 released

Version 8.19.18 of the Elastic Stack was released today. We recommend you upgrade to this latest version. We recommend 8.19.18 over the previous versions 8.19.17 For details of the issues that have been fixed and a full list of changes for each product in this version, please refer to the release notes.

Elastic BlogRead original
ExternalSoftware Engineering
DEV Community

Making the Context Across 46 Repositories Semantically Searchable for AI (Part 2)

Hi, I'm Ryan, CTO at airCloset. In Part 1, I wrote about unifying 46 repositories of production code into a single knowledge graph via static analysis. The graph itself got built, but I closed the post with four open issues: no semantic search, node explosion, having to open the file to actually know what a function does, and the cost of writing a new parser every time a new boundary pattern showed up. This Part 2 is about how I solved the first one — the entry-point problem (no semantic search)

aiknowledgegraphstaticanalysis
DEV CommunityRead original
ExternalSoftware Engineering
DEV Community

How We Built StyleSense: AI Virtual Try-On Powered by Amazon Aurora & Vercel

Online clothing returns cost the industry over $816 billion a year. The root cause is simple: shoppers can't see how clothes look on their body before buying. We built StyleSense to fix that — an AI-powered virtual wardrobe where you upload a selfie, add clothes from any product URL, and instantly see yourself wearing them. Here's how we built it, and why Amazon Aurora PostgreSQL and Vercel were the right choices for a 72-hour hackathon build. Frontend: Next.js 14 App Router + TypeScript + Tailw

aiawsshowdev
DEV CommunityRead original
ExternalSoftware Engineering
DEV Community

Building BrewCore: Espresso Tracking on Vercel, DynamoDB, and Amazon Bedrock

Beyond the Timer: How I Built BrewCore for the H0 Hackathon Home espresso is a paradox. Baristas obsess over the micro-details the gram weight, the seconds on the clock, the pressure profile-but we usually track it all on sticky notes or fragmented mental maps. When that morning shot turns sour, we don’t have a database to query; we have a bad cup of coffee and a Reddit thread from 2019. For the H0 Hackathon, I wanted to bridge that gap. I've built BrewCore: a full-stack coffee companion that

awsh0hackathonbedrock
DEV CommunityRead original

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