cartero Wednesday, August 12, 2026 · No. 25929
Memory and Hardware

Understanding a Process’s Address Space Layout

In this video, we look at how a process’s virtual address space is laid out: code, data, heap, stack, shared libraries, mmap regions, and more.

Uber

Python 3.14 garbage collection rigamarole

Python 3.14.0 introduced a new incremental garbage collector. But reports of higher memory usage caused the Python team to revert the garbage collector changes in 3.14.5.We investigate how memory management works in Python and workloads that perform best and worst for the incremental garbage collector.

Artificial Intelligence

AI Worm

Large Language Models

How LLMs Work

PostgreSQL

Is my RAG stack overengineered? Graph DB + vector DB + Postgres + local and cloud LLMs for a nasty regulatory corpus

I've spent months building a RAG system over a large, dense regulatory/compliance corpus and I genuinely can't tell anymore whether the architecture is "appropriately complex for the problem" or whether I've talked myself into a monster. Looking for a gut check from people who've shipped this stuff. The corpus, to give you a feel without naming it: - Long legal-technical documents, heavily cross-referenced (one section will point to 5-15 others, plus external standards). - The *answers people...

PostgreSQL

Andrew Atkinson: Beta Testing PostgreSQL With Docker

The Postgres community values feedback from testing of Beta releases, and with Docker it’s been easier to get pre-release versions up and running. With the recent announcement of PostgreSQL 19 Beta 1, let’s get that running and test some of the new capabilities. Pre-Release Versions of Postgres with Docker First, you’ll need to install Docker for your OS! Grab the version needed for your OS and processor architecture, for example ARM or AMD/Intel/x86. On MacOS run uname -m or sw_vers...

MySQL

Migrating Etsy’s database sharding to Vitess

Etsy has maintained a sharded MySQL architecture since around 2010. This database cluster contains most of Etsy’s online data and is made up of ~1,000 tables distributed across ~1,000 shards. Over the last 16 years, it has grown significantly: combined, these tables have over 425 TB of data and receive roughly 1.7 million requests per second. Etsy engineers access our MySQL data through a proprietary object-relational mapping (ORM). The ORM has a corresponding model for each MySQL table. W...

Artificial Intelligence

Making Ads Count: Using MMoE and Auxiliary Tasks to Better Connect Buyers & Sellers

When buyers search on Etsy, they need to quickly and easily find the perfect item. At the same time, sellers need to be confident their unique products are being seen by the right customers. Our Ads Search ranking model, which is built on a multitask learning foundation, is the critical link in this connection. Recently, we identified an opportunity to drive more meaningful buyer engagement by enhancing our model’s ability to predict purchase intent. We achieved this via a dual-pronged impr...

RAG

Shaping Product Understanding with Contrastive Reinforcement Learning

Etsy’s marketplace is defined by the creativity and craftsmanship of our sellers and the hundreds of millions of highly diverse products they offer. You can find silversmiths who cold-forge recycled sterling silver, weavers who dye raw fleece with indigo and black walnut, and ceramicists who throw stoneware on a kick wheel. These details define each product and often determine whether it matches a buyer’s taste, style, and interests. Sometimes buyers know exactly what they want, searching...

MySQL

Migrating Etsy’s database sharding to Vitess

Etsy has maintained a sharded MySQL architecture since around 2010. This database cluster contains most of Etsy’s online data and is made up of ~1,000 tables distributed across ~1,000 shards. Over the last 16 years, it has grown significantly: combined, these tables have over 425 TB of data and receive roughly 1.7 million requests per second. Etsy engineers access our MySQL data through a proprietary object-relational mapping (ORM). The ORM has a corresponding model for each MySQL table. W...

Artificial Intelligence

Making Ads Count: Using MMoE and Auxiliary Tasks to Better Connect Buyers & Sellers

When buyers search on Etsy, they need to quickly and easily find the perfect item. At the same time, sellers need to be confident their unique products are being seen by the right customers. Our Ads Search ranking model, which is built on a multitask learning foundation, is the critical link in this connection. Recently, we identified an opportunity to drive more meaningful buyer engagement by enhancing our model’s ability to predict purchase intent. We achieved this via a dual-pronged impr...

RAG

Shaping Product Understanding with Contrastive Reinforcement Learning

Etsy’s marketplace is defined by the creativity and craftsmanship of our sellers and the hundreds of millions of highly diverse products they offer. You can find silversmiths who cold-forge recycled sterling silver, weavers who dye raw fleece with indigo and black walnut, and ceramicists who throw stoneware on a kick wheel. These details define each product and often determine whether it matches a buyer’s taste, style, and interests. Sometimes buyers know exactly what they want, searching...

MySQL

Migrating Etsy’s database sharding to Vitess

Etsy has maintained a sharded MySQL architecture since around 2010. This database cluster contains most of Etsy’s online data and is made up of ~1,000 tables distributed across ~1,000 shards. Over the last 16 years, it has grown significantly: combined, these tables have over 425 TB of data and receive roughly 1.7 million requests per second. Etsy engineers access our MySQL data through a proprietary object-relational mapping (ORM). The ORM has a corresponding model for each MySQL table. W...

Artificial Intelligence

Making Ads Count: Using MMoE and Auxiliary Tasks to Better Connect Buyers & Sellers

When buyers search on Etsy, they need to quickly and easily find the perfect item. At the same time, sellers need to be confident their unique products are being seen by the right customers. Our Ads Search ranking model, which is built on a multitask learning foundation, is the critical link in this connection. Recently, we identified an opportunity to drive more meaningful buyer engagement by enhancing our model’s ability to predict purchase intent. We achieved this via a dual-pronged impr...

RAG

Shaping Product Understanding with Contrastive Reinforcement Learning

Etsy’s marketplace is defined by the creativity and craftsmanship of our sellers and the hundreds of millions of highly diverse products they offer. You can find silversmiths who cold-forge recycled sterling silver, weavers who dye raw fleece with indigo and black walnut, and ceramicists who throw stoneware on a kick wheel. These details define each product and often determine whether it matches a buyer’s taste, style, and interests. Sometimes buyers know exactly what they want, searching...

AI Coding Tools

The Vanishing Apprentice

The first rung of the vaunted career ladder now seems frustratingly out of reach for thousands of would-be software engineers.