cartero Thursday, August 13, 2026 · No. 25960
Software Engineering

On The <dl>

Database Administration and Tooling

Built an open-source tool for DLQ schema recovery after that thread 1 month ago

A few weeks back I posted here asking how teams handle DLQ messages that become incompatible after a schema change. i Got some great replies u/BroBroMate mentioned spinning up a Kafka Streeams app each time, u/KTCrisis mentioned the v1 consumer drain pattern, u/latkde gave solid prevention advice. The recovery gap kept bothering me so I built the tool that was missing: github.com/Saifulhuq01/dlq-revive What it does: connects to Kafka, paginates DLQ messages using assign()+seek() so it never j...

Prompt Engineering

Let the AI Cook

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...

Data Governance

Agent Fabric Context Catalog and the Future of AI Governance

Modern agents no longer execute within predictable application boundaries. They invoke APIs dynamically, retrieve enterprise context through MCP servers, orchestrate workflows across multiple platforms and interact with structured and unstructured data sources in real time. As these systems become more autonomous, organizations lose visibility into what data influenced an outcome, what systems were touched during […] The post Agent Fabric Context Catalog and the Future of AI Governance appe...