Setting Docker Hardened Images free (Interview)

Welcome, everyone. I'm Jared, and you are listening to the change log, where each week we interview the hackers, the leaders, and the innovators of the software world. In May 2025, Docker launched hardened images, a secure, minimal, production ready set of images. And in December, they made DHI freely available and open source to everyone who builds software. On this episode, we are joined by Tushar Jain, EVP of engineering at Docker, to learn all about it. But first, a big thank you to our partners at flyta.io, the platform for devs who just wanna ship, build fast, run any code fearlessly at fly.io. Okay. Docker harden images for all on the change log. Let's do it. This is the year we almost break the database. Let me explain. Where do agents actually store their stuff? They've got vectors, relational data, conversational history, embeddings, and they're hammering the database at speeds that humans just never have done before. And most teams are duct taping together a Postgres instance, a vector database, maybe Elasticsearch for search. It's a mess. Well, our friends at Tiger Data looked at this and said, what if the database just understood agents? That's agentic Postgres. It's Postgres built specifically for AI agents, and it combines three things that usually require three separate systems. Native model context protocol servers, MCP, hybrid search, and zero copy forks. The MCP integration is the clever bit your agents can actually talk directly to the database. They can query data, introspect schemas, execute SQL without you writing fragile glue code. The database essentially becomes a tool your agent can wield safely. Then there's hybrid search. Tagger data merges vector similarity search with good old keyword search into a SQL query. No separate vector database, no elastic search cluster, semantic and keyword search in one transaction. One engine. Okay. My favorite feature, the forks. Agents can spawn sub second zero copy database clones for isolated testing. This is not a database they can destroy. It's a fork. It's a copy off of your main production database if you so choose. We're talking a one terabyte database forked in under one second. Your agent can run destructive experiments in a sandbox without touching production, and you only pay for the data that actually changes. That's how Copy On Right works. All your agent data, vectors, relational tables, time series metrics, conversational history lives in one queryable engine. It's the elegant simplification that makes you wonder why we've been doing it the hard way for so long. So if you're building with AI agents and you're tired of managing a zoo of data systems, check out our friends at Tiger Data at tigerdata.com. They've got a free trial and a CLI with an MCP server you can download to start experimenting right now. Again, tigerdata.com. So first, we have supply chain attacks caused $60,000,000,000 in damages in 2025. Triple what they caused in 2021. Every language, every ecosystem, every build stuff, they're a …