Harness is on a mission to make it simpler for builders to do database migrations with its new AI-Powered Database Migration Authoring function. This new functionality permits customers to explain schema adjustments in pure language to obtain a production-ready migration.
For instance, a developer might ask “Create a desk named animals with columns for genus_species and common_name. Then add a associated desk named birds that tracks unladen airspeed and correct identify. Add rows for Captain Canary, African swallow, and European swallow.”
Harness’ platform would then analyze the present schema and insurance policies, generate a backward-compatible migration, validate the change for security and compliance, commit it to Git for testing, and create rollback migrations.
“That is greater than an incremental function – it’s a step towards AI-native DevOps, the place methods perceive intent, implement coverage, and automate supply from code to cloud to database,” Harness wrote in a weblog publish.
This new functionality is part of Harness Database DevOps and is powered by Harness’ Software program Supply Information Graph and MCP Server, which understands the person’s database and pipelines and has built-in greatest practices.
In accordance with Harness, AI has sped up the method of writing code, however methods that transfer that code into manufacturing, like testing, safety, and database supply, haven’t saved up. Moreover, most growth groups nonetheless handle schema updates manually by way of SQL scripts, spreadsheet monitoring, and late-stage approvals.
“In a latest Harness research, 63% of organizations ship code quicker since adopting AI, however 72% have suffered a minimum of one manufacturing incident brought on by AI-generated code. The result’s the AI Velocity Paradox: quicker coding, slower supply. However there’s an answer. 83% of leaders agree that AI should prolong throughout your complete SDLC to unlock its full potential. Database DevOps helps to shut that hole by extending AI-powered automation and governance to the final mile of DevOps: the database,” Harness wrote.