SShortSingh.
Back to feed

Guide: How to Test Risky PostgreSQL Migrations Safely Using Volume Cloning

0
·8 views

Database migrations that pass in development can still break production, particularly when adding a NOT NULL column without a default to a table that already contains rows. A new technical guide demonstrates how to build a multi-tenant Go API backed by PostgreSQL on Unikraft Cloud, then safely test dangerous migrations by cloning the live database's persistent volume. The cloned volume is used to boot a separate, disposable Postgres instance where the risky migration runs first, ensuring failures are caught before they reach production. The guide deliberately uses Unikraft Cloud's broadly available volume-cloning mechanism rather than its enterprise-only instance branching feature, making the approach accessible without a special license. Tools used include Go, pgx, and the Goose migration library, with the workflow designed to address the shortcomings of staging databases and slow pg_dump restore cycles.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Why Scaling MCP Beyond Local Dev Creates Serious Enterprise Governance Challenges

The Model Context Protocol (MCP) allows developers to connect AI models to tools and data quickly, making it popular for local development workflows. However, when organizations attempt to roll out MCP at enterprise scale, significant problems emerge around security, visibility, and governance. Hardcoded credentials, untracked server instances, and overly broad permissions granted to AI agents can expose organizations to serious risks. Platform and security teams struggle to audit which users, models, and tools are involved in any given operation when MCP servers are managed independently across teams. Experts argue that enterprise-scale MCP deployments require a dedicated gateway layer with centralized identity management, observability, and governance controls.

0
ProgrammingDEV Community ·

Developer builds cryptographic verification system to audit AI agent delegation

A solo developer has released an open-source MVP called AI-tower that makes AI agent delegation cryptographically verifiable using Ed25519 digital signatures. The system addresses a gap in current AI agent infrastructure, where monitoring alone cannot prove which agent authorized a specific action or capability handoff. When one AI agent delegates tasks to another, the system creates a signed payload recording who delegated, to whom, what capabilities were granted, and when. Verification is performed client-side using the Web Crypto API, meaning the server cannot tamper with delegation records after the fact. The project is available on GitHub, and the developer is seeking community feedback on the canonicalization approach and capability model.

0
ProgrammingHacker News ·

Robin Williams' Daughter Calls Out Fans Making AI Videos of Late Actor

Zelda Williams, daughter of the late comedian Robin Williams, has publicly criticized fans who are creating AI-generated videos featuring her father. She urged those responsible to reconsider their actions, telling them to 'have some shame.' The issue highlights growing concerns around the use of artificial intelligence to recreate deceased celebrities without family consent. The story was reported by Variety in 2026 and drew attention on social platforms and tech forums.

0
ProgrammingDEV Community ·

PonyMux 0.10 Adds Full-Text Search Across Claude Code and Codex Chat History

AI coding agent tools like Claude Code and Codex store complete conversation logs locally on disk, but retrieving specific past discussions has long been difficult without manual grep commands or third-party utilities. PonyMux 0.10 addresses this by integrating full-text search directly into its existing Cmd+K terminal launcher, allowing users to search across all stored conversation transcripts from a single interface. The feature indexes every prompt, agent response, and tool call from local JSONL and session files, returning matched snippets with highlighted keywords. The index is built using SQLite FTS5 with trigram tokenization, enabling substring and CJK language matches without extra configuration, and updates automatically via filesystem events after the initial 10–30 second setup. The search index is stored separately and can be paused or rebuilt from settings without affecting other PonyMux data.