For most of the last 15 years, DevOps has been engaged in a massive automation project. First, it was server provisioning, then configuration management, then infrastructure as code. CI/CD pipelines followed, along with containers, Kubernetes, GitOps and eventually platform engineering. Each wave built on the previous one, steadily pushing infrastructure and operations further away from manual processes and deeper into programmable systems.The industry became extraordinarily successful at it. Tasks that once required ticket queues, weekend maintenance windows and large operations teams became automated workflows that could execute repeatedly and reliably. Infrastructure stopped being something organizations manually assembled and increasingly became…
Author: drweb
Let’s take a minute to make our terminal setup a lot more resilient so we do not…
AI-assisted coding tools are getting a meaningful upgrade. Cursor has released Composer 2.5, the latest version of its proprietary coding agent model, and the improvements go well beyond a version bump.Composer 2.5 is described as a substantial improvement in intelligence and behavior over its predecessor, Composer 2. It handles sustained work on long-running tasks better, follows complex instructions more reliably, and is easier to work with overall.For development teams already using Cursor or evaluating AI coding tools, that combination matters. Raw capability is one thing. But an agent that can stay on task across a lengthy workflow — without drifting,…
Now that we have the basic permission flow in place, we’re going to tighten things up and…
Now that we have the sandbox handling the basics, we need to tighten up how permission checks…
May 12, 2026 Docker AI Governance: Unlock Agent Autonomy, Safely Introducing Docker AI Governance: centralized control over how agents execute, what they can reach on the network, which credentials they can use, and which MCP tools they can call, so every developer in your company can run AI agents safely, wherever they work. Your laptop is the new prod Agents are the biggest productivity unlock… Read now
Before we jump into bypass permission mode, we should pause for a quick look at Anthropic’s new…
Reactive autoscaling is a critical safety net. Demand rises, metrics spike, policies trigger, and capacity increases. But flash-crowd events, product drops, major campaigns, and limited-inventory moments do not ramp. They cliff. Users arrive at once, and reactive scaling is structurally late because “scale triggered” is only the start of the journey to usable capacity. If your demand spike arrives faster than your system can warm up, reactive scaling will lag no matter how well you tune it. The fix is planning and verification: scale before the event and prove the system is ready before customers arrive. This article outlines a practitioner approach: schedule-aware, tier-based predictive scaling…
Now that we’ve let this autonomous loop run wild, we’re going to step back and look at…
Now that we’ve seen Ralph running locally, let’s move it onto a remote machine so we can…