Leela Kumili writes about DoorDash's Flux platform, which moved LLM-based coding agent workloads from developer laptops to cloud infrastructure, automating 130,000 engineering tasks in a single month and supporting over 25,000 automated code reviews per week. The platform was built after local execution hit limits on power, uptime, and security, and is organized around four primitives: Firecracker microVM sandboxes, an in-house MCP gateway, YAML-defined playbooks, and multiple invocation surfaces (Slack, GitHub, cron, CLI, conversational interfaces).
- Sandboxes achieve a 95th percentile SLO under 5 seconds for full setup, including microVM start, repo clone, build tool install, and agent harness configuration.
- Playbooks can mix agent-driven steps with deterministic code where predictable execution or validation is required.
- The Agent Gateway enforces scoped permissions and logs all agent activity for auditing and policy enforcement.
- DoorDash switched Slack integration from private channels to public threads so engineers could observe agent executions and see how other teams delegated work.
- Sandboxes achieve a 95th percentile SLO under 5 seconds for full setup, including microVM start, repo clone, build tool install, and agent harness configuration.
- Playbooks can mix agent-driven steps with deterministic code where predictable execution or validation is required.
- The Agent Gateway enforces scoped permissions and logs all agent activity for auditing and policy enforcement.
- DoorDash switched Slack integration from private channels to public threads so engineers could observe agent executions and see how other teams delegated work.
AWS has released Agent Plugins for AWS, an open-source repository enabling AI coding agents to automate cloud deployment workflows. The initial deploy-on-aws plugin accepts natural language commands to generate complete deployment pipelines with architecture recommendations, cost estimates, and infrastructure-as-code.
A recent article by Google Cloud SREs describes how they use the AI-powered Gemini CLI internally to resolve real-world outages. This approach improves reliability in critical infrastructure operations and reduces incident response time by integrating intelligent reasoning directly into the terminal-based operational tools.
This article explores the emerging category of AI-powered operations agents, comparing AI DevOps engineers and AI SRE agents, how cloud providers are responding, and what engineers should consider when evaluating these tools.
Late last year, startup Platform Engineering Labs made waves in the world of Infrastructure as Code (IaC) by introducing a new IaC platform, called Formae, available initially on Amazon Web Services. This week, Platform Engineering Labs‘ platform gets (beta) support from additional cloud platforms, including Google Cloud Platform, Microsoft Azure, Oracle Cloud Infrastructure, and OVHcloud. The company has also released new AI-enhanced software for managing infrastructure tooling, called the Platform for Infrastructure Builders.
TurnKey GNU/Linux is a free Debian based library of system images that pre-integrates and polishes the best free software components into secure, easy to use solutions.
Platform Engineering Labs has released formae, an open-source infrastructure-as-code platform designed to address limitations in existing tools, focusing on automatic discovery, codification of existing infrastructure, and a reconcile/patch workflow. It uses PKL instead of HCL and targets reducing drift and complexity.
AI is revolutionizing Infrastructure as Code (IaC), enhancing speed, intelligence, and responsiveness. However, human expertise remains crucial for understanding AI-generated outputs and ensuring proper system functionality.
The article discusses the increasing complexity of Kubernetes and suggests that Silicon Valley is exploring alternative technologies for container orchestration, citing a benchmark showing a stripped-down stack outperforming Kubernetes.
Founded in 2007, Bitnami initially simplified open-source software deployment with pre-packaged stacks, eliminating complex configuration tasks for developers.
Bitnami has adapted to the changing tech landscape, expanding from installers and VMs to support cloud platforms, containers (Docker, Helm), and Kubernetes.
Bitnami has adapted to the changing tech landscape, expanding from installers and VMs to support cloud platforms, containers (Docker, Helm), and Kubernetes.
