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.
OpenSandbox is a general-purpose sandbox platform for AI applications offering multi-language SDKs, unified sandbox APIs and Docker/Kubernetes runtimes for use cases like coding agents, GUI agents, evaluation, code execution and RL training. It provides SDKs, CLI and MCP integration, a sandbox protocol for custom runtimes, built-in environments such as command, filesystem and code interpreter, network ingress/egress controls, credential vault injection and strong isolation via gVisor, Kata Containers and Firecracker.
- Release images published to Docker Hub, GHCR and Alibaba Cloud with Cosign signatures and provenance
- SDKs for Python, Java/Kotlin, TypeScript/JavaScript, C#/.NET and Go
- OpenSSF Best Practices badge and CNCF Landscape listing
- Release images published to Docker Hub, GHCR and Alibaba Cloud with Cosign signatures and provenance
- SDKs for Python, Java/Kotlin, TypeScript/JavaScript, C#/.NET and Go
- OpenSSF Best Practices badge and CNCF Landscape listing
OpenShell is a safe, private runtime environment designed for autonomous AI agents. It provides sandboxed execution with declarative YAML policies to control file access, data exfiltration, and network activity. Built with an agent-first approach, OpenShell offers pre-built skills for tasks like cluster debugging and policy generation.
Currently in alpha, it focuses on single-player mode and aims to expand to multi-tenant enterprise deployments. OpenShell uses a containerized K3s Kubernetes cluster for isolation and enforces security across filesystem, network, process, and inference layers. It supports agents like Claude, OpenCode, and Copilot, managing credentials securely.
Currently in alpha, it focuses on single-player mode and aims to expand to multi-tenant enterprise deployments. OpenShell uses a containerized K3s Kubernetes cluster for isolation and enforces security across filesystem, network, process, and inference layers. It supports agents like Claude, OpenCode, and Copilot, managing credentials securely.
OpenSandbox is a general-purpose sandbox platform for AI applications, offering multi-language SDKs, unified sandbox APIs, and Docker/Kubernetes runtimes for scenarios like Coding Agents, GUI Agents, Agent Evaluation, AI Code Execution, and RL Training.
Exploring secure environments for testing and running AI agent code, including options like Docker, online IDEs, and dedicated platforms.
