Introducing DigitalOcean Managed Agents: One AI-native stack to power your intelligence

Introducing DigitalOcean Managed Agents: One AI-native stack to power your intelligence | DigitalOcean

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Introducing DigitalOcean Managed Agents: One AI-native stack to power your intelligence

By DigitalOcean

Updated: September 22, 2026 11 min read

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Following a successful private preview, we’re thrilled to open DigitalOcean Managed Agents to everyone. Teams can now deploy their preferred agent harness (like OpenCode, Codex CLI) or bring their own, connect agents to 16,000+ tools, and help agents do more work at scale without building or maintaining any infrastructure themselves. With native integration to DigitalOcean’s Inference Engine , Managed Agents brings inference tokens, agent execution, and tool use together, so you can scale your intelligence all in one place . Agents go from session creation to a response in less than a couple of seconds and resume paused work in ~300 milliseconds. With per-second active CPU billing, you pay only for the CPU your agents actually consume . Customers like OpenHands, Qencode, and Amplitude are building and scaling on Managed Agents, get started today .

Why are agentic workloads different from traditional cloud applications?

Developers and teams are asking agents to do increasingly ambitious work: implement features, investigate production issues, build new applications, research across systems, and coordinate subagents across different tasks. Consider an agent investigating a spike in checkout errors: it queries logs across several services through an MCP server, writes and runs a script to reproduce the bug, tests a fix, and opens a pull request for a teammate to review before it ships to production. Querying the logs, running the reproduction script, and testing the fix can each briefly demand substantial CPU and memory. Between those steps, and while it waits on tokens or a human approval, the agent may consume little or no CPU at all. But its context, files, and working state need to stay available the whole time, so it can pick back up exactly where it left off.

Agents working beyond software development use cases also need to execute code and produce artifacts others can use. An agent helping a team plan inventory might read sales datasets and supplier PDFs, run Monte Carlo simulations of demand and delivery delays, and produce reports recommending stock levels. To do that work, it needs an isolated sandbox to install dependencies and execute code that inspects results and generates reports for analysis. The datasets, scripts, and reports must outlive the session that created them, so a teammate can review the recommendations or another agent can update the analysis as new data arrives.

A traditional VM provides an empty computer, and leaves developers to build the environment and APIs that agentic workflows desperately need to get work done. Developers are forced to invest in plumbing work to preserve the agent’s context, persist artifacts and keep them accessible beyond the agent that created them, coordinate parallel work, and security-hardened access to tools. Keeping spare VMs running helps agents start quickly but adds idle cost; provisioning and configuring capacity on demand can take minutes, slowing work. Billing for provisioned CPU also continues while agents wait for model responses, tool results, or human approval. Time spent making VMs work for agents is time developers could spend making those agents better at the work customers care about.

Agentic work needs infrastructure built for it: security hardened code execution, persistent sessions, fast startup, and governed tool access. Checkpointing and forking let that work branch, pause, and continue across devices and teammates. Active CPU billing keeps cost tied to actual consumption. Designed as purpose-built primitives for agents rather than adapted from general purpose virtual machines, Managed Agents lets developers focus on what matters most: making agents capable of more valuable work .

DigitalOcean Managed Agents: Scale agentic work with purpose-built computing

Managed Agents brings together two services vertically integrated to deliver a great agentic experience.

DigitalOcean Harness Runtime combines the functionality of a lightweight microVM, built-in tools like chromium and a coding sandbox needed by agents to do work. The product also offers rich lifecycle APIs that persist conversational history and working state across sessions, along with pause/resume/fork semantics so that developers can control costs and adapt workflows to the nonlinear quirks of agentic work.

DigitalOcean Action Gateway gives agents governed access to 16,000+ tools through a single managed MCP endpoint. This includes tool integrations, like Web Search, Web Fetch, Browser Automation, and DigitalOcean infrastructure management APIs, along with connectors for widely used platforms like GitHub, HubSpot, Stripe, Snowflake, Box, Supabase, Exa and more. Teams can also extend the catalog with their own MCP servers and internal tools.

Together, they let developers scale the work their agents can do while DigitalOcean manages the execution, persistence, tool access, and infrastructure underneath. Let’s dive a bit deeper into each of these new services, their capabilities and how they enable you to scale agentic work in the cloud.

DigitalOcean Harness Runtime: Sessions that outlive your laptop

Harness Runtime gives agents a durable cloud workspace where they can execute code, work with artifacts, and continue across devices and teammates. It manages the compute, storage, and session lifecycle, so developers can run agents in parallel, explore different approaches, and return to ongoing work without reconstructing the environment or context. The runtime provides these critical capabilities these agents need:

Isolated execution with Firecracker microVMs. Each session runs inside a dedicated Firecracker microVM with its own compute resources and filesystem. Hardware virtualization isolates the environment where agents install dependencies, execute generated code, and run background processes.

Execution and Access APIs. Use exec to run commands, launch tests, and inspect the session’s environment. Security hardened port forwarding lets developers preview applications and connect to services running inside the session without exposing them publicly.

Pause and resume with snapshot storage. Pausing captures the...