Render Sandboxes give every agent its own isolated Linux computer. Sandboxes starts in under a second and can run any agent or harness, like Claude Code or Codex. Your agent can also run your app with Docker Compose to test its changes. You decide which domains each sandbox can reach. When your agent goes idle, the sandbox suspends and compute charges stop. It wakes with files and memory intact. And you can reliably run thousands at once - all on the same platform as the rest of your app.
I've run a dozen or more coding agents at once on one 48GB Mac. In September that took the whole machine down from memory exhaustion and every session died together, so the isolation is the part I care about here. What happens when one sandbox hits its memory limit: does only that agent die while the others keep going? And how well does suspend and wake hold up with a big install? Our node_modules is 18GB.
Congrats on the launch! How would you recommend running long AI jobs alongside a web API on Render? I'd be especially interested in what happens to jobs already in progress during a deployment.
Keeping memory and files through a pause is useful for longer tasks. When debugging a retry, I'd also want to see clearly which work resumed and which work ran again.
Hey Product Hunt 👋 I'm Slav, PM for Render Sandboxes.
The work agents are given is becoming increasingly complex. Like people, agents need machines on which to do this work, so they can write and run code, install dependencies, manipulate files, and more.
But not just any machine will do! To work safely, agents need a separate machine for each task or user, isolated from your app and from each other. And since agent work comes in bursts, those machines need to start and stop with demand.
Render Sandboxes give each user or task its own machine the moment it’s needed. Each sandbox runs in its own Firecracker microVM.
Speed: a sandbox is ready for its first command in under a second.
Scale: you can run thousands of sandboxes at once, reliably.
Security: you can set each sandbox to allow all outbound traffic, allow only the domains you list, or block outbound traffic entirely. Credential brokering (now in early access; let us know if you're interested) adds your API keys to outgoing requests, so the keys never sit inside the sandbox.
Pricing: you pay for the CPU a sandbox actually uses and the memory it allocates. A suspended sandbox stops both charges and billing, except for snapshot storage.
Long-running work: A sandbox can run with no time limit. When it goes idle, Render suspends it and wakes it on the next command with its files and memory intact.
One platform: your sandboxes live in the same workspace as your web services, background workers, and Render Postgres databases, with one API key, one SDK, and one bill.
Teams use Render Sandboxes to run an agent harness like Claude Code or Codex inside a sandbox, to start a full copy of an app so a coding agent can test its changes, and to run code and files they didn't write.
Render Sandboxes are in public beta - tell us if anything feels missing or doesn't work as expected. We'll be here throughout the day answering questions!
About Render Sandboxes on Product Hunt
“A computer for every agent”
Render Sandboxes launched on Product Hunt on November 4th, 2026 and earned 109 upvotes and 7 comments, placing #8 on the daily leaderboard. Render Sandboxes give every agent its own isolated Linux computer. Sandboxes starts in under a second and can run any agent or harness, like Claude Code or Codex. Your agent can also run your app with Docker Compose to test its changes. You decide which domains each sandbox can reach. When your agent goes idle, the sandbox suspends and compute charges stop. It wakes with files and memory intact. And you can reliably run thousands at once - all on the same platform as the rest of your app.
Render Sandboxes was featured in Developer Tools (522.4k followers), Artificial Intelligence (482.8k followers) and SDK (871 followers) on Product Hunt. Together, these topics include over 227.2k products, making this a competitive space to launch in.
Who hunted Render Sandboxes?
Render Sandboxes was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Render Sandboxes stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ben Lang
I've run a dozen or more coding agents at once on one 48GB Mac. In September that took the whole machine down from memory exhaustion and every session died together, so the isolation is the part I care about here. What happens when one sandbox hits its memory limit: does only that agent die while the others keep going? And how well does suspend and wake hold up with a big install? Our node_modules is 18GB.