Open-source AI infrastructure
Daytona's open source repository stopped receiving updates in June 2026 when core development moved to a private codebase. What that means if you were planning to s…
Daytona's README states it plainly: as of June 2026 core development moved to a private codebase, and the repository will receive no further updates, fixes or releases. It remains public and free to use, fork and build on, as is and without support or warranty. The last commit landed on 25 June 2026. The 71,871 GitHub stars are attached to a tree that has stopped moving.
The initial commit on 6 February 2024 was Apache-2.0. A commit on 28 April 2025 relicensed the project to AGPL-3.0 alongside the AI-sandbox pivot, shipped as v0.100.0. A commit on 23 June 2026 deleted the LICENSE file entirely, and GitHub now reports the repository licence as none. The last open release, v0.190.0, is AGPL-3.0, and the README points forks at that tag. If you were planning to fork, that tag is the thing to fork.
Daytona's documentation says default sandboxes are Linux containers, with VM sandboxes offered as a separate option. The repository README claims each sandbox has a dedicated kernel, filesystem and network stack, which describes a VM rather than a container. Both statements are theirs and we are not harmonising them. For untrusted, model-generated code, get the answer in writing before you commit.
The notice concerns the open source repository. Daytona the company continues to develop the product and their hosted service is unaffected. If you are a hosted customer, none of this is your problem. If your plan was to self-host, you would be running an unmaintained snapshot including for security fixes.
Daytona documents sandboxes starting in under 90 milliseconds from code to execution, which is faster than Everstack claims. Their stateful snapshot support is also more mature than ours. If you spawn a sandbox per request rather than per session, that latency number may outweigh everything else here.