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daytonaio daytona
Daytona is a Secure and Elastic Infrastructure for Running AI-Generated Code
Stars
71
Forks
5,649
Watchers: 71,823
Language
—
Github
Repository Radar Score
44 / 100
Growth
- 7d
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Last observed: 5 days ago
Score breakdown
- popularity 46
- growth 0
- activity 55
- freshness 100
- community 88
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This repository is no longer maintained.
As of June 2026, Daytona's core development has moved to a private codebase. This repository will receive no further updates, fixes, or releases. It remains public and free to use, fork, and build on under the LICENSE, as is and without support or warranty.
Daytona resources are available at github.com/daytona.
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Daytona is a secure and elastic infrastructure runtime for AI-generated code execution and agent workflows. Our open-source platform provides sandboxes, full composable computers with complete isolation, a dedicated kernel, filesystem, network stack, and allocated vCPU, RAM, and disk.
Sandboxes are the core component of the Daytona platform, spinning up in under 90ms from code to execution and running any code in Python, TypeScript, and JavaScript. Built on OCI/Docker compatibility, massive parallelization, and unlimited persistence, sandboxes deliver consistent, predictable environments for agent workflows.
Agents and developers interact with sandboxes programmatically using the Daytona SDKs, API, and CLI. Operations span sandbox lifecycle management, filesystem operations, process and code execution, and runtime configuration through base images, packages, and tooling. Our stateful environment snapshots enable persistent agent operations across sessions, making Daytona the ideal foundation for AI agent architectures.
Daytona provides an extensive set of features and tools for interacting with sandboxes.
- Platform: governance and operational controls for organizations standardizing on Daytona
- Sandboxes: isolated full composable computers that execute workloads and retain state
- Agent tools: programmatic capabilities for application code, agents, and integrations
- Human tools: interfaces and remote sessions for interacting with sandboxes
- System tools: platform-level hooks and controls for lifecycle events and network access
Daytona platform is organized into multiple plane components, each serving a specific purpose. A detailed overview of each component is available in the architecture documentation.
- Interface plane: provides client interfaces for interacting with Daytona
- Control plane: orchestrates all sandbox operations
- Compute plane: runs and manages sandbox instances
Client libraries integrate the Daytona platform from application code through developer-facing SDKs backed by OpenAPI-generated REST clients and toolbox API clients. Each directory is a publishable package for a specific language or runtime, available in the libs directory.
pip install daytonaStandalone packages and libraries for interacting with Daytona using Python:
sdk-python•api-client-python•api-client-python-async•toolbox-api-client-python•toolbox-api-client-python-async
npm install @daytona/sdkStandalone packages and libraries for interacting with Daytona using TypeScript:
gem install daytonaStandalone packages and libraries for interacting with Daytona using Ruby:
go get github.com/daytonaio/daytona/libs/sdk-goStandalone packages and libraries for interacting with Daytona using Go:
Gradle (build.gradle.kts):
dependencies {
implementation("io.daytona:sdk:x.y.z")
}Maven (pom.xml):
<dependency>
<groupId>io.daytona</groupId>
<artifactId>sdk</artifactId>
<version>x.y.z</version>
</dependency>Standalone packages and libraries for interacting with Daytona using Java:
- Create an account at app.daytona.io
- Generate an API key
- Create a sandbox
from daytona import Daytona, DaytonaConfig
config = DaytonaConfig(api_key="YOUR_API_KEY")
daytona = Daytona(config)
sandbox = daytona.create()
response = sandbox.process.code_run('print("Hello World!")')
print(response.result)import { Daytona } from "@daytona/sdk";
const daytona = new Daytona({ apiKey: "YOUR_API_KEY" });
const sandbox = await daytona.create();
const response = await sandbox.process.codeRun('print("Hello World!")');
console.log(response.result);require 'daytona'
config = Daytona::Config.new(api_key: 'YOUR_API_KEY')
daytona = Daytona::Daytona.new(config)
sandbox = daytona.create
response = sandbox.process.code_run(code: 'print("Hello World!")')
puts response.resultpackage main
import (
"context"
"fmt"
"github.com/daytonaio/daytona/libs/sdk-go/pkg/daytona"
"github.com/daytonaio/daytona/libs/sdk-go/pkg/types"
)
func main() {
config := &types.DaytonaConfig{APIKey: "YOUR_API_KEY"}
client, _ := daytona.NewClientWithConfig(config)
ctx := context.Background()
sandbox, _ := client.Create(ctx, nil)
response, _ := sandbox.Process.ExecuteCommand(ctx, "echo 'Hello World!'")
fmt.Println(response.Result)
}import io.daytona.sdk.Daytona;
import io.daytona.sdk.DaytonaConfig;
import io.daytona.sdk.Sandbox;
import io.daytona.sdk.model.ExecuteResponse;
public class Main {
public static void main(String[] args) {
DaytonaConfig config = new DaytonaConfig.Builder()
.apiKey("YOUR_API_KEY")
.build();
try (Daytona daytona = new Daytona(config)) {
Sandbox sandbox = daytona.create();
ExecuteResponse response = sandbox.getProcess().executeCommand("echo 'Hello World!'");
System.out.println(response.getResult());
}
}
}curl 'https://app.daytona.io/api/sandbox' \
--request POST \
--header 'Authorization: Bearer <YOUR_API_KEY>' \
--header 'Content-Type: application/json' \
--data '{}'daytona createRepository Radar analysis
Deterministic insights derived from public metadata and our observations — not personal testing or reviews.
Why this repository is interesting
- Listed in our discovery index with public GitHub metadata for analysis.
Who should use it
- Teams exploring AI tooling, agents, or ML infrastructure
Potential use cases
- Prototype AI/agent workflows or study reference architectures
Strengths
- README present in our index
- Substantial fork count (5,649) suggests reuse and contribution interest
Limitations / considerations
- License not recorded in our index — confirm on GitHub before production use
What to watch
- Re-check last push, issues, and releases on GitHub before production adoption
Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.
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