Ollama Integration with Fly.io Sprites for Secure AI Agent Deployment

Ollama integration with Fly.io Sprites allows developers to run AI agents in secure, isolated Linux virtual machines with persistent storage, supporting models like kimi-k3 and deepseek-v4.1-flash.

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Integration of Ollama with Fly.io Sprites

The integration of Ollama with Fly.io Sprites enables developers to run AI agents in secure, isolated environments. Each Sprite is a full Linux virtual machine with persistent storage, allowing for stateful operations between sessions. This setup supports the use of advanced models such as kimi-k3, glm-5.3, and deepseek-v4.1-flash through the new Ollama Connector. This combination provides a scalable and reliable infrastructure for deploying AI agents without compromising security or performance. The Ollama Cloud integration within Fly.io Sprites is described in Ollama.

Security and API Key Management

When using Ollama with Fly.io, security and API key management are handled through a combination of encryption and gateway-based authentication. According to Ollama, users add their Ollama API key to their Fly.io organization, and Fly.io encrypts it, ensuring it is never returned through the API. When code inside a Sprite calls Ollama, it goes through a Fly.io gateway, as noted in Ollama. This gateway automatically adds the API key, eliminating the need for an Authorization header, as stated in Ollama. This approach minimizes exposure of sensitive credentials and reduces the risk of API key leakage. The process ensures that developers do not need to handle or transmit the key directly, enhancing security without requiring changes to the application logic.

Implementation and Setup Process

To implement AI agents using Ollama and Fly.io, begin by obtaining an Ollama API key and ensuring you have at least one Sprite available for deployment (Ollama). Next, navigate to the Fly.io dashboard and access the Sprites section. From there, select Connectors and add an Ollama connector, entering your API key when prompted (Ollama). Finally, configure access settings by specifying which Sprites are permitted to use the connector, then save your changes (Ollama). This setup enables secure and scalable deployment of AI agents without requiring direct API key exposure across multiple environments.

Usage of Ollama Models in Sprites

To use Ollama models within Sprites, first verify connectivity by clicking 'Test reachability' next to a Sprite to ensure it can access Ollama. Once confirmed, use the provided curl command from within the Sprite, replacing <connection_id> with your specific ID. This command sends a request to the Sprites gateway, which routes it to the Ollama service. Alternatively, developers can configure an OpenAI-compatible client by setting the base_url to the gateway endpoint and specifying an api_key (which may be unused depending on the setup). Ollama’s native /api/* routes also function through the Sprites gateway, enabling seamless integration of AI models into applications hosted on the platform.

Agent Capabilities and Example Use Cases

Agent capabilities on Fly.io Sprites are enhanced through integration with Ollama, allowing AI models to interact with code generation tools like Claude Code, Cursor, Codex, and Gemini CLI. When a Sprite has access, agents can leverage Ollama models without requiring additional setup, streamlining development workflows. For example, a smaller model like nemotron-3-nano:30b may produce malformed inputs, which a Sprite can then run against a program to test its robustness. A larger model, such as kimi-k3, can analyze the resulting crashes, providing insights into potential issues. These use cases demonstrate how Ollama and Fly.io can be combined to improve the reliability and performance of AI-driven development tools.