Agent deployment modes
Deploy the agent by using either stand-alone mode or embedded mode, depending on your system architecture and integration requirements.
The agent can be deployed in the following ways.
- Stand-alone mode. In stand-alone mode, the agent operates as a separate component alongside the
runtime. Therefore, the agent continues to function independently even if the runtime shuts down.
This mode is relevant when developers do not have access to the runtime's source code. For instance, if developer wants to connect AWS gateway to federated API management, the stand-alone mode is the appropriate choice as the developer does not have access to the source code of AWS gateway.
Pros Cons Independent from runtime. Offers flexibility and resilience, as the agent can continue to run even if the runtime is down or undergoing maintenance. Increased complexity. Introduces more complexity in terms of deployment, configuration, and management. It requires coordination between the agent and runtime components. Modular deployment. Simplifies management and allows faster updates and scaling. Potential resource overhead. Incurs resource overhead compared to embedded mode. - Embedded mode. In embedded mode, the agent implementation becomes integrated within the runtime
source code. Upon initiating the runtime application, the agent initializes alongside it. This tight
coupling ensures that the agent operates while the runtime is active and becomes inactive when the
runtime shuts down.
This mode is only relevant when developers have access to the runtime's source code, and when the runtime's source code is developed in Java™. Because the agent SDK code is also written in Java.
Pros Cons Tight integration. Reduces the operational complexity. Limited flexibility. Changes to the agent might require modifications to the runtime code, leading to operational complexities and dependencies. Ease of deployment. Eliminates the need for separate deployment or configuration steps. Possible resource utilization. Excessive consumption by the agent might overkill the runtime performance and operation. Resource efficiency. Consumes fewer resources compared to stand-alone mode as it operates within the same runtime environment. Potential runtime instability. Any issues or instability in the agent might affect the overall runtime performance and stability.