can we use multiple agents in hybrid mode and what are the benefits?

Yes, you can use multiple agents in a hybrid deployment, and there are several benefits to doing so. According to the documentation, running multiple agents can be useful for scenarios such as high availability, redundancy, and managing workloads across different network segments or environments. For example, in a hybrid deployment on Google Cloud Platform (GCP), if you're using Google Kubernetes Engine (GKE), you can use the Kubernetes agent to manage your workloads. If GKE is not an option, you could use the Docker agent on a single node or instance. This flexibility allows you to adapt to the specific requirements of your deployment environment. In terms of benefits, having multiple agents can help with: 1. High Availability: Multiple agents can provide redundancy, ensuring that if one agent goes down, others can take over and continue to manage the workload without interruption. 2. Workload Management: You can have agents that are specialized for different types of workloads or that operate in different network segments, such as on-premises and cloud environments. This can help in preserving global lineage and providing overall orchestration while respecting network boundaries. 3. Scalability: Multiple agents can help distribute the workload, allowing for better scalability as the number of jobs or the computational requirements grow. 4. Isolation: Agents can be configured to handle specific code locations or environments, which can be useful for separating staging and production workloads, for example. It's important to note that with the release of Dagster 1.6.0, a feature called agent routing was introduced, which allows you to route specific code locations to specific agents. This feature is particularly useful if you want to ensure that each agent operates solely within its designated environment. However, this feature requires a Dagster Cloud Pro subscription. In summary, using multiple agents in a hybrid deployment can enhance the robustness, scalability, and flexibility of your data pipelines, allowing you to tailor the orchestration to your specific operational needs.