Finance ML Modeling in Databricks

Can you please explain your experience in databricks platform, end to end deployment, monitoring, ml lifecycle management, experimentation, model provisioning, model serving, alerting monitoring, retraining, data drift, model drift, vm design for databricks workspace, databricks optimization and performance techniques, canary deployment on databricks, databricks genie, agentbricks, multi-agent orchestration, long running agent management, episodic, procedural, semantic memory, evaluation, observability, tracing , humna in the loop, unity catalog, databricks lakehosue, databricks api gateway, databricks security, databricks governance and authentication, we need to build databricks native solution completely on databricks utilizing all databricks features, capabilities, architures and resources?