## Where DACA **does** fill the holes

| Limitation from your list | How DACA addresses it |
| --- | --- |
| **Agent-centric logging & observability** | Dapr sidecars emit OpenTelemetry/Prometheus metrics and traces that track actor calls, A2A round-trips, tool invocations, and reasoning paths — all machine-parsable by other agents  |
| **Integrated architecture** | A three-tier, event-driven micro-services stack (presentation / agent logic / data) plus Dapr workflows gives a single, opinionated blueprint instead of scattered bolt-ons   |
| **Real-time, low-latency processing** | Stateless containers talk over Kafka/RabbitMQ with back-pressure and retries; Dapr pub/sub keeps message hops inside the node when possible   |
| **Scalability & cost efficiency** | Horizontal scaling on Kubernetes or Azure Container Apps; pay-as-you-go state stores like CockroachDB Serverless keep idle costs near zero  |
| **Standardised APIs** | A2A exposes capability cards and task endpoints; MCP normalises tool/function calling, so every agent and tool speaks the same dialect  |
| **Persistent memory & state management** | Dapr Actors wrap each agent in a lightweight stateful object with automatic reminders, timers, and pluggable state stores (Redis, Cockroach, etc.)   |
| **Seamless agent collaboration & orchestration** | A2A for cross-domain chatter + Dapr Workflows for long-running, fan-out/fan-in orchestrations   |
| **Vendor lock-in mitigation** | “Open-core / managed-edges” mantra: Kubernetes + Dapr at the core, swap-in managed DBs or LLM APIs at the rim   |

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