Akka

An endpoint is how a service is exposed to the outside world. HTTP endpoints accept and return JSON by default.

Workflows run long-running, multi-step business processes while you write only the domain logic. They provide durability and consistency, and can call other components and services.

An agent interacts with an AI model to perform a specific task. It keeps contextual history in session memory, which can be shared with other agents working toward the same goal.

An agent can delegate to specialists, hand off to peers, or lead a team sharing a task list, so multi-agent systems are assembled from focused agents without writing orchestration code.

MCP endpoints expose a service to MCP clients, including LLM desktop applications and agents running on other services. What you expose becomes tools the model can call on its own behalf.

Instead of storing the current state, these persist every event that led to it, written to a journal with ACID semantics.

These persist state as a single current value, keyed by id. Akka guarantees exactly one instance of each entity across the whole cluster, so commands are handled one at a time with no concurrency to reason about.

Views let you read across many entities, or find an entity by something other than its id. Each view is built for a specific access pattern and updates as the underlying entity state changes.

Consumers read a stream of events, from an entity's journal, from key value state changes, or from a message broker topic. They also produce events outward, which is how an Akka service interacts with systems beyond it.

Timers schedule a call to run later, which is useful for checking whether something completed after the fact. They are stored by the runtime and guaranteed to run at least once: if the call fails, the timer reschedules itself until it succeeds.

Binary serialization and protobuf's forward and backward compatibility make service-to-service calls fast and safe to evolve without breaking existing clients.