Asynchronous message passing system enabling decoupled communication between AI agents and services in distributed agentic systems
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Asynchronous message passing system enabling decoupled communication between AI agents and services in distributed agentic systems
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Message Queuing enables asynchronous, decoupled communication between producers and consumers via durable queues. Brokers provide delivery guarantees (at-least-once, at-most-once, sometimes exactly-once), ordering options (per-partition/group), acknowledgments, retries, and dead-lettering. Common implementations include Apache Kafka (log-based partitions, consumer groups), RabbitMQ/AMQP (queues, exchanges, bindings), cloud queues like AWS SQS and Google Pub/Sub, NATS JetStream, and Redis Streams.
Ultra low-latency, synchronous request/response paths where queueing overhead breaks SLOs → prefer direct RPC (gRPC/REST).
Strict global ordering across high-throughput streams when the broker cannot guarantee it without severe throughput loss.
Simple, tightly coupled integrations where a queue adds operational complexity without clear benefit.
Relying on implicit ordering across partitions/queues; not keying messages consistently.
Non-idempotent side effects with retries → duplicates and data corruption.
Unbounded queue growth and consumer lag due to missing backpressure or insufficient scaling.
Retry storms and thundering herds; missing circuit breakers and jittered backoff.
Large payloads in the broker; lack of schema evolution strategy leading to consumer breakage.
Resource profile: CPU for serialization/compression and broker coordination; memory for buffers; disk I/O for durable logs; network for replication and client traffic.
Optimize with batching and compression; right-size partitions/consumer concurrency; bound message size (e.g., SQS 256 KB, Pub/Sub 10 MB, Kafka configurable).
Avoid embedding large blobs; store externally and send references; apply per-tenant quotas and rate limits.
Decoupling microservices; asynchronous workflows; background job processing.
Event-driven architectures and fan-out processing; audit/event logs.
Load leveling and burst smoothing; backpressure control in downstreams.
Cross-region buffering and intermittent-connectivity resilience.
Message Queuing enables asynchronous, decoupled communication between producers and consumers via durable queues. Brokers provide delivery guarantees (at-least-once, at-most-once, sometimes exactly-once), ordering options (per-partition/group), acknowledgments, retries, and dead-lettering. Common implementations include Apache Kafka (log-based partitions, consumer groups), RabbitMQ/AMQP (queues, exchanges, bindings), cloud queues like AWS SQS and Google Pub/Sub, NATS JetStream, and Redis Streams.
Ultra low-latency, synchronous request/response paths where queueing overhead breaks SLOs → prefer direct RPC (gRPC/REST).
Strict global ordering across high-throughput streams when the broker cannot guarantee it without severe throughput loss.
Simple, tightly coupled integrations where a queue adds operational complexity without clear benefit.
Relying on implicit ordering across partitions/queues; not keying messages consistently.
Non-idempotent side effects with retries → duplicates and data corruption.
Unbounded queue growth and consumer lag due to missing backpressure or insufficient scaling.
Retry storms and thundering herds; missing circuit breakers and jittered backoff.
Large payloads in the broker; lack of schema evolution strategy leading to consumer breakage.
Resource profile: CPU for serialization/compression and broker coordination; memory for buffers; disk I/O for durable logs; network for replication and client traffic.
Optimize with batching and compression; right-size partitions/consumer concurrency; bound message size (e.g., SQS 256 KB, Pub/Sub 10 MB, Kafka configurable).
Avoid embedding large blobs; store externally and send references; apply per-tenant quotas and rate limits.
Decoupling microservices; asynchronous workflows; background job processing.
Event-driven architectures and fan-out processing; audit/event logs.
Load leveling and burst smoothing; backpressure control in downstreams.
Cross-region buffering and intermittent-connectivity resilience.