Tag: messaging

Use Redis pub/sub channels to broadcast events between processes, handle subscriptions, and implement real-time notifications

Handle failed messages gracefully with dead letter queues, retry policies, and poison pill detection in message-driven architectures.

Design event-driven microservices with message brokers, event sourcing, CQRS, and eventual consistency patterns.

Build growth-ready event-driven systems using Apache Kafka with producers, consumers, consumer groups, and exactly-once semantics for reliable asynchronous messaging

Design idempotent message processors that safely handle duplicate deliveries without side effects in async and event-driven systems.

Implement reliable task distribution and request-reply patterns using RabbitMQ with durable queues, dead-letter exchanges, and prefetch for controlled concurrency

Build real-time pub/sub messaging with Redis and Python including pattern subscriptions, message serialization, connection pooling, and broadcast patterns for microservices.

Store large payloads in external storage and pass only a lightweight reference token through the message bus, reducing broker load and preventing message size limits from being exceeded.

Capture and publish major occurrences within a domain model to decouple side effects from core business logic and enable reactive workflows.

Decouple components by routing events through a central bus. A behavioral pattern for loosely coupled communication between modules.

Process messages from a queue exactly once regardless of duplicates by using idempotent operations, unique identifiers, and deduplication strategies at the consumer level.

Use a dedicated inbox table or queue to record incoming events or requests, ensuring reliable delivery, deduplication, and idempotent processing even when downstream systems fail.

Reliably publish domain events by persisting them in an outbox table within the same database transaction as the business operation.

Introduce a queue between task producers and consumers to smooth out traffic spikes, decouple components, and prevent downstream services from being overwhelmed by burst workloads.

Preserve message ordering for related messages in a distributed system by grouping them into ordered sequences and processing them one at a time through a single consumer.

Runbook for handling and replaying dead letter queue messages in Kafka and RabbitMQ: DLQ setup, inspection procedures, root cause analysis, replay strategies, monitoring alerts, and automation scripts for failed message recovery.

Template for standardizing Kafka topic names across teams: naming patterns, environment prefixes, domain segmentation, event type suffixes, partition count rules, and retention policies with examples.

Policy for evolving message schemas safely in event-driven systems: backward and forward compatibility rules, schema registry usage, versioning strategies, migration procedures, and breaking change handling with Avro, Protobuf, and JSON examples.

Template for documenting RabbitMQ queue, exchange, and binding design: exchange types, queue properties, binding rules, dead letter handling, TTL policies, and capacity planning with code examples.

Build real-time event streaming pipelines with Kafka. Covers producers, consumers, Kafka Streams, Kafka Connect, schema registry, and stream processing patterns.

Design and operate event-driven backends. Covers event sourcing, CQRS, sagas, outbox pattern, idempotency, eventual consistency, and production patterns for reliable event-driven architectures.

Run Apache Kafka in production with confidence. Covers partitions, replication, consumer groups, monitoring, performance tuning, and operational best practices for high-throughput streaming pipelines.

Design and operate RabbitMQ for reliable messaging. Covers exchanges, queues, bindings, routing patterns, dead letter queues, clustering, and production best practices for high-throughput workloads.

A thorough guide to message queues: when to use RabbitMQ, Kafka, or SQS. Covers patterns, throughput, ordering, and operational considerations.