GoQueue - The flexible Go job queue that grows with you. Start with in-memory for development, scale to Redis for production, or deploy to AWS SQS for the cloud. Built-in retries, DLQ, middleware pipeline, and observability - everything you need for reliable background processing.

基于 Flutter 和 Gin 的前端分离的记账工具的服务端部分

Supercharge your async applications with tasks so fast, you’ll think you’re bending time itself.

A sample of non-blocking retries and dead letter topics (aka reliable reprocessing and dead letter queues) with Apache Kafka using Spring Boot and Spring Kafka.

A tiny go package to manage HTTP requests with dead letter management/retry. Based on go-redis.

CLI to bring your messages back from SQS Dead Letter Queues.

A monorepo, microservice setup with full support for CI/CD, kafka as a message broker, inter-service API using service discovery endpoint

Reliable Message Processing with Dead-Letter-Queues Replay

Spring RabbitMQ Dead Letter Queue (DLQ) Example

simple rabbitmq retry mechanism with ttl + dead lettering

Reliably process messages in queue with dead-letter queues in SQS

Serverless image processor built with Go, AWS Lambda, S3, and SQS. Automatically creates thumbnails and medium-sized versions of uploaded images with optimized compression.

Exploring spring rabbitmq dead letter queue

Production-ready Go library with 8 essential design patterns: Bloom Filter, Bulkhead, Circuit Breaker, Dead Letter Queue, Pub/Sub, Redlock, Retry, and Worker Pool. Enterprise-grade with security hardening, comprehensive testing, and performance optimization.

Transport-agnostic messaging contracts & helpers for AmpyFin: Protobuf envelopes, NATS/Kafka bindings, DLQ/replay, metrics, Go/Python SDKs.

Implementation Fast Search use Meilisearch using CQRS Pattern, CDC pattern, Queue Pattern, Dead Letter Queue and Scheduler Sync Cross DB.

A production-grade, open-source Go module for high-performance, asynchronous RabbitMQ messaging with extensibility to Kafka, featuring built-in connection pooling, memory optimization, observability, security, fault tolerance, and comprehensive profiling.

Loading data into DynamoDB Global Table with KMS encryption enabled using Kinesis-Lambda

A set of scripts that help with DLQ message processing

This is an event-driven microservices architecture implementation running on docker containers.