TAG
Message_Queue
19 notes
- 1.1 Message Queues and Event Logshistorical
Why asynchronous messaging exists, queue vs. pub-sub/log models, delivery semantics, backpressure, idempotency, ordering, and the trade-offs introduced by a broker.
- 1.2 Message Orderinghistorical
How to preserve per-entity message order through partitioning, producer sequencing, consumer concurrency control, and idempotent version checks.
- Kafka Installation and Local Setuphistorical
A version-neutral Kafka local setup guide that distinguishes modern KRaft deployments from historical ZooKeeper-based instructions.
- 2.2 Kafka Introductionhistorical
Kafka as a distributed durable event log for messaging, storage, replay, and stream processing.
- Kafka Usage Guidehistorical
A compact Kafka workflow for topics, producers, consumers, groups, offsets, and administration without freezing the note to one old CLI syntax.
- 2.4 Kafka Architecturehistorical
Kafka producers, partition leaders/followers, brokers, consumers, KRaft metadata quorum, replication, failover, and partitioned scaling.
- 2.5 Kafka Producershistorical
Kafka producer batching, serialization, partitioning, acknowledgements, retries, idempotent production, transactions, and their exact scope.
- 2.6 Kafka Brokers and Replicationhistorical
Kafka broker responsibilities, modern controllers, ISR/min.insync.replicas, producer acknowledgements, leader election, and durability trade-offs.
- 2.7 Kafka Consumers and Consumer Groupshistorical
Kafka consumer groups, partition assignment, offsets, rebalancing, at-least-once processing, idempotency, and modern cooperative rebalancing considerations.
- 2.8 Kafka Log Storagehistorical
Kafka partition log segments, sparse indexes, retention vs. compaction, page cache, sequential I/O, batching, and zero-copy-related transport efficiency.
- 2.9 Kafka Topics, Partitions, Offsets, and Replicashistorical
Kafka topic/partition semantics, per-partition ordering, offsets, replication, ISR, high watermark, retention, and reassignment.
- Kafka Performance Tuninghistorical
Kafka tuning as a balance among throughput, latency, durability, batching, compression, partition count, storage, and consumer lag.
- Kafka Benchmarkinghistorical
How to benchmark Kafka producer, broker, and consumer capacity with realistic record sizes, partitions, replication, acknowledgements, compression, and end-to-end lag.
- Managed Kafkahistorical
What managed Kafka services operate for you, what semantics remain your responsibility, and how to evaluate compatibility, networking, scaling, and cost.
- Reading Kafka Source Codehistorical
A value-first route through Kafka source: protocol requests, producer batching, broker append/fetch, replication, group coordination, and KRaft metadata.
- 3. RabbitMQhistorical
RabbitMQ fundamentals: exchanges, queues, bindings, routing, acknowledgements, publisher confirms, and modern quorum-queue high availability.
- 3.1 RabbitMQ Routing and Usagehistorical
RabbitMQ exchanges, bindings, queues, direct/fanout/topic routing, work queues, acknowledgements, prefetch, and dead-letter patterns.
- 3.2 RabbitMQ Message Reliabilityhistorical
Publisher confirms, durable queues, persistent messages, quorum queues, consumer acknowledgements, redelivery, and why end-to-end idempotency is still required.
- 3.3 RabbitMQ Clustering and Quorum Queueshistorical
Modern RabbitMQ cluster responsibilities, queue data placement, quorum queues, leader/follower replication, and the legacy status of mirrored classic queues.