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17-year internet software developer specializing in AI applications, networking, architecture, and open source. Led the delivery of network services handling hundreds of millions of concurrent devices and tens of millions of QPS, and has three years of experience designing and building an agent platform. Follow to stay updated.

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Recent Articles

Latest from Random Bulletin

81 recent articles
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Jun 23, 2026 · Backend Development

Choosing the Right Replication Factor for 10M QPS Message Queues: From Dual to Multi‑Replica

The article walks through why a single replica is insufficient for million‑scale message queues, explains the latency and data‑loss trade‑offs of dual‑replica sync and async modes, shows how three‑replica majority voting becomes the sweet spot, and then details the engineering considerations for scaling to five or more replicas across availability zones and regions.

AZ awarenessDistributed SystemsHigh Availability
0 likes · 18 min read
Choosing the Right Replication Factor for 10M QPS Message Queues: From Dual to Multi‑Replica
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Jun 20, 2026 · Backend Development

Message Ordering at 10M+ QPS: From Global to Partition to Business-Key

The article explains that message ordering is a spectrum—from strict global ordering to partition-level and finally business-key ordering—and examines the trade‑offs, pitfalls, and engineering techniques needed to maintain order while scaling to tens of millions of QPS.

Kafkabusiness keymessage ordering
0 likes · 24 min read
Message Ordering at 10M+ QPS: From Global to Partition to Business-Key
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Jun 18, 2026 · Operations

Zero Message Loss at 10M QPS: From Best‑Effort to Proven Guarantees

The article dissects why message loss is an end‑to‑end engineering challenge across production, broker, and consumer stages, presents real‑world failure cases at ten‑million QPS, and outlines concrete strategies—ack loops, outbox tables, broker replication settings, consumer handling rules, observability, reconciliation, and SLA‑driven compensation—to evolve from best‑effort to provable, recoverable reliability.

High QPSMessage QueueSLA
0 likes · 17 min read
Zero Message Loss at 10M QPS: From Best‑Effort to Proven Guarantees
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Jun 17, 2026 · Backend Development

Rebalance Optimization for Million‑QPS Kafka Clusters: From Default to Custom Assignors

At a 5,000‑instance, 20,000‑partition Kafka consumer cluster, the default eager Rebalance caused a 90‑second stop‑the‑world pause, illustrating how a single GC‑induced heartbeat miss can flood brokers with tens of millions of messages; the article dissects eager vs cooperative protocols, built‑in assignor limits, and four custom assignor patterns to scale Rebalance from 100 K to tens of millions of QPS.

AssignorCooperative ProtocolCustom Scheduler
0 likes · 28 min read
Rebalance Optimization for Million‑QPS Kafka Clusters: From Default to Custom Assignors
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Jun 16, 2026 · Backend Development

Consumer Rate Limiting: From Zero to Full Control in Million‑QPS Architectures

The article explains why consumer‑side rate limiting is essential in million‑QPS systems, detailing how unchecked consumers can overwhelm downstream services, and presents practical strategies—including pause/resume, token‑bucket algorithms, adaptive thresholds, and global coordination—to safely throttle consumption without dropping messages.

Distributed SystemsHigh QPSKafka
0 likes · 16 min read
Consumer Rate Limiting: From Zero to Full Control in Million‑QPS Architectures
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Jun 15, 2026 · Backend Development

From Auto to Manual: Mastering Consumer Offsets for Ten‑Million QPS Systems

The article examines a real payment loss incident caused by Kafka's default automatic offset commit, explains why automatic commits become a hidden trap at high traffic, and provides a step‑by‑step guide to switching to manual commits with async‑first, sync‑fallback, idempotency, dead‑letter handling, batch strategies, and concurrency controls for reliable ten‑million QPS consumption.

KafkaMessage Queuedead-letter queue
0 likes · 15 min read
From Auto to Manual: Mastering Consumer Offsets for Ten‑Million QPS Systems
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Jun 14, 2026 · Backend Development

Scaling to Millions of QPS: How Batch Consumption Beats Single-Message Processing

The article explains why single‑message consumption stalls under high QPS due to fixed per‑message overhead, and how merging pull, processing, and commit into batch operations dramatically boosts throughput while introducing trade‑offs in latency, memory, and failure handling, with practical guidelines for batch size selection and dynamic tuning.

KafkaMessage QueuePerformance Optimization
0 likes · 16 min read
Scaling to Millions of QPS: How Batch Consumption Beats Single-Message Processing
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Jun 13, 2026 · Backend Development

Scaling Consumer Parallelism: From Single‑Thread to Multi‑Thread for Ten‑Million QPS

The article analyzes why single‑threaded message consumption hits processing, I/O/CPU mismatch, and fault‑tolerance limits, then walks through a step‑by‑step evolution—pull/worker split, key‑based routing, sliding‑window offset commits, backpressure, and multi‑layer parallelism—to achieve stable ten‑million‑QPS throughput.

Message Queuebackpressureconsumer parallelism
0 likes · 22 min read
Scaling Consumer Parallelism: From Single‑Thread to Multi‑Thread for Ten‑Million QPS
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Jun 12, 2026 · Backend Development

From Random to Intelligent: Partition Selection Strategies for 10 Million QPS Systems

The article walks through four generations of partition‑selection strategies—from naive random and round‑robin to key‑hash, sticky, and finally intelligent load‑aware routing—explaining how hotspot keys, batch inefficiency, consumer skew, and fault amplification threaten stability at 10 M QPS and offering concrete engineering actions to design, test, monitor, and switch strategies in large‑scale message‑queue deployments.

Kafkahigh‑throughputhot‑key mitigation
0 likes · 20 min read
From Random to Intelligent: Partition Selection Strategies for 10 Million QPS Systems