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Random Bulletin

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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Latest from Random Bulletin

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Random Bulletin

Sep 7, 2026 · Operations

Fault Injection at Scale: Turning Paper Capacity into Trusted Resilience

This article explains why traditional capacity planning fails under real faults, detailing how to build continuous fault injection practices with hypothesis-driven experiments, blast radius control, automated stop conditions, and fault capacity maps to transform theoretical headroom into verified effective throughput at 10M QPS scale.

Fault Injectionblast radiuscapacity map

0 likes · 32 min read

Fault Injection at Scale: Turning Paper Capacity into Trusted Resilience

Random Bulletin

Sep 6, 2026 · Operations

Continuous Load Testing: Keeping Capacity Evidence in Sync with System Evolution at 10M QPS

This article explains why ad-hoc load testing fails at scale and details a four-stage evolution toward continuous load testing, covering baseline regression, release gates, failure capacity verification, production safety boundaries, and organizational ownership to keep capacity evidence current with system changes.

QPSSystem architecturebaseline regression

0 likes · 40 min read

Continuous Load Testing: Keeping Capacity Evidence in Sync with System Evolution at 10M QPS

Random Bulletin

Sep 5, 2026 · Operations

Why Static 80% Thresholds Fail at 10M QPS: Dynamic Water Level Management

The article explains why fixed thresholds like 80% CPU are inadequate for large-scale systems, and introduces dynamic water level management that combines load, resource, service, and resilience signals with capacity profiling, trend prediction, and action latency to drive automated scaling, scheduling, rate limiting, and degradation in a closed loop.

10M QPSAuto-scalingSLO

0 likes · 31 min read

Why Static 80% Thresholds Fail at 10M QPS: Dynamic Water Level Management

Random Bulletin

Sep 4, 2026 · Operations

Capacity Prediction at 10M QPS: From Gut Feel to Data-Driven Decisions

This article explains why experience-based capacity planning fails at 10M QPS scale and presents a data-driven framework separating business demand, system load, and resource capacity, using prediction intervals, error feedback loops, and incremental model building to turn vague traffic estimates into verifiable resource decisions.

QPS scalingSystem architecturecapacity planning

0 likes · 30 min read

Capacity Prediction at 10M QPS: From Gut Feel to Data-Driven Decisions

Random Bulletin

Sep 2, 2026 · Operations

Automating Root‑Cause Analysis for Million‑QPS Systems: From Manual to AI‑Assisted

When a transaction‑success rate dropped at 02:13 AM and 186 alerts flooded the on‑call channel, engineers struggled to piece together fragmented evidence, highlighting why manual root‑cause analysis is slow at scale and how an evidence‑driven automated pipeline can narrow investigation space, rank candidates with confidence, and keep humans in the loop for safe remediation.

Root Cause AnalysisSite Reliability Engineeringautomation

0 likes · 26 min read

Automating Root‑Cause Analysis for Million‑QPS Systems: From Manual to AI‑Assisted

Random Bulletin

Sep 1, 2026 · Operations

From Manual to Automatic: Scaling Alert Automation for Million‑QPS Systems

The article examines why manual alert handling stalls at massive scale, outlines the risks of naïve auto‑rollback, and presents a step‑by‑step framework—including event control planes, executable runbooks, safety guards, and staged automation—to reliably move from human‑only to fully automated incident response in high‑throughput environments.

alert automationincident responseobservability

0 likes · 23 min read

From Manual to Automatic: Scaling Alert Automation for Million‑QPS Systems

Random Bulletin

Aug 30, 2026 · Operations

Alert Tiering: From a Single Level to a P0‑P3 Multi‑Level Response System

The article examines why a single‑level alerting approach fails at massive scale, outlines the five practical limitations it creates, and presents a step‑by‑step framework—classification matrix, routed channels, SLA timers, escalation policies, and on‑call discipline—to allocate limited human attention to the most business‑critical incidents.

Incident ManagementSLAalert tiering

0 likes · 18 min read

Alert Tiering: From a Single Level to a P0‑P3 Multi‑Level Response System

Random Bulletin

Aug 29, 2026 · Operations

Alert Convergence at Scale: From Simple Deduplication to AI‑Driven Clustering

A 40‑second DB jitter triggered over 3,000 alerts, but by applying a five‑layer alert‑convergence strategy—deduplication, grouping, inhibition & silencing, dependency‑based aggregation, and AI‑powered clustering—teams can reduce noise by up to 90 %, turning a storm of notifications into a single actionable signal.

AIOpsIncident Managementalerting

0 likes · 19 min read

Alert Convergence at Scale: From Simple Deduplication to AI‑Driven Clustering

Random Bulletin

Aug 28, 2026 · Operations

Log Correlation: From Isolated Entries to Linked Traces in High‑QPS Systems

The article explains how to turn millions of independent error logs into a coherent, request‑level waterfall and business‑level story by injecting trace_id, business keys, and cross‑signal foreign keys, while addressing async boundaries, sampling, naming consistency, and storage costs.

distributed-tracinglog correlationmetrics

0 likes · 18 min read

Log Correlation: From Isolated Entries to Linked Traces in High‑QPS Systems

Random Bulletin

Aug 27, 2026 · Operations

Scaling Log Indexing: From Full‑Index to Selective Strategies for Million‑QPS Systems

Full‑text log indexing inflates storage, CPU and mapping costs for 99% of queries that never run, so the article breaks down the five cost walls of full indexing at TB‑scale and presents four selective indexing paths—ES field reduction, Loki tag indexing, ClickHouse column‑store with skip indexes, and hot‑warm‑cold tiering—to pay only for high‑frequency queries.

ClickHouseElasticsearchLoki

0 likes · 19 min read

Scaling Log Indexing: From Full‑Index to Selective Strategies for Million‑QPS Systems