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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

81 recent articles

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.

Automationincident responselarge scale systems

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.

SLAalert tieringalerting

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.

AIOpsalertingdeduplication

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.

Metricsdistributed tracinglog correlation

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

Random Bulletin

Aug 26, 2026 · Operations

Log Standards at Million‑QPS Scale: From Free‑form to Strict Structured Logging

When a production outage forces a midnight investigation across five services, the lack of log standards turns a quick debug into an all‑night forensic hunt; the article explains how structured logs, a unified schema, level semantics, trace_id linking, and field‑level masking enforced by SDK, Lint and CI can eliminate these five walls and make logging scalable, searchable, and compliant.

CI enforcementHigh QPSlog masking

0 likes · 22 min read

Log Standards at Million‑QPS Scale: From Free‑form to Strict Structured Logging

Random Bulletin

Aug 24, 2026 · Operations

Scaling Log Volumes from GB to TB at Ten‑Million QPS: Cost‑Effective Strategies and Architecture

At ten‑million QPS, log data can explode from a few gigabytes to terabytes or even petabytes, triggering storage blow‑up, pipeline saturation, slow queries, runaway costs, and poor signal‑to‑noise, and the article breaks down ingest, index, and store costs while presenting edge sampling, label‑based indexing, tiered storage, and log‑to‑metric rollup as mitigation tactics.

ElasticsearchHigh QPSLoki

0 likes · 19 min read

Scaling Log Volumes from GB to TB at Ten‑Million QPS: Cost‑Effective Strategies and Architecture

Random Bulletin

Aug 22, 2026 · Operations

From Manual Trace Queries to Intelligent Link Analysis at Million‑QPS Scale

The article walks through how link tracing evolves from manually searching individual traces to an automated, intelligent system that aggregates massive spans, derives RED metrics and service maps, performs critical‑path and differential analysis, auto‑detects anomalies, and ties together traces, metrics, and logs for rapid root‑cause identification.

RED metricscritical pathdifferential analysis

0 likes · 19 min read

From Manual Trace Queries to Intelligent Link Analysis at Million‑QPS Scale

Random Bulletin

Aug 21, 2026 · Operations

Scaling Link Tracing Storage: From Centralized Elasticsearch to Tiered Architecture

The article analyzes why storing massive tracing spans in a single Elasticsearch cluster fails at high QPS, outlines the four key challenges of trace data, and presents a three‑step engineering solution—sampling, hot‑warm‑cold tiered storage, and separating indexes from span payloads—while comparing major back‑ends such as Elasticsearch, Cassandra, ClickHouse, and Tempo.

ClickHouseElasticsearchTempo

0 likes · 19 min read

Scaling Link Tracing Storage: From Centralized Elasticsearch to Tiered Architecture