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observability

1324 articles · Page 2 of 14
Smart Era Software Development
Smart Era Software Development
Aug 12, 2026 · Artificial Intelligence

Why Only 30% of an AI Agent Is Deployed – The Critical 70% That Determines Success

The article dissects six engineering gaps that separate demo‑level AI agents from production, then details serverless elasticity, memory recall, intelligent sandboxing, million‑scale messaging, multi‑agent governance, observability, and a data‑flywheel loop, concluding that post‑launch evolution, not initial rollout, decides real‑world success.

AI AgentAgentOpsMulti-agent
0 likes · 23 min read
Why Only 30% of an AI Agent Is Deployed – The Critical 70% That Determines Success
samdeepthink
samdeepthink
Aug 12, 2026 · Operations

Why Observability Is More Than Monitoring: Finding the Root Cause Quickly

The article explains that observability goes beyond simple monitoring by combining metrics, logs, and traces to pinpoint where and why a system issue occurs, especially in microservice and cloud‑native environments, and stresses the importance of correlating data rather than merely collecting more.

AIOpsCloud NativeLogs
0 likes · 3 min read
Why Observability Is More Than Monitoring: Finding the Root Cause Quickly
Ray's Galactic Tech
Ray's Galactic Tech
Aug 11, 2026 · Cloud Native

Microservice Governance: Gateway, Config Center & Tracing to Avoid Pitfalls

Splitting a monolithic order system into separate services introduces challenges such as scattered routing, uncontrolled configuration changes, and fragmented logs, which can be mitigated by implementing a unified API Gateway, a centralized Nacos configuration center, and comprehensive SkyWalking tracing to ensure observability, fault isolation, and safe incremental releases.

API GatewayMicroservicesNacos
0 likes · 50 min read
Microservice Governance: Gateway, Config Center & Tracing to Avoid Pitfalls
CodeSmart Hoops
CodeSmart Hoops
Aug 11, 2026 · Operations

Scaling ELK from 1 GB to 1 TB Daily Logs: Full‑Stack Observability Guide

This comprehensive ELK tutorial walks through the journey of a company whose log volume grew from 1 GB to 1 TB per day, detailing the root causes of cluster failures and providing step‑by‑step guidance on index design, ILM policies, shard sizing, ingest pipelines, query optimization, high‑availability architecture, capacity planning, and security best practices.

ELKElasticsearchILM
0 likes · 35 min read
Scaling ELK from 1 GB to 1 TB Daily Logs: Full‑Stack Observability Guide
Alibaba Cloud Native
Alibaba Cloud Native
Aug 9, 2026 · Mobile Development

Reconstructing an AI App’s Waiting Experience with Flutter RUM Monitoring

This article explains how to use Alibaba Cloud's Flutter RUM SDK to correlate user actions, network requests, long‑tasks and errors, reconstructing the full “spinning page” scenario in AI applications, and shows how STAROps can pinpoint interface failures, client‑side blocks, and rendering bottlenecks with concrete integration steps and code examples.

FlutterPerformanceSTAROps
0 likes · 20 min read
Reconstructing an AI App’s Waiting Experience with Flutter RUM Monitoring
Frontline Investigation
Frontline Investigation
Aug 8, 2026 · Artificial Intelligence

Silent LLM Upgrades: When 'Smarter' Models Break Production Workflows

Frequent, unannounced LLM upgrades in industry applications can silently alter decision boundaries, tool usage, and confirmation logic, breaking established processes. The article proposes a four-dimension observation framework and argues for reversible, observable iterations with versioned knowledge, rules, and orchestration to maintain trust and compliance.

AI complianceAI governanceLLM upgrades
0 likes · 12 min read
Silent LLM Upgrades: When 'Smarter' Models Break Production Workflows
webdream
webdream
Aug 8, 2026 · Artificial Intelligence

Engineering a Multi‑Agent System: Architecture, Stability, and Observability Lessons

This article shares practical engineering insights from building a multi‑agent LLM system, covering why multiple agents are needed, the 3‑agent + 1 skill architecture, LangGraph orchestration, tool integration via MCP, stability mechanisms, layered memory, traceability, streaming UI, and common pitfalls.

LLMLangGraphMCP
0 likes · 12 min read
Engineering a Multi‑Agent System: Architecture, Stability, and Observability Lessons
Alibaba Cloud Native
Alibaba Cloud Native
Aug 8, 2026 · Backend Development

Designing AI‑Friendly Backend Architecture for 24/7 Unattended Development

The article outlines a comprehensive roadmap for transforming traditional backend systems into AI‑friendly architectures, introducing concepts such as Architecture Maps, Service Cards, SKILL packages, multi‑layered testing, permission tiers, and a Harness framework to enable reliable, 24/7 unattended AI‑driven development and operations.

AIArchitectureBackend Development
0 likes · 39 min read
Designing AI‑Friendly Backend Architecture for 24/7 Unattended Development
Ray's Galactic Tech
Ray's Galactic Tech
Aug 7, 2026 · Operations

Scaling Nginx to Handle 500M Daily Requests: From Reverse Proxy to Traffic Governance Hub

This article walks through an enterprise‑grade Nginx upgrade for a payment platform handling ~500 million daily requests, detailing why simple reverse‑proxying fails, how Nginx can become a traffic‑governance edge with rate limiting, edge caching, gray releases, high‑availability, and observability, and provides production‑ready configurations and step‑by‑step analysis.

Edge CachingGray ReleaseNginx
0 likes · 42 min read
Scaling Nginx to Handle 500M Daily Requests: From Reverse Proxy to Traffic Governance Hub
Alibaba Cloud Native
Alibaba Cloud Native
Aug 7, 2026 · Artificial Intelligence

Best Practices for Skill Evaluation and Optimization with Alibaba Cloud AgentLoop

This article presents a complete, data‑driven workflow for creating, instrumenting, offline evaluating, analyzing bad cases, and iteratively optimizing Skills on Alibaba Cloud AgentLoop, enabling developers to quantify quality, track improvements across versions, and reliably deliver high‑quality AI Agent capabilities.

AI AgentAgentLoopBad Case Analysis
0 likes · 43 min read
Best Practices for Skill Evaluation and Optimization with Alibaba Cloud AgentLoop
IT Services Circle
IT Services Circle
Aug 7, 2026 · Operations

Midnight NullPointerException? How Arthas Fixes It in Minutes

When a production Java service throws a NullPointerException at 2 AM, this article shows how the Arthas diagnostic tool can attach to the running JVM, inspect threads, monitor method parameters, and pinpoint the faulty null value without restarting the service, all within a few minutes.

ArthasJVMJava
0 likes · 12 min read
Midnight NullPointerException? How Arthas Fixes It in Minutes
Cloud Native Technology Community
Cloud Native Technology Community
Aug 6, 2026 · Cloud Native

5 Production Challenges for Running AI Workloads on Kubernetes: From GPU Scheduling to Observability

Running AI workloads on Kubernetes introduces five production‑grade challenges—complex GPU and accelerator management, workload‑aware scheduling, inference autoscaling beyond CPU metrics, multi‑layer observability, and Day 2 governance—requiring platform teams to extend their capabilities beyond traditional container operations.

AI workloadsCloud NativeDay 2 operations
0 likes · 10 min read
5 Production Challenges for Running AI Workloads on Kubernetes: From GPU Scheduling to Observability
Data Party THU
Data Party THU
Aug 6, 2026 · Artificial Intelligence

What Is an AI Agent Harness and Why It’s Essential Beyond the Model

The article explains how an AI Agent Harness transforms a powerful language model into a reliable, controllable agent by adding tool access, memory, permissions, guardrails, observability, and recovery mechanisms, and outlines its core components, workflow, and a practical customer‑service example.

AILLMagent harness
0 likes · 12 min read
What Is an AI Agent Harness and Why It’s Essential Beyond the Model
Meituan Technology Team
Meituan Technology Team
Aug 6, 2026 · Artificial Intelligence

A Deep Dive into Agent Evaluation: From Basics to Advanced Practices

This article explains why evaluating AI agents requires more than answer correctness, outlines a four‑layer evaluation framework (result, process, efficiency, risk), compares short‑ and long‑horizon agents, and presents a practical methodology that combines objective and subjective metrics, rubric binary‑ization, case management, and infrastructure requirements for scalable, repeatable agent testing.

AI AgentAgent EvaluationRubric
0 likes · 25 min read
A Deep Dive into Agent Evaluation: From Basics to Advanced Practices
Ray's Galactic Tech
Ray's Galactic Tech
Aug 5, 2026 · Backend Development

Mastering Go Concurrency: From Worker Pools to Production‑Ready Pipelines

This article analyzes why naïve goroutine usage fails in high‑throughput microservices, outlines five common concurrency pitfalls, and walks through a complete production‑grade Go pipeline—covering worker pools, semaphores, fan‑out/fan‑in, back‑pressure, error classification, observability, and step‑by‑step code implementation for an order‑processing service.

GoMicroservicesWorker Pool
0 likes · 29 min read
Mastering Go Concurrency: From Worker Pools to Production‑Ready Pipelines
Alibaba Cloud Native
Alibaba Cloud Native
Aug 4, 2026 · Operations

From Building Wheels to Embedding OpenAPI: Jingchen’s Choice of an Intelligent Ops Foundation

Facing exploding system complexity, unclear global topology, fragmented observability data, and noisy alerts, Jingchen migrated its full‑stack to the cloud and adopted Alibaba Cloud STAROps, a unified CMS 2.0 data base, UModel digital‑twin topology, and OpenAPI‑driven AI diagnostics to turn heavy‑lifting ops work into an automated, business‑focused capability.

Cloud NativeOpenAPISRE
0 likes · 10 min read
From Building Wheels to Embedding OpenAPI: Jingchen’s Choice of an Intelligent Ops Foundation
Alibaba Cloud Native
Alibaba Cloud Native
Aug 3, 2026 · Artificial Intelligence

Building a Financial‑Grade AI Agent Platform with AgentScope: A Practical Whitepaper

FinXScope, a financial‑grade AI‑native agent base built on AgentScope Java, serves as the core engine of the Agent Harness system, offering multi‑agent orchestration, dual‑mode execution, six‑layer architecture, high‑availability, security, observability and low‑code to high‑code pathways, and has already been adopted by dozens of leading financial institutions.

AI AgentsAgentScopeCloud Native
0 likes · 33 min read
Building a Financial‑Grade AI Agent Platform with AgentScope: A Practical Whitepaper
Alibaba Cloud Native
Alibaba Cloud Native
Aug 2, 2026 · Cloud Native

From Visibility to Self‑Healing: ChangjieTong’s Observability and AI‑Powered Ops Journey

ChangjieTong transformed its SaaS‑based, multi‑tenant finance cloud platform by building a five‑layer observability stack on Alibaba Cloud CloudMonitor 2.0, integrating a UModel digital‑twin, and deploying AI‑driven inspection, self‑healing and capacity‑prediction loops, which lifted SLA from 99.9% to 99.995% and cut average fault‑resolution time from over 10 minutes to under 30 seconds.

AIOpsCapacity PredictionCloud Native
0 likes · 15 min read
From Visibility to Self‑Healing: ChangjieTong’s Observability and AI‑Powered Ops Journey
Linyb Geek Road
Linyb Geek Road
Aug 2, 2026 · Operations

How to Build a Systematic Enterprise Monitoring Architecture

This article outlines a comprehensive, step‑by‑step approach for constructing a systematic enterprise monitoring system, covering the four core technical modules (collection, data, operators, alerts), designing a layered metric framework, and establishing a health‑management lifecycle that includes proactive alert prevention, real‑time handling, and post‑incident review.

AlertingCMDBSRE
0 likes · 21 min read
How to Build a Systematic Enterprise Monitoring Architecture
Ray's Galactic Tech
Ray's Galactic Tech
Aug 1, 2026 · Databases

Beyond CRUD: Full‑Scale Production Guide for MySQL 8.4 LTS

This article walks through a complete production‑grade view of MySQL 8.4 LTS, explaining how a chain of traffic spikes, connection‑pool exhaustion, long transactions and replication lag can cause an avalanche, and then detailing the five core modules, seven production mechanisms, architectural evolution steps, incident post‑mortems, and concrete configuration and code examples to build a resilient MySQL service.

InnoDBMySQLPerformance
0 likes · 36 min read
Beyond CRUD: Full‑Scale Production Guide for MySQL 8.4 LTS
DataFunSummit
DataFunSummit
Jul 31, 2026 · Operations

Why Observability Agents Still Can’t Confirm Root Causes Despite Wider Connectors

Grafana Assistant now queries over 30 data sources, expanding incident clues across monitoring, databases, and ticket systems, but cross‑source access only improves correlation; without unified entity mapping, time alignment, and evidence verification, engineers cannot reliably prove a root cause.

Cross-Source QueryGrafana AssistantOperations
0 likes · 12 min read
Why Observability Agents Still Can’t Confirm Root Causes Despite Wider Connectors
Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
Jul 29, 2026 · Operations

Why Alibaba Cloud Became the Only APAC Challenger in Gartner’s 2026 Observability Magic Quadrant

Alibaba Cloud has entered the Challenger quadrant of Gartner’s 2026 Magic Quadrant for Observability Platforms—the sole APAC vendor—by unifying its monitoring, logging, and tracing services into CMS 2.0 and launching the STAROps AI‑driven operations platform that enables 24/7 autonomous root‑cause analysis and closed‑loop remediation.

AI OpsAlibaba CloudCMS 2.0
0 likes · 5 min read
Why Alibaba Cloud Became the Only APAC Challenger in Gartner’s 2026 Observability Magic Quadrant
DeWu Technology
DeWu Technology
Jul 29, 2026 · Backend Development

AI‑Native Development for Transaction Core: A Five‑Gate Framework to Stabilize Legacy Systems

To adapt legacy order‑system development to AI‑generated code, the authors propose a five‑gate, spec‑driven workflow—demand clarification, technical design, TDD implementation, gate‑controlled review, and end‑to‑end telemetry—built on a five‑layer bottom‑up architecture that enforces stability, observability, and human‑validated safeguards.

AI codingBackend DevelopmentSpec-Driven Development
0 likes · 17 min read
AI‑Native Development for Transaction Core: A Five‑Gate Framework to Stabilize Legacy Systems
Full-Stack DevOps & Kubernetes
Full-Stack DevOps & Kubernetes
Jul 29, 2026 · Operations

How AI-Integrated EFK Lets Machines Handle Log Screening and Fault Diagnosis

The article examines how integrating large language models with the EFK logging stack transforms traditional, manual log inspection into an AI-driven process that automatically filters logs, identifies anomalies, performs root‑cause analysis, and generates structured fault reports, dramatically improving operational efficiency and reducing mean‑time‑to‑resolution.

AI OpsAIOpsEFK
0 likes · 10 min read
How AI-Integrated EFK Lets Machines Handle Log Screening and Fault Diagnosis
DataFunSummit
DataFunSummit
Jul 28, 2026 · Artificial Intelligence

Why Enterprises Still Hesitate to Deploy Production‑Ready AI Agents Despite Palantir’s New Capabilities

Palantir’s Agent Stack introduces Orchestrator, observability, and Ontology layers to make AI agents durable, interruptible, and governed, but enterprises remain reluctant because trust, state management, permission control, and continuous evaluation are required before agents can operate on real business processes.

AI AgentsEnterprise AIOrchestrator
0 likes · 14 min read
Why Enterprises Still Hesitate to Deploy Production‑Ready AI Agents Despite Palantir’s New Capabilities
AI Engineer Programming
AI Engineer Programming
Jul 26, 2026 · Artificial Intelligence

Agent Development Lifecycle (ADLC): Vendor‑Neutral Guide to Build, Test, Deploy, Monitor, and Govern AI Agents

This note outlines a vendor‑agnostic Agent Development Lifecycle (ADLC) that extends traditional SDLC with five stages—Build, Test, Deploy, Monitor, and Govern—detailing layer‑wise tooling choices, evaluation strategies, deployment infrastructure, observability practices, and governance concerns for modern AI agents.

AI lifecycleAgentOpsLLM
0 likes · 15 min read
Agent Development Lifecycle (ADLC): Vendor‑Neutral Guide to Build, Test, Deploy, Monitor, and Govern AI Agents
Ray's Galactic Tech
Ray's Galactic Tech
Jul 26, 2026 · Artificial Intelligence

Add Reusable Templates to an AI Assistant with AgentScope 2.0.3

AgentScope 2.0.3 introduces a Skills layer that lets teams attach reusable, versioned work templates to AI assistants without writing code, separating business logic from runtime control, enabling fine‑grained governance, high‑concurrency isolation, task‑based execution, and robust observability for production‑grade deployments.

AI AgentsSkillsTask Queue
0 likes · 36 min read
Add Reusable Templates to an AI Assistant with AgentScope 2.0.3
Alibaba Cloud Native
Alibaba Cloud Native
Jul 26, 2026 · Industry Insights

Alibaba Cloud Becomes Asia‑Pacific’s Only Challenger in Gartner’s Observability Magic Quadrant

Gartner’s 2026 Magic Quadrant for Observability Platforms places Alibaba Cloud as the sole APAC challenger, highlighting its CMS 2.0 unified data foundation and STAROps global intelligent‑operations platform that enable AI Agents to autonomously perform 24/7 root‑cause analysis through closed‑loop remediation, showcasing strong intelligent‑ops competitiveness worldwide.

AI AgentAlibaba CloudCMS 2.0
0 likes · 4 min read
Alibaba Cloud Becomes Asia‑Pacific’s Only Challenger in Gartner’s Observability Magic Quadrant
Linyb Geek Road
Linyb Geek Road
Jul 26, 2026 · Operations

Postmortem: How an Alert Flood Masked the Real Problem

A late‑night incident flooded the on‑call channel with dozens of red alerts, hiding the true root cause—a core service latency spike—until the team re‑ordered information, prioritized early signals, and applied a simple three‑tier alert classification to restore clarity and speed up resolution.

AIOpsOperationsalert management
0 likes · 11 min read
Postmortem: How an Alert Flood Masked the Real Problem
DeepHub IMBA
DeepHub IMBA
Jul 24, 2026 · Operations

Avoid Repeating Microservice Governance Pitfalls in AI Agent Management

The article analyzes how AI agents create hidden, "shadow" integrations that are harder to detect than traditional services, outlines five critical governance questions, and proposes a set of operational capabilities and principles—identity, observability, governance, lifecycle, and reuse—to responsibly scale AgentOps.

AI AgentOperationsShadow Integration
0 likes · 10 min read
Avoid Repeating Microservice Governance Pitfalls in AI Agent Management
Ray's Galactic Tech
Ray's Galactic Tech
Jul 23, 2026 · Artificial Intelligence

Stop Embedding Business Logic in Prompts: An Enterprise Guide to Spring AI Alibaba Skills

The article explains why many AI projects fail not because of model performance but due to architectural boundaries, illustrates a real‑world incident caused by an ever‑growing "super Prompt", and shows how Spring AI Alibaba Skills can split responsibilities, enforce governance, and make AI services production‑ready.

Alibaba SkillsEnterprise AIMicroservices
0 likes · 26 min read
Stop Embedding Business Logic in Prompts: An Enterprise Guide to Spring AI Alibaba Skills
YiSu Grain
YiSu Grain
Jul 22, 2026 · Cloud Native

Day 31: Distinguishing Elasticity, Resilience, and Observability in Cloud‑Native Architecture

Moving an application to cloud VMs and Docker does not automatically grant cloud‑native capabilities; this article explains the seven cloud‑native principles—service‑orientation, elasticity, observability, resilience, full automation, zero‑trust, and continuous evolution—using concrete e‑commerce scenarios, tables, and step‑by‑step guidance to show how each principle solves specific problems and how they interrelate.

Cloud NativeMicroservicesResilience
0 likes · 32 min read
Day 31: Distinguishing Elasticity, Resilience, and Observability in Cloud‑Native Architecture
Cloud Architecture
Cloud Architecture
Jul 21, 2026 · Cloud Native

Kubernetes Troubleshooting in Practice: 20 Survival Rules from Real Incidents

This article presents a hands‑on guide to diagnosing Kubernetes production failures, distilling a real e‑commerce outage into 20 actionable rules that cover nodes, control plane, networking, scheduling, storage and observability, and provides a step‑by‑step diagnostic workflow with concrete commands and examples.

ConfigMapHPAKubernetes
0 likes · 29 min read
Kubernetes Troubleshooting in Practice: 20 Survival Rules from Real Incidents
DataFunSummit
DataFunSummit
Jul 21, 2026 · Industry Insights

Why Enterprises Still Hesitate to Deploy Production‑Ready AI Agents Despite Palantir’s New Stack

The article analyzes Palantir’s Agent Stack—Orchestrator, observability, optimization, and Ontology—explaining how moving AI agents from chat interfaces to long‑running production tasks raises challenges of state management, fault handling, permission control, and trust, shifting the focus from model capability to enterprise‑grade infrastructure.

AI AgentsEnterprise AIOrchestrator
0 likes · 14 min read
Why Enterprises Still Hesitate to Deploy Production‑Ready AI Agents Despite Palantir’s New Stack
DataFunTalk
DataFunTalk
Jul 21, 2026 · Industry Insights

Why Stronger AI Agents Make Enterprises More Reluctant: Palantir’s New Trust Infrastructure

The article analyzes Palantir's Agent Stack, showing that while building capable AI agents is now easy, enterprises hesitate to deploy them at scale because trust, state persistence, observability, and governance must be engineered through durable orchestration, ontology mapping, and continuous optimization.

AI AgentsEnterprise AIOrchestrator
0 likes · 13 min read
Why Stronger AI Agents Make Enterprises More Reluctant: Palantir’s New Trust Infrastructure
TechVision Expert Circle
TechVision Expert Circle
Jul 21, 2026 · Cloud Native

How to Build an Elastic Auto‑Scaling Cloud‑Native Application

After a 15‑fold traffic surge forced manual scaling of an e‑commerce platform, the team rebuilt the system with true elastic scaling—horizontal, vertical, and architectural—using Kubernetes, Envoy, KEDA, predictive autoscaling, and a comprehensive observability stack, achieving fully automated scaling from 12 to 80 pods in under 90 seconds and cutting peak resource costs by 60%.

Cloud NativeElastic ScalingKEDA
0 likes · 13 min read
How to Build an Elastic Auto‑Scaling Cloud‑Native Application
Ray's Galactic Tech
Ray's Galactic Tech
Jul 20, 2026 · Artificial Intelligence

From Demo to Production: A Complete AI Agent Engineering Roadmap with Detailed Resources

This article analyzes why AI Agent demos often fail in production, outlines the essential runtime components such as state persistence, tool isolation, async scheduling, observability, and cost control, and provides a step‑by‑step engineering roadmap, architectural diagrams, code examples, and a practical checklist for building reliable, production‑grade AI Agents.

AI AgentBackend EngineeringLLM
0 likes · 28 min read
From Demo to Production: A Complete AI Agent Engineering Roadmap with Detailed Resources
Golang Shines
Golang Shines
Jul 20, 2026 · Cloud Native

7 Golden Rules for Building High‑Availability Cloud‑Native Go Services (Production‑Proven)

This article presents a step‑by‑step guide to building highly available cloud‑native Go systems, covering graceful error handling, structured logging, minimal dependencies, concurrency control, health checks, Raft‑based replication, timeout/retry strategies, circuit breaking, rate limiting, observability with Zap, Loki, Prometheus, OpenTelemetry, and future architectural directions.

Cloud NativeGoMicroservices
0 likes · 18 min read
7 Golden Rules for Building High‑Availability Cloud‑Native Go Services (Production‑Proven)
Data Party THU
Data Party THU
Jul 20, 2026 · Artificial Intelligence

What I Learned After Six Months Building Production AI Agents: The Five Costly Mistakes

The article analyzes why AI agents that shine in demos often fail in production, identifies five common mistakes—including over‑reliance on prompts, manual evaluation, unchecked cost and latency, fragile tool integrations, and missing safety guards—and introduces a five‑layer Harness Engineering framework with a practical four‑week rollout plan to make agents reliable at scale.

AI AgentCost ManagementHarness Engineering
0 likes · 23 min read
What I Learned After Six Months Building Production AI Agents: The Five Costly Mistakes
Xiaolin Talks Programming
Xiaolin Talks Programming
Jul 20, 2026 · Backend Development

Spring Boot Logging Governance: Structured JSON, Dynamic Levels & TraceId Propagation

This article details a production-grade logging system for Spring Boot microservices covering structured JSON output, MDC-based TraceId propagation across async threads and RPC calls, dynamic log level updates via Actuator or config centers, sensitive data masking, and disk protection strategies with async appenders and containerized log collection.

Dynamic Log LevelLogbackMDC
0 likes · 21 min read
Spring Boot Logging Governance: Structured JSON, Dynamic Levels & TraceId Propagation
Ray's Galactic Tech
Ray's Galactic Tech
Jul 19, 2026 · Artificial Intelligence

Why the Real Production Bottleneck for AI Agents Is the Harness, Not the Model

The article explains that when AI agents move from prototype to production, failures usually stem from the execution harness—issues like multi‑step orchestration, tool integration, context overflow, and lack of observability—rather than the underlying language model itself, and it provides a concrete seven‑layer framework (ETCLOVG) to diagnose and engineer a reliable harness.

AI AgentsETCLOVGHarness Engineering
0 likes · 32 min read
Why the Real Production Bottleneck for AI Agents Is the Harness, Not the Model
KooFE Frontend Team
KooFE Frontend Team
Jul 18, 2026 · Artificial Intelligence

Understanding the Seven‑Layer ETCLOVG Architecture for Production‑Grade AI Agents

The article introduces the ETCLOVG framework—a standardized seven‑layer architecture that separates structural core functions from control‑plane capabilities, detailing each layer's purpose and how together they define the essential engineering abilities required for robust, production‑level AI agent systems.

AI AgentsETCLOVGExecution Environment
0 likes · 4 min read
Understanding the Seven‑Layer ETCLOVG Architecture for Production‑Grade AI Agents
Big Data and Microservices
Big Data and Microservices
Jul 18, 2026 · Artificial Intelligence

Ensuring Reliable AI Agents: Reflection, Error‑Correction, and Guardrail Design

The article examines how to keep AI agents reliable by introducing reflection mechanisms that let agents learn from failures, multi‑layer guardrails that prevent runaway loops, and a governance framework with permission controls, budget limits, observability, and human‑in‑the‑loop checks, illustrated with concrete benchmarks and case studies.

AI AgentsLLM SafetyReflection
0 likes · 16 min read
Ensuring Reliable AI Agents: Reflection, Error‑Correction, and Guardrail Design
Golang Shines
Golang Shines
Jul 17, 2026 · Cloud Native

Building a Scalable Go Service Mesh from Scratch: Core Cloud‑Native Practices

This article walks through why Go is ideal for cloud‑native development and demonstrates step‑by‑step how to build a scalable service mesh, covering static compilation, HTTP services, Go modules, Gin/Gorilla APIs, configuration, logging, health checks, service registration, load balancing, sidecar proxies, traffic interception, circuit breaking, rate limiting, retries, and distributed tracing with OpenTelemetry.

Cloud NativeGoKubernetes
0 likes · 16 min read
Building a Scalable Go Service Mesh from Scratch: Core Cloud‑Native Practices
Ctrip Technology
Ctrip Technology
Jul 17, 2026 · Artificial Intelligence

From Demo to Production: How Our Java Agent Harness Fixes Common Pitfalls

Java agents often work in demos but crash in production due to stack mismatches, governance gaps, and runtime issues such as memory drift, large tool outputs, and lack of observability; the Spring‑Ai‑Trip harness adds progressive compression, spill protection, skill injection, hot‑plug tools, and concurrent execution to bridge the gap.

AI AgentJavaMemory Compression
0 likes · 31 min read
From Demo to Production: How Our Java Agent Harness Fixes Common Pitfalls
Linyb Geek Road
Linyb Geek Road
Jul 15, 2026 · Artificial Intelligence

From ReAct to Harness: Building Production‑Ready Agent Architectures

The article outlines the five‑stage evolution of AI agents—from the basic ReAct loop to self‑driving, self‑optimizing systems—and presents six engineering pillars (verification, stop, state, recovery, isolation, observability) that together form a Harness framework for deploying reliable, production‑grade agents.

AI AgentsAgent Architectureobservability
0 likes · 8 min read
From ReAct to Harness: Building Production‑Ready Agent Architectures
Cloud Architecture
Cloud Architecture
Jul 14, 2026 · Operations

From Avalanche to Self‑Healing: Why Nginx 502 Spikes During High‑Traffic Sales and How to Fix It

During large‑scale promotions a sudden flood of Nginx 502 errors signals upstream interaction failures across proxy, kernel, application and orchestration layers, and the article explains the exact conditions, root causes, traffic amplification, and a systematic self‑healing approach to diagnose and eliminate them.

502KubernetesNginx
0 likes · 27 min read
From Avalanche to Self‑Healing: Why Nginx 502 Spikes During High‑Traffic Sales and How to Fix It
Ray's Galactic Tech
Ray's Galactic Tech
Jul 14, 2026 · Backend Development

How We Built a RAG‑Powered Knowledge Base That Actually Understands Source Code

The article explains why traditional FAQs fail for complex production issues, then details the design of a retrieval‑augmented generation knowledge engine that ingests source code, configuration, design docs, and incident reports, offering version‑consistent, permission‑aware answers with evidence‑backed citations.

Access ControlKnowledge EngineKubernetes Deployment
0 likes · 27 min read
How We Built a RAG‑Powered Knowledge Base That Actually Understands Source Code
Ray's Galactic Tech
Ray's Galactic Tech
Jul 13, 2026 · Artificial Intelligence

When AI Agents Meet Cloud‑Native: Practical Multi‑Agent Orchestration for High‑Concurrency Scenarios

The article explains why naïve multi‑agent demos fail in production, defines the core concepts of Task, Step, Agent Role and Event, proposes a four‑plane cloud‑native architecture, shows concrete Go and Python code, and provides detailed guidance on state machines, reliability, observability, security and budget governance for building scalable, production‑grade AI agent systems.

AI AgentsCloud NativeKubernetes
0 likes · 36 min read
When AI Agents Meet Cloud‑Native: Practical Multi‑Agent Orchestration for High‑Concurrency Scenarios
Alibaba Cloud Observability
Alibaba Cloud Observability
Jul 13, 2026 · Frontend Development

Seeing Every User Action: How Session Replay and Heatmaps Enable Data‑Driven Front‑End Optimization

The article explains how Alibaba Cloud's CMS 2.0 uses Session Replay to record DOM changes and user interactions, and three types of heatmaps—click, area, and scroll—to provide low‑overhead, privacy‑controlled insights that help developers reproduce bugs, analyze conversion funnels, and improve overall front‑end user experience.

frontend monitoringheatmapobservability
0 likes · 15 min read
Seeing Every User Action: How Session Replay and Heatmaps Enable Data‑Driven Front‑End Optimization
AI Large Model Application Practice
AI Large Model Application Practice
Jul 13, 2026 · Artificial Intelligence

20 Essential Agent Engineering Concepts for 2026: Making Agents Practical, Scalable, and Deployable

The article breaks down ten core engineering pillars for production‑grade AI agents—including tool calling with MCP, reusable skills, persistent memory, multi‑agent collaboration, workflow orchestration, hooks, observability, sandboxing, prompt‑injection defense, and the role of forward‑deployed engineers—to help turn demo agents into reliable, enterprise‑ready systems.

Agent EngineeringMulti-agentPrompt Injection Defense
0 likes · 21 min read
20 Essential Agent Engineering Concepts for 2026: Making Agents Practical, Scalable, and Deployable
AI Engineer Programming
AI Engineer Programming
Jul 12, 2026 · Artificial Intelligence

Building a Full-Agent Observability and Quality Evaluation System: From Data Collection to the Data Flywheel

This article presents a comprehensive, engineering‑focused practice for observing and evaluating large‑model agents, covering new data‑collection challenges, a three‑layer observability architecture, offline and online testing pipelines, quality‑gate mechanisms, and a self‑reinforcing data flywheel that continuously improves performance, cost, and safety.

AIOpsAgentLLM
0 likes · 18 min read
Building a Full-Agent Observability and Quality Evaluation System: From Data Collection to the Data Flywheel
AI Engineer Programming
AI Engineer Programming
Jul 11, 2026 · Operations

Building an Observability Platform for LLM Agents with OpenTelemetry

This article explains why LLM agents need a dedicated observability platform, introduces OpenTelemetry’s core concepts and architecture, shows how to manually instrument Python code, enable automatic instrumentation, configure the Collector, handle common distributed‑system pitfalls, and extend OTel with agent‑specific semantics and evaluation loops.

CollectorLLM AgentOpenTelemetry
0 likes · 20 min read
Building an Observability Platform for LLM Agents with OpenTelemetry
TechVision Expert Circle
TechVision Expert Circle
Jul 11, 2026 · Artificial Intelligence

2026 H2 IT Landscape Shifts: From Model Competition to the Three Battlefields of Agents, Data, and Governance

The article argues that in the second half of 2026 the AI race will move from chasing ever larger models to mastering three pragmatic fronts—AI Agent engineering, data‑infrastructure redesign, and robust AI governance—detailing the technical shifts, cost pressures, and compliance demands that will decide which teams succeed.

AI AgentsAI governanceData Infrastructure
0 likes · 13 min read
2026 H2 IT Landscape Shifts: From Model Competition to the Three Battlefields of Agents, Data, and Governance
Java Companion
Java Companion
Jul 9, 2026 · Operations

Tired of Manually Sifting Through Monitoring? Meet Ongrid, the Ops‑World’s OpenClaw

Ongrid is an open‑source AI Ops agent that integrates with Slack, DingTalk and other chat platforms, automatically detects alerts, performs root‑cause analysis using a built‑in Prometheus/Loki/Tempo/Grafana stack, and can even remediate issues—all without opening inbound ports, offering browser‑based shells and one‑click deployment via install.sh.

AI OpsChatOpsOngrid
0 likes · 9 min read
Tired of Manually Sifting Through Monitoring? Meet Ongrid, the Ops‑World’s OpenClaw
Big Data and Microservices
Big Data and Microservices
Jul 9, 2026 · Artificial Intelligence

How to Evaluate and Observe AI Agents: Optimizing Your Digital Employee

The article explains why traditional benchmark scores are insufficient for production AI agents and proposes a four‑dimensional evaluation framework—task success, step efficiency, cost, and safety—combined with an observability stack of metrics, structured logs, and full‑trace decision snapshots to continuously measure, debug, and improve digital employees.

AI AgentsCost ManagementLLM
0 likes · 17 min read
How to Evaluate and Observe AI Agents: Optimizing Your Digital Employee
Java Captain
Java Captain
Jul 7, 2026 · Artificial Intelligence

Alibaba’s Open‑Source Spring AI Alibaba Admin Solves Prompt Debugging, Quality, and Ops Pain Points

Spring AI Alibaba Admin, Alibaba’s open‑source extension of Spring AI, addresses three major enterprise hurdles—inefficient prompt debugging, unreliable AI quality, and opaque production operations—by providing versioned prompt management, dataset lifecycle control, flexible evaluator configuration, automated experiment execution, and end‑to‑end observability.

AI AgentAlibabaOpenTelemetry
0 likes · 8 min read
Alibaba’s Open‑Source Spring AI Alibaba Admin Solves Prompt Debugging, Quality, and Ops Pain Points
Cloud Architecture
Cloud Architecture
Jul 6, 2026 · Backend Development

Spring Boot Template Engine Mix: Designing a Multi‑Engine Coexistence Architecture for Production

The article explains why running multiple template engines in a Spring Boot application becomes an operational challenge, outlines a four‑layer architecture and routing strategies, provides concrete code for a custom ViewResolver, configuration, observability, deployment, testing and migration steps, and shows how to govern the process safely in production.

KubernetesSpring BootThymeleaf
0 likes · 39 min read
Spring Boot Template Engine Mix: Designing a Multi‑Engine Coexistence Architecture for Production
Alibaba Cloud Observability
Alibaba Cloud Observability
Jul 6, 2026 · Cloud Native

Why Is My AI Agent Slow? Using a Node.js Probe to Unify Model, Tool, and Service Traces

The article analyzes how modern Node.js services act as a convergence layer for HTTP, databases, caches, RPCs, and AI calls, making performance problems cross‑layer, and introduces Alibaba Cloud ARMS Node.js probe that, with a single integration, automatically gathers APM, AI observability, runtime health, and dynamic configuration to provide full‑stack tracing and simplify troubleshooting.

APMOpenTelemetryPerformance Monitoring
0 likes · 17 min read
Why Is My AI Agent Slow? Using a Node.js Probe to Unify Model, Tool, and Service Traces
Xike
Xike
Jul 6, 2026 · Backend Development

Seeing the Full Request Journey: Completing Spring Boot Trace Integration

This guide shows how to extend an existing Prometheus‑Grafana‑Loki stack with SkyWalking to capture full request traces in Spring Boot, explaining trace fundamentals, automatic instrumentation, manual spans, log‑trace correlation, cross‑service topology, and production considerations.

LogsSkyWalkingSpring Boot
0 likes · 17 min read
Seeing the Full Request Journey: Completing Spring Boot Trace Integration
AI Engineer Programming
AI Engineer Programming
Jul 5, 2026 · Artificial Intelligence

Will Stronger Models Render Harnesses Obsolete? (Part 2)

The article analyzes how advancing model capabilities are displacing traditional Harness components such as Context Reset and Sprint Contract, outlines which Harness functions remain essential, and offers engineering practices for co‑evolving Harnesses with ever‑more capable AI agents.

AI EngineeringAgent FrameworkHarness
0 likes · 14 min read
Will Stronger Models Render Harnesses Obsolete? (Part 2)
TechVision Expert Circle
TechVision Expert Circle
Jul 5, 2026 · Artificial Intelligence

Why 77% of Enterprises Deploy AI Agents—and CIOs Fear Loss of Control

A Gartner survey shows 77% of companies have rolled out AI agents, shifting CIO anxiety from deployment feasibility to governance challenges such as data exposure, decision accountability, and emergent multi‑agent interactions, prompting a call for robust agent registries, least‑privilege controls, observability, and circuit‑breakers.

AI AgentAgent SprawlCIO
0 likes · 11 min read
Why 77% of Enterprises Deploy AI Agents—and CIOs Fear Loss of Control
java1234
java1234
Jul 5, 2026 · Artificial Intelligence

9 Practical Tips for Efficient Spring AI 2.0 Agent Development

The article shares nine hands‑on tips for building Spring AI 2.0 agents—including using ChatClient as the entry point, delegating tool calls to ToolCallingAdvisor, defining tools with @Tool, crafting effective system prompts, leveraging Advisor chains, streaming responses early, managing conversation memory, limiting tool count, and adding observability—each illustrated with concrete code snippets.

AgentChatClientJava
0 likes · 12 min read
9 Practical Tips for Efficient Spring AI 2.0 Agent Development
Cloud Architecture
Cloud Architecture
Jul 4, 2026 · Backend Development

Production-Ready SMS Verification Login System: Security Countermeasures and Engineering

This article presents a comprehensive guide to building a production-grade SMS verification login system, covering threat modeling, multi-layer rate limiting, state management with Redis, asynchronous message handling, multi‑provider routing, token issuance and operational monitoring to ensure security, cost control, and high availability.

OutboxRedisSMS verification
0 likes · 36 min read
Production-Ready SMS Verification Login System: Security Countermeasures and Engineering
DataFunSummit
DataFunSummit
Jul 3, 2026 · Databases

Agent Native: Ultra‑Fast Analytical Database Paradigm for Agents

The presentation at the Agentic AI Summit details the four core challenges of agent‑driven data analysis and introduces SelectDB’s Agent Native architecture—combining sub‑second query speed, unified multimodal search, semantic understanding, and cloud‑elastic observability, with reported storage savings of up to 88% and 5‑10× text‑search acceleration.

Agentic AICloud ElasticityData Infrastructure
0 likes · 7 min read
Agent Native: Ultra‑Fast Analytical Database Paradigm for Agents
Linyb Geek Road
Linyb Geek Road
Jul 3, 2026 · Artificial Intelligence

Production-Ready AI Agent Harness: Architecture and Design Principles

The article explains why the stability of AI agents depends on the harness rather than the model, outlines a five‑layer production‑grade harness architecture (Environment, Tool, Control, Memory, Evaluation), and presents five engineering principles to build a reliable, observable, and maintainable agent runtime system.

AI AgentHarness EngineeringSystem Design
0 likes · 18 min read
Production-Ready AI Agent Harness: Architecture and Design Principles
TechVision Expert Circle
TechVision Expert Circle
Jul 2, 2026 · Operations

Designing an Automated Operations System for Hybrid Cloud Environments

This article shares a hands‑on experience of building a unified, layered automation platform for hybrid‑cloud operations, covering challenges like network, API, and state inconsistencies, and detailing architecture, CMDB, IaC, observability, workflow orchestration, AIOps, security, cost governance, and practical rollout lessons.

AIOpsCost ManagementIaC
0 likes · 13 min read
Designing an Automated Operations System for Hybrid Cloud Environments
Thought Artisan
Thought Artisan
Jul 1, 2026 · Mobile Development

Android 17 Binder Observability: Lock-Free Observer V2 & Kernel Netlink Events

Android 17 enhances Binder observability with a lock-free SPSC queue, boot-stable sharding, exponential latency histograms, and CPU sampling in the user-space Observer V2, while introducing a kernel Netlink channel for asynchronous, zero-overhead IPC error events like frozen transactions and spam detection.

Android 17BinderIPC
0 likes · 8 min read
Android 17 Binder Observability: Lock-Free Observer V2 & Kernel Netlink Events
Java Tech Enthusiast
Java Tech Enthusiast
Jun 30, 2026 · Backend Development

Spring Boot 4.1.0 Released: Official gRPC Support Boosts Java Microservices

Spring Boot 4.1.0 introduces official gRPC support, unified Jackson configuration, HTTP client SSRF protection, enhanced observability with OpenTelemetry, and flexible Log4j file‑rotation strategies, while the roadmap confirms a one‑year lifecycle for each version and signals the shift to the 4.x era for Java microservices.

JacksonJavaSSRF
0 likes · 8 min read
Spring Boot 4.1.0 Released: Official gRPC Support Boosts Java Microservices
Architect
Architect
Jun 27, 2026 · Backend Development

From Task Cycles to a Maintainable, Observable, Replayable Agent Loop

The article explains how Loop Engineering turns multi‑round Agent execution into a maintainable, observable, and replayable closed‑loop by defining six core components, reusing traditional development patterns, presenting a CI‑failure triage demo, and highlighting architectural and practical pitfalls.

Agent LoopCI pipelineobservability
0 likes · 19 min read
From Task Cycles to a Maintainable, Observable, Replayable Agent Loop
Cloud Architecture
Cloud Architecture
Jun 27, 2026 · Backend Development

Enterprise Messaging System Deep Dive: Core Engine to High‑Concurrency

This guide explains how enterprise messaging systems reliably propagate state changes across distributed services, covering core concepts, outbox patterns, topic/tag modeling, consumer idempotency, dead‑letter handling, high‑concurrency engineering, monitoring, and Kubernetes deployment to build a production‑grade, observable platform.

KafkaOutboxevent-driven
0 likes · 44 min read
Enterprise Messaging System Deep Dive: Core Engine to High‑Concurrency
DeepNoMind
DeepNoMind
Jun 27, 2026 · Backend Development

Designing a Production‑Grade Distributed Logging and Metrics Platform

This article presents an end‑to‑end design of a production‑grade observability platform that ingests millions of real‑time logs, metrics, and events, detailing functional and non‑functional requirements, capacity planning, component choices such as Kafka, Flink, Elasticsearch, object‑storage data lakes, and the trade‑offs involved.

Data LakeElasticsearchFlink
0 likes · 21 min read
Designing a Production‑Grade Distributed Logging and Metrics Platform
TechVision Expert Circle
TechVision Expert Circle
Jun 26, 2026 · Operations

How CTOs Can Build Systems That Make Their Own Decisions

The article explains why, in 2026, CTOs must equip production systems with self‑decision capabilities, outlines an OODA‑loop‑based architecture with perception, decision (three‑brain LLM agent), execution, and feedback layers, and addresses practical challenges such as latency, hallucinations, cost, and team adoption.

LLMOODAOperations
0 likes · 14 min read
How CTOs Can Build Systems That Make Their Own Decisions
DataFunTalk
DataFunTalk
Jun 26, 2026 · Databases

How SelectDB Tackles Speed, Unification, Agent‑Native and Cloud Elasticity for the Agent Era

The 2026 SelectDB AI product launch outlines how the database addresses four Agent‑era challenges—sub‑second speed, unified multi‑modal data, Agent‑Native interfaces, and cloud elasticity—through benchmark‑backed performance, a new MCP server, Litefuse observability, and a serverless architecture.

AI Data InfrastructureAgent-NativeMulti-modal
0 likes · 10 min read
How SelectDB Tackles Speed, Unification, Agent‑Native and Cloud Elasticity for the Agent Era
AI Architecture Hub
AI Architecture Hub
Jun 26, 2026 · Artificial Intelligence

30 Core AI Agent Engineering Concepts Every Developer Must Know

This article breaks down the essential 30 concepts behind AI agents—covering their loop‑based execution, state management, common patterns, configuration files, prompt caching, context corruption, capability protocols, sandbox security, permission controls, observability, and practical entry‑level advice—so developers can understand any new framework without chasing hype.

AI AgentsAgent ArchitectureMCP
0 likes · 21 min read
30 Core AI Agent Engineering Concepts Every Developer Must Know
Cloud Architecture
Cloud Architecture
Jun 25, 2026 · Backend Development

SpringBoot + WeChat Pay V3: Architecture for Million-Concurrent Payments

The article explains how to build a production‑grade, million‑concurrent payment pipeline with SpringBoot and WeChat Pay V3, covering the new security model, state‑machine design, idempotent handling, decoupled architecture, compensation mechanisms, and operational best practices such as connection‑pool tuning, observability, and fault‑tolerant deployment.

SpringBootWeChat Paycompensation
0 likes · 56 min read
SpringBoot + WeChat Pay V3: Architecture for Million-Concurrent Payments
Programmer DD
Programmer DD
Jun 25, 2026 · Cloud Native

Why Agents Need a Full Engineering Platform Beyond the Demo

The article analyses how EdgeOne Makers provides a comprehensive engineering foundation—including managed runtime, sandbox tools, conversation storage, observability, model integration, authentication, and Git‑based deployment—to turn AI Agent demos into production‑ready services, and compares it with alternative approaches.

Agent RuntimeEdgeOne MakersGit deployment
0 likes · 16 min read
Why Agents Need a Full Engineering Platform Beyond the Demo
Cloud Architecture
Cloud Architecture
Jun 24, 2026 · Backend Development

Spring Boot Alipay Integration: A Production-Ready Solution for High Concurrency and Financial Consistency

This article explains how to build a production‑grade Alipay payment subsystem with Spring Boot that goes beyond simple API calls, covering asynchronous flow, idempotent notification handling, state‑machine design, outbox event delivery, high‑concurrency safeguards, and end‑to‑end reconciliation.

AlipayBackend DevelopmentOutbox
0 likes · 32 min read
Spring Boot Alipay Integration: A Production-Ready Solution for High Concurrency and Financial Consistency
Coder Trainee
Coder Trainee
Jun 23, 2026 · Backend Development

Production-Grade Deployment and Best Practices for Java AI Applications

This article examines the three core challenges—stability, cost, and observability—of running Java AI services in production and presents concrete solutions such as timeout and retry policies, circuit‑breaker fallback, token‑monitoring, caching, tracing, custom metrics, and Docker‑based containerization.

AIDockerJava
0 likes · 6 min read
Production-Grade Deployment and Best Practices for Java AI Applications
DataFunSummit
DataFunSummit
Jun 23, 2026 · Artificial Intelligence

How to Engineer Trustworthy AI Agents: Execution Control, Safety Boundaries, and Multi‑Agent Collaboration

In a 90‑minute live technical dialogue, experts from OPPO and Tencent Cloud dissect ten core challenges of moving AI agents from demo to production—covering sandbox vs. permission boundaries, checkpoint design, rollback strategies, tool‑call safety, human‑in‑the‑loop control, multi‑agent coordination, and observability—offering concrete engineering guidelines for building reliable, auditable agents.

AI Agent EngineeringCheckpoint DesignRollback Strategies
0 likes · 18 min read
How to Engineer Trustworthy AI Agents: Execution Control, Safety Boundaries, and Multi‑Agent Collaboration
Alibaba Cloud Observability
Alibaba Cloud Observability
Jun 22, 2026 · Operations

How One‑Line Code Turns Electron Apps into Fully Observable Desktop Agents

The article analyzes the monitoring blind spots of Electron's dual‑process architecture—native crashes, fragmented data, unreliable reporting, and IPC opacity—and presents @arms/rum-electron, a zero‑config SDK that injects full‑stack observability, WASM‑based crash parsing, tRPC tracing, memory‑leak detection, and multi‑protocol distributed tracing, while comparing it to Sentry and generic RUM solutions.

Crash MonitoringElectronMemory Leak
0 likes · 15 min read
How One‑Line Code Turns Electron Apps into Fully Observable Desktop Agents
Alibaba Cloud Observability
Alibaba Cloud Observability
Jun 22, 2026 · Cloud Native

Zero‑Code Full‑Stack Observability with OpenTelemetry eBPF: CloudMonitor 2.0’s In‑Kernel “Lens”

OpenTelemetry eBPF Instrumentation (OBI) injects a kernel‑level, zero‑code probe that automatically captures OpenTelemetry‑compatible traces, metrics, and logs for over 15 protocols—including HTTP, gRPC, MySQL, Redis, Kafka, and CUDA—while handling cross‑language context propagation, GPU tracing, and seamless integration with CloudMonitor 2.0.

Cloud NativeOpenTelemetryZero-Code Monitoring
0 likes · 19 min read
Zero‑Code Full‑Stack Observability with OpenTelemetry eBPF: CloudMonitor 2.0’s In‑Kernel “Lens”
Smart Era Software Development
Smart Era Software Development
Jun 22, 2026 · Artificial Intelligence

Constrained Autonomy: An Agentic Architecture Scaling to Hundreds of Thousands of Creators

The talk details a multi‑agent system for AI video creation that tackles orchestration uncertainty, fault irrecoverability, and quality attribution by applying a "constrained autonomy" principle, implementing a six‑layer architecture, high‑concurrency optimizations, comprehensive observability, and layered quality gates to support hundreds of thousands of simultaneous creators.

AI video generationAgentic ArchitectureQuality Gatekeeping
0 likes · 12 min read
Constrained Autonomy: An Agentic Architecture Scaling to Hundreds of Thousands of Creators
Cloud Architecture
Cloud Architecture
Jun 21, 2026 · Backend Development

How to Build a Production‑Ready AI Service with Spring 7.0 and Spring AI for High‑Concurrency Microservices

This article explains how to integrate large language models into enterprise Java microservices using Spring 7.0 and Spring AI, covering architectural layers, design principles, code structure, resilience, observability, and a step‑by‑step production checklist to turn AI capabilities into a maintainable, high‑throughput service.

AIBackendJava
0 likes · 38 min read
How to Build a Production‑Ready AI Service with Spring 7.0 and Spring AI for High‑Concurrency Microservices
Alibaba Cloud Native
Alibaba Cloud Native
Jun 21, 2026 · Cloud Native

One‑Line SDK Turns Electron Desktop Apps into Fully Observable Services

This article explains how the dual‑process architecture of Electron creates a monitoring blind spot, outlines four key challenges—separate runtimes, native crash dumps, unreliable data reporting, and unobservable IPC—and presents a single‑init SDK that provides zero‑config injection, local crash parsing, tRPC monitoring, distributed tracing, memory leak detection, and comprehensive exception protection while keeping overhead negligible.

ElectronSDKWasm
0 likes · 16 min read
One‑Line SDK Turns Electron Desktop Apps into Fully Observable Services
Cloud Architecture
Cloud Architecture
Jun 20, 2026 · Backend Development

Beyond Nearby Users: Building a Millisecond‑Level Real‑Time Dispatch System with GeoHash and Spring Boot

This article dissects the architecture, algorithms, and production practices behind a millisecond‑level real‑time dispatch system that uses GeoHash for spatial indexing, Spring Boot for service orchestration, Redis GEO for fast candidate selection, and a series of scoring, atomic reservation, and observability techniques to handle millions of riders under high concurrency.

GeoHashMicroservicesRedis Geo
0 likes · 36 min read
Beyond Nearby Users: Building a Millisecond‑Level Real‑Time Dispatch System with GeoHash and Spring Boot