Apple Container 1.0, an open‑source Linux container tool for Apple Silicon macOS 26, replaces Docker Desktop's shared VM with per‑container lightweight VMs, offering sub‑second startup, about 30% less idle memory, a persistent Container Machine environment, and detailed migration guidance.
A 3 am alert that once required hours of manual triage is now closed in six minutes thanks to AgentTeams, a cloud‑native platform that treats AI agents as first‑class citizens, defines declarative organization structures, and orchestrates multi‑agent collaboration across development, operations, and open‑source workflows.
OpenTelemetry eBPF Instrumentation (OBI) embeds a kernel‑level, zero‑code probe that automatically captures network traffic, RPC, database, message‑queue and GPU operations across Go, Java, Python, Node.js and .NET, generating standard OpenTelemetry traces and metrics without modifying application code.
The article explains how Alibaba Cloud's MaxCompute transforms a traditional data warehouse into a cloud‑native, multimodal Data+AI platform by introducing a four‑layer architecture, SQL‑based AI functions, the Python‑native MaxFrame framework, and a series of industry case studies that demonstrate performance gains and flexible resource scheduling.
An experienced architect compares RabbitMQ and Kafka across core protocols, storage, replication, consumption semantics, and real‑world production designs, offering Java 17/Spring Boot code, cloud‑native deployment tips, observability, and a decision framework that matches messaging patterns to business requirements.
This issue of Zhuanzhuan Frontend Weekly curates five industry articles that examine AI‑driven skill transformation for developers, the rise of Frontline Deployment Engineers, the three‑layer Agentic Engineering model, the distinction between Loop and Harness engineering, and cloud‑native AI‑Native multi‑agent architectures.
This guide walks through the problem of fluctuating traffic in Kubernetes, explains the differences between Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA), and provides step‑by‑step commands, YAML examples, best‑practice recommendations, troubleshooting tips, and monitoring alerts for deploying a production‑grade HPA + VPA solution.
This article provides a concise, step‑by‑step reference of the most frequently used kubectl commands for Kubernetes, explaining each command's purpose, typical scenarios, useful options, and the information it reveals to help operators troubleshoot clusters, nodes, pods, deployments, logs, and resources.
The article analyzes Alibaba Cloud's Agent Infra constraint infrastructure, detailing the Harness formula, the six foundational capabilities, concrete technical stacks, multi‑layer governance, observability, rule management, and a data‑driven feedback loop that enables continuous evolution of AI agents in production.
This article explains why Java applications face unique memory problems in Kubernetes, details the core conflict between container limits and JVM heap sizing, and provides step‑by‑step methods for collecting and analyzing heap dumps to resolve OOM kills, performance degradation, and memory leaks.
The article analyzes how security guardrails have shifted from invisible infrastructure components to visible product experiences, using Anthropic's Claude Fable 5, Alibaba Cloud's AI gateway, and cloud resource policies as case studies to illustrate design principles and implementation details.
The article details how a cloud‑native platform called AgentTeams enables AI‑Native multi‑agent digital‑human teams to replace manual incident response, automate end‑to‑end development workflows, and securely integrate LLMs and internal services through declarative orchestration and fine‑grained permission models.
The article explains how to capture event‑level AI coding agent data using LoongSuite‑Pilot, align it with the LoongSuite GenAI semantic conventions, store it in Alibaba Cloud Log Service (SLS), and construct a multi‑layered SQL dashboard that turns personal usage signals into organization‑wide metrics for informed decision‑making.
The Agentic AICon event gathered over 180 technical professionals to dissect enterprise‑scale agent engineering, presenting the full lifecycle of Agent Infra—including construction, deployment, observability, and intelligent operations—through detailed sessions on HiClaw, AgentRun, AgentLoop, STAROps, and a RocketMQ‑based asynchronous architecture.
The article analyzes how AI agents, platform engineering, and infrastructure‑as‑code are enabling IT departments to cut staff by up to two‑thirds while maintaining or even improving delivery, outlines which roles are disappearing, proposes a reference 45‑person structure, and warns that reduced headcount does not automatically mean proportional cost savings.
Facing exploding alarm volumes, cross‑cloud data silos, and slow root‑cause resolution, Geely Auto partnered with Alibaba Cloud STAROps to build a three‑step data foundation that unified heterogeneous data, enabled AI‑driven insight, and transformed the ops team from reactive responders to proactive platform operators.
This guide maps the complete skill tree for aspiring software architects, detailing foundational knowledge, core competencies such as system design and performance tuning, extended expertise in cloud‑native and big‑data technologies, and a staged learning roadmap to help newcomers acquire the necessary gear.
The article analyzes how AI is transforming IT hiring by favoring system‑level talent, ranks AI infrastructure, cloud‑native platform engineering and SRE as the most cost‑effective roles for the next 5‑10 years, and advises current ops staff to upskill accordingly.
The article examines how leading software companies such as Google, Microsoft, and Intel adopt and scale the SLSA framework, detailing internal validation, open‑source contributions, cloud‑native integration, and hardware‑anchored trust to illustrate a strategic shift toward industry‑wide software‑supply‑chain security.
The article examines Nacos 3.2’s transformation from a micro‑service registry into a unified AI asset governance platform, detailing the AI Registry, MCP Registry, multi‑layer Skill security, and Copilot integrations that address asset scattering, change difficulty, and security risks in enterprise AI deployments.
The article outlines a step‑by‑step architecture redesign for a 20‑year‑old monolithic production system, detailing problem analysis, a phased microservice migration using the "killer" pattern, data‑sync strategies, distributed transaction handling, observability, rollback mechanisms, and practical interview‑style insights.
Nacos 3.2 expands beyond a microservice registry to become a unified AI asset governance platform, introducing AI Registry, MCP Registry, a three‑layer Skill security sandbox, Copilot assistance, and A2A protocol integration, enabling seamless discovery, versioning, and secure execution of AI assets.
This guide walks SREs and DevOps engineers through the challenges of log aggregation in containerized Kubernetes environments and shows how Loki, Promtail, and Grafana together provide a low‑cost, label‑based alternative to the ELK stack, covering architecture, deployment, query language, multi‑tenant security, performance tuning, alerting, and disaster recovery.
This guide compiles over 200 practical kubectl commands, covering cluster setup, context switching, resource inspection, workload management, networking, storage, security hardening, high‑availability patterns, troubleshooting techniques, and performance monitoring to help operators efficiently administer Kubernetes environments.
The article details Alibaba Cloud’s LoongSuite platform, which leverages OpenTelemetry to provide non‑intrusive, end‑to‑end observability, auditing, and cost tracking for various AI Agent types—including coding assistants, personal assistants, and framework‑based agents—by introducing unified data collection, enriched GenAI semantic conventions, and plug‑in architectures that enable full traceability of LLM calls, tool executions, and multi‑round reasoning.
SkillClaw captures experience from real Agent conversations, automatically extracts reusable Skills, and, combined with Nacos’s AI Registry, provides versioned, audited, and team‑wide distribution, forming a closed‑loop pipeline that turns personal Agent knowledge into shared, governable AI assets.
The article analyzes the shortcomings of Kubernetes' native HPA and presents a comprehensive AI‑Agent architecture that predicts load, makes autonomous scaling decisions, and integrates with the K8s API to achieve proactive, adaptive, and globally coordinated pod autoscaling.
The article explains how to design a production‑grade, unified batch‑task platform on Kubernetes that goes beyond a simple job UI, covering unified abstractions, multi‑tenant governance, state‑machine modeling, scalable scheduling, high‑concurrency handling, observability, security, and a phased roadmap for incremental implementation.
This article explains how to design and operate a scalable, multi‑tenant batch processing platform on Kubernetes using Argo Workflows, covering core concepts, DAG scheduling, concurrency control, controller scaling, artifact handling, event‑driven triggers, and practical best‑practice patterns for production reliability and cost efficiency.
Alibaba Cloud's Knative now integrates a dedicated Agent Sandbox workload type, enabling stateful AI agents to run in a serverless Kubernetes environment with per‑user isolation, automatic scaling, instant pause/resume, and warm‑pool pre‑warming for zero‑cost idle periods.
The article explains how ontology—an explicit, unambiguous knowledge map—addresses the cognitive and data challenges of AIOps, describes the UModel framework that models entities, relationships, and telemetry, and shows how the STAROps agent built on UModel delivers more accurate, explainable, and trustworthy operations intelligence.
The article analyzes DataWorks Data Agent’s evolution from a helper‑style tool to an autonomous data‑centric AI agent, detailing its five‑stage roadmap, dual‑engine CLI/Claw architecture, unified runtime kernel, open skill ecosystem, and CPU‑GPU joint optimization for enterprise‑grade data automation.
This article explains that CrashLoopBackOff is a symptom, not the root cause, and walks through a production‑grade troubleshooting workflow—including checking pod status, describing events, examining logs (current and previous), and exec‑ing into containers—while covering common failures such as OOMKilled, liveness‑probe misconfiguration, bad config files, database connection issues, image command errors, and disk‑pressure problems, and warns against premature pod deletion.
This article presents a deep technical walkthrough of AgentScope Builder, showing how the Harness framework enables a single Java agent implementation to run on a personal machine as MinQwenPaw and then scale to a multi‑tenant, distributed enterprise platform with workspace isolation, sandboxing, and pluggable storage backends.
The article examines how AI‑native scientific agents demand flexible, secure, and observable infrastructure, and how Alibaba Cloud’s Serverless‑based AgentRun platform delivers extreme elasticity, cost reduction, stateful long‑running support, sandbox security, and full‑chain tracing to enable rapid deployment of tens of thousands of research tools.
Facing over 1 PB of daily sensor data, BYD replaced Airflow with a multi‑cluster Argo Workflows and Argo CD architecture, integrated Ray for GPU workloads, and achieved 20‑40 k concurrent workflows, an 11‑fold efficiency boost, 30% cost reduction, and near‑99% success rates.
NVIDIA quietly rewrote its AI cloud platform using Go, open‑sourcing NVCF, AICR, and AIStore, where Go accounts for over 80% of the code, enabling a three‑plane architecture, scale‑to‑zero via NATS JetStream, and a cloud‑native stack that balances performance, maintainability, and rapid iteration.
This article details Hisense's journey to create an AI‑ready multimodal data platform, covering the challenges of integrating diverse business systems, the shift from a Hadoop‑based architecture to a cloud‑native data lake, the JuData governance and development platform, and six practical scenarios that demonstrate unified ingestion, metadata management, rule‑based quality control, intelligent asset retrieval, and future AI‑driven DataOps capabilities.
The 2026 XCOPS Intelligent Operations Conference in Guangzhou gathered leading scholars, industry experts, and technology innovators to explore AI‑driven operational upgrades, database intelligence, cloud‑native observability, and multi‑agent architectures, with detailed talks, case studies, and practical roadmaps shared by speakers from academia, finance, and major tech firms.
As AI agents begin generating hundreds of lines of code and rapidly iterating database changes, traditional DBA manual review becomes obsolete; NineData’s AI‑native cloud‑native platform leverages intelligent SQL generation, automated review, and ChatDBA to boost development efficiency tenfold, cut repetitive work by 90%, and deliver high‑availability, secure, multi‑cloud data management at enterprise scale.
The article analyzes how AI agents require datacenter‑scale compute beyond a single virtual machine, explains why existing cloud‑native stacks cannot meet this demand, and details Ant Group's AKernel and openYuanrong solution—including three technical pillars, performance benchmarks, a tiny development team, and a streamlined deployment workflow that turns any developer into a "Build Your Own Cluster" operator.
The article explains Service Mesh as a cloud‑native architecture that separates control and data planes, details its sidecar proxies, core components like Istio Pilot and Citadel, and outlines key capabilities such as traffic management, security, observability, and resilience to help exam candidates master the topic.
Enterprises with hundreds of RESTful APIs often cannot expose them to AI agents, not because models are weak but because tool integration is cumbersome; the article shows how the MCP Gateway enables zero‑code conversion of existing interfaces, centralizes authentication, logging, and protocol translation, and supports multi‑backend scenarios for seamless AI ecosystem access.
This guide compiles the most critical architecture concepts for the software architect certification, covering mandatory styles, quality‑attribute analysis, ATAM evaluation, microservice vs. SOA/monolith trade‑offs, Lambda/Kappa big‑data designs, cloud‑native fundamentals, high‑concurrency web patterns, distributed‑system theories, DDD, AI‑ops, IoT/edge computing, blockchain basics, and DevOps practices, each illustrated with concrete metrics and decision‑making steps.
Nacos 3.2 evolves from a micro‑service registry into a unified AI asset governance platform, introducing AI Registry, MCP Registry with declarative protocol conversion, a three‑layer Skill security sandbox, Copilot assistance, and A2A integration to make AI capabilities manageable, auditable and reusable across the enterprise.
Facing hour‑level demands for new educational tools, Yuanfudao created the internal Rush platform that lets any employee describe a need in natural language and instantly receive a full‑stack application, thanks to Volcano Supabase’s AI‑native BaaS, dramatically cutting development time, cost, and operational complexity.
This article provides a comprehensive analysis of Spring AI Alibaba, detailing its five‑layer architecture, core capabilities such as unified model access, cloud‑native integration, and Agentic AI features, and offers concrete code examples and production recommendations to help Java developers quickly build and deploy AI agents.
The article draws a detailed analogy between millions of years of human evolution—standing up, shedding hair, expanding the brain, and recruiting ancient bacteria—and modern IT architecture, showing how each design choice brings hidden costs, why perfect systems are impossible, and how embracing trade‑offs, extensions, and continuous iteration can lead to resilient, self‑healing databases.
The article explains how enterprises can shrink a typical three‑hour CI/CD release pipeline to a 30‑second, controllable deployment by decoupling build, verification, deployment and release, adopting incremental builds, parallel validation, GitOps, Argo Rollouts, feature flags, and rigorous governance, resulting in a 300‑fold speedup.
The article analyzes the challenges of deploying AI agents in cloud‑native environments—cold‑start latency, state persistence, and security isolation—and presents Huawei Cloud’s Agent Harness Infra, which uses capacity‑prediction, parallel scheduling, microVM‑based decoupling, and lightweight OS techniques to achieve up to 5× throughput, 100 ms startup and 80% warm‑start hit rates.
This article walks through the design and implementation of a production‑grade, cloud‑native MySQL slow‑log collection and analysis platform, covering everything from MySQL slow‑log fundamentals and multi‑node ingestion to Kafka buffering, Go‑based parsing, SQL fingerprinting, Elasticsearch and ClickHouse storage, alerting, APM integration, and a phased rollout roadmap.
The article explains how Alibaba Cloud's MaxCompute has been transformed into a cloud‑native Data+AI platform, detailing its layered architecture, multimodal storage, model management, hybrid compute scheduling, SQL AI functions, the MaxFrame Python framework, and several enterprise case studies that demonstrate performance gains and flexible resource orchestration.
The article analyzes how software is evolving from static applications to goal‑driven AI agents, detailing the looped decision process, hierarchical architecture, multi‑agent collaboration, semantic data handling, memory as a knowledge system, and the cloud‑native deployment challenges of cost, security, and state management.
In 2026, the very standardization and structured nature of complex, multi‑service architectures turn them into ideal targets for AI agents, dramatically lowering the cost of automating architecture design, coding, and deployment, while human value shifts to ambiguous, strategic, and innovative tasks.
ScopeDB introduces a cloud‑native, real‑time analytics database that combines structured core columns with a flexible JSON column, adaptive indexing, a custom query language (ScopeQL), and true compute‑storage separation, delivering sub‑second query latency, high throughput, and up to 70% cost reduction compared with traditional big‑data stacks.
The article explains how GooseFS integrates with the Lance vector format to overcome the IO bottlenecks of object storage, detailing native acceleration mechanisms such as namespace catalog services, event‑driven warm caching, automatic compaction, native transactions, and page‑level caching that together deliver up to three‑fold performance gains for AI workloads.
This article provides a comprehensive, seven‑layer AIOps architecture that transforms raw infrastructure, application, log, alert, change, business, topology, and external knowledge data into intelligent, proactive operations, detailing the technologies, models, processes, and measurable benefits such as reduced MTTD, MTTR, and alert noise.
RocketMQ 5.0 replaces the monolithic Broker with a stateless Proxy layer that decouples compute from storage, solves scalability, multi‑protocol and cloud‑native adaptation challenges, and is demonstrated through detailed architecture comparisons, Java code samples, and two real‑world IoT and finance case studies showing significant performance and cost benefits.
The article analyzes why AI coding agents thrive in software engineering while agents in other industries lag, identifies context‑supply as the core bottleneck, and proposes a five‑dimensional framework—information completeness, sensory management, knowledge reconciliation, change governance, and accessibility—illustrated with EventHouse’s polling, event subscription, and mount‑query approaches, unified catalog, knowledge wiki, and CI/CD‑style release to make enterprise agents simple, reliable, and production‑ready.
This guide compiles the most frequently used Docker commands—covering basics, image handling, container control, volume management, networking, security, and additional utilities—providing clear screenshots to help developers boost deployment efficiency and resource management.
The article explains how Data as a Service (DaaS) builds on data lakes and SaaS models to centralize governance, cut duplication and infrastructure costs, accelerate real‑time analytics, support cloud‑native deployments, and enable mobile/web applications through unified APIs.
This article outlines a step‑by‑step Java learning roadmap—from core fundamentals to microservices, high‑concurrency, AI integration, and cloud‑native deployment—showing how targeted skill progression can dramatically boost both technical competence and earning potential.
The article argues that in 2026 code has become a cheap commodity and the true value of technology teams lies in amplifying individual, non‑technical, and organizational capabilities through AI agents, platform engineering, and observability, outlining concrete examples, architecture layers, and a three‑stage adoption path.
The article introduces the open‑source AgentRun CLI v0.1.0, explains how a single command can launch a hosted Agent, details its core features, declarative YAML API, six unified command groups, and shows how the new Python SDK integrates for full lifecycle management of Agentic AI workloads.
The article explains how Alibaba Cloud’s Hermes observability plugin, built on OpenTelemetry, makes the entire execution process of AI agents visible by tracing reasoning steps, tool calls, token usage, latency, and security risks, enabling precise cost, performance, and error analysis.
The half‑marathon race of over 300 humanoid robots highlighted three core operational bottlenecks—environmental uncertainty, hidden hardware‑software coupling risks, and outdated maintenance models—prompting a cloud‑native observability solution that combines metrics, tracing, and log governance to enable predictive, tiered fault handling for large‑scale deployments.
The article explains that running production Kubernetes clusters without regular backup and recovery plans exposes businesses to severe risks such as cluster failures, data loss, and prolonged downtime, and it details practical etcd physical and Velero logical backup strategies to mitigate these threats.
This guide explains GitOps fundamentals—declarative, versioned, automated deployments—and shows how tools like Argo CD, Flux, Helm, Kustomize, Tekton, and Sealed Secrets can speed up Kubernetes delivery, improve reliability, enhance security, and foster better collaboration across DevOps teams.
The article compares direct API calls, CLI tools, and the Model Context Protocol (MCP) for agent integration, explains MCP's token overhead, presents two token‑reduction strategies, and outlines design principles for building high‑availability MCP servers to maximize agent utility.
This guide explains why life‑insurance AI must move beyond black‑box recommendations, outlines eight production‑grade requirements, and presents a cloud‑native architecture that combines GraphRAG, rule engines, AI orchestration, observability, security, and Kubernetes to deliver explainable, auditable underwriting decisions.
The article details Vivo's activity system globalization, covering multilingual support, multi‑timezone handling, multi‑tenant architecture, multi‑datacenter deployment, and a unified global code line, showing how these measures increase component reuse, lower maintenance costs, and improve global service stability.
Airbnb completely rewrote its internal key‑value store Mussel, moving from a legacy V1 system to a cloud‑native, NewSQL‑backed V2 that reduces operational complexity, improves scalability, adds flexible consistency, and supports massive batch imports, all while achieving zero‑downtime migration of over 1 PB of data.
Analyzing over 500 community comments from Reddit, Hacker News, and X, this report compares OpenClaw and Hermes Agent, outlines their architectural differences, lists each platform's strengths and weaknesses, quantifies user adoption and cost, and proposes best‑practice patterns for combining the two in cloud‑native AI workflows.
AgentRun offers a cloud‑native, serverless platform that abstracts the full lifecycle of AI agents—definition, runtime, session, and event stream—while providing enterprise‑grade features such as model‑agnostic services, data‑in‑region networking, unified credential management, multi‑tenant isolation, full‑stack observability, and elastic scaling.
The article argues that deep Linux knowledge is essential for AI and cloud‑native work, cites real‑world incidents and market data showing 30‑50% higher salaries, and outlines a practical three‑month learning path to give newcomers a decisive career edge.
The article analyzes the unprecedented challenges of operating hundreds of humanoid robots in outdoor, network‑unstable, and heterogeneous environments, and demonstrates how Alibaba Cloud's unified observability stack—combining metric monitoring, distributed tracing, and log governance—delivers a standardized, reusable, and edge‑aware operations framework for large‑scale embodied AI deployments.
When Kubernetes becomes the backbone of enterprise applications and AI workloads, securing the container node OS is critical; ContainerOS tackles this by introducing an immutable root filesystem and eliminating the shell, thereby creating a read‑only, attack‑surface‑free environment that simplifies operations, guarantees integrity, and reduces costs.
This article presents a step‑by‑step guide to designing and implementing a production‑grade Kubernetes platform with GitOps, observability, capacity governance, fault‑injection, and SRE practices, showing how to achieve unified delivery, reliability, and low‑cost operation for high‑concurrency business services.
This article explains how Docker can streamline local development by isolating environments, using Docker Compose for multi‑service setups, enabling instant code changes with bind mounts or the official develop:watch feature, and simplifying database connections and common dev commands.
This comprehensive guide walks operators through the entire Kubernetes workflow from creating a Deployment to exposing a Service, explaining core resources, control loops, scheduling, networking, rolling updates, troubleshooting steps, best‑practice configurations, performance tuning, and security hardening.
This comprehensive Docker guide explains the technology’s rapid adoption in China, walks through installation, image management, data handling, networking, security, underlying Linux mechanisms, Docker Compose, and Mesos integration, providing step‑by‑step examples for ops engineers and backend developers.
The article analyzes enterprise testing challenges and presents the AIO intelligent testing platform, which combines cloud‑native architecture, MLLM‑RAG dual engines, and a knowledge‑graph to automate test case generation, improve coverage, and cut maintenance costs, backed by concrete benchmarks and multi‑modal inputs.
The Chinese database sector has moved beyond the question of whether domestic products exist to a fierce survival race where legacy system weight, migration engineering, and ecosystem strength determine which vendors can become lasting, cloud‑native, and AI‑ready infrastructure assets.
With microservices and cloud‑native workloads, manual performance test case creation consumes most testing time; this article details a four‑step method—traffic profiling, boundary stress injection, data factory integration, and smart script orchestration—to automatically generate realistic JMeter scripts, avoid common pitfalls, and embed performance contracts into CI/CD.
The article explains how HiClaw’s Worker templates turn ad‑hoc multi‑agent tasks into repeatable, stable processes by encapsulating skills, constraints, and SOPs, enabling easier reuse, versioning, and distribution across teams and private markets.
This article compares four microservice deployment strategies—single-host multi-instance, containerized with Kubernetes, serverless functions, and full orchestration—detailing their architectures, benefits, drawbacks, and suitable scenarios, helping engineers select the most appropriate approach for scalability, reliability, and operational complexity.
The article examines why Go remains dominant in core cloud‑native infrastructure in 2026—thanks to its static compilation, low memory footprint, and mature ecosystem—while highlighting emerging competition from Rust in high‑performance data planes and Python in AI workloads, and outlines Go’s recent evolutions such as generics, scheduler enhancements, and native observability.
The article revisits the rise and fall of database sharding, explains why it became problematic, and evaluates newer cloud‑native, distributed‑SQL, and serverless databases as modern replacements, offering a practical four‑step guide to help engineers choose the right solution for their workload and team.
This guide walks through deploying Prometheus and Grafana in a Kubernetes cluster using binary installation, detailing the Prometheus scrape configurations for core components, the necessary Service and Endpoints manifests, and how to reload the configuration to enable full‑stack monitoring.
This guide walks through deploying Prometheus (v2.51) and Grafana on a Kubernetes cluster, configuring hostPath storage, setting up node‑exporter, adding scrape jobs via Kubernetes service discovery, reloading configurations, and visualizing metrics through Grafana dashboards, with complete YAML examples and screenshots.
This article explains Docker's client‑server architecture, core isolation mechanisms like Linux namespaces and cgroups, the layered UnionFS image model, and how libcontainer/runc creates containers, providing a comprehensive technical overview of Docker as a cloud‑native platform.
In today's cloud‑native era, Prometheus and Grafana have become the de‑facto standard for full‑stack monitoring across servers, databases, containers, and applications, offering multi‑dimensional data models, flexible queries, and alerting that are essential skills for developers, SREs, and ops engineers.
The article details how the HiClaw distributed multi‑agent platform is built and organized for SRE teams, explains the roles of human users and digital bots, describes permission design, showcases fault‑diagnosis and release scenarios, and evaluates the efficiency and innovation gains of this cloud‑native automation approach.
This article details the design and implementation of a cloud‑native, real‑time monitoring system for Alibaba Cloud OpenAPI, covering background challenges, a Flink‑SLS architecture, multi‑region data processing, checkpoint and state‑backend tuning, source‑side predicate pushdown, visualization with Grafana, and production results.
This article analyses Lockheed Martin’s publicly disclosed software‑factory approach, showing how it prioritises sustained delivery of mission‑critical capabilities through tightly integrated DevSecOps, standardized environments, cloud‑native and GitOps practices, and an evolving focus on system interoperability.
The OpenClaw CMS observability plugin v0.1.2 solves the hidden‑trace problem by fully restoring multi‑round LLM execution, stabilizing concurrent chains, and introducing granular agent metrics, enabling developers, testers, and operators to debug faster, assess costs accurately, and improve cross‑team collaboration.
A March 2026 supply‑chain attack injected malicious code into LiteLLM versions 1.82.7/1.82.8, silently stealing API keys, SSH credentials, cloud tokens and more, while a cloud‑native AI gateway from Alibaba offers a secure, zero‑exposure alternative and detailed remediation steps.
EventHouse, Alibaba Cloud’s AI‑native data platform, unifies event ingestion, storage, governance and intelligent analysis through a layered architecture that supports real‑time SQL, zero‑ETL federation and Luma Agent‑driven conversational analytics, positioning it as a next‑generation AI data foundation for enterprises seeking to turn event streams into actionable insights.
This article analyzes the cloud‑native challenges of deploying large‑model inference on Kubernetes and presents Kthena’s architecture—ModelServing, Router, Autoscaler, and ModelBooster—along with Volcano integration, vLLM‑Ascend setup, and a real‑world Qwen3‑235B deployment case, highlighting performance gains and future directions.
An image is a static snapshot of an OS, runtime and code; a container runs that snapshot, while Dockerfile and docker‑compose define how to build and orchestrate images. Pods group containers for shared resources, and Kubernetes schedules, scales, heals, networks and stores them, enabling true “run anywhere” deployment.
