The article explains why the Kubernetes Dashboard has been deprecated due to security and multi‑cluster limitations, and introduces Headlamp as the officially endorsed, lightweight web UI that offers multi‑cluster management, strict RBAC enforcement, and extensible plugins, with simple installation steps.
This guide explains how to integrate the lightweight Cerebro monitoring tool with Easysearch, covering core features, configuration steps, and detailed solutions for frequent issues such as Java version conflicts, SSL certificate errors, and authentication mismatches.
Learn 15 practical kubectl techniques—from resource shortcuts and context switching to advanced JSONPath queries, custom output formats, and efficient alias configurations—that enable Kubernetes administrators to streamline cluster management, improve debugging, and boost operational productivity.
This guide provides a concise collection of essential Ceph commands for starting services, checking health and status, managing monitors, metadata servers, and OSDs, as well as creating admin users, purging nodes, and handling crush maps, enabling administrators to efficiently operate and troubleshoot a Ceph storage cluster.
This article walks through configuring Easysearch write throttling at the node, shard, and index levels, showing dynamic cluster settings, key parameters, DSL examples, and when to use retry versus drop actions to protect cluster stability during massive bulk indexing operations.
An experienced engineer shares practical Elasticsearch insights covering index design with aliases and routing, field type choices, query optimization techniques, pagination strategies, real‑time refresh settings, memory limits, and cluster management, offering concrete examples and actionable recommendations for robust search implementations.
This guide presents twenty practical Kubernetes best‑practice tips covering productivity shortcuts, resource limits, health probes, node draining, PodDisruptionBudgets, RBAC hardening, read‑only ConfigMaps/Secrets, non‑root containers, network policies, image version pinning, secret rotation, centralized logging, etcd backups, resource cleanup, and secure access methods.
This comprehensive guide walks you through the most useful kubectl commands for Kubernetes, covering cluster inspection, pod lifecycle, services, networking, storage, troubleshooting, performance tuning, security, and automation, empowering ops engineers to manage containerized clusters efficiently.
This guide explains why changing a ZooKeeper node’s IP requires updating the configuration on all members, then walks through a step‑by‑step procedure—including stopping the target node, editing zoo.cfg on every server, restarting the remaining nodes, and verifying the quorum—plus best‑practice tips for Kubernetes deployments.
The article introduces INFINI Console, an open‑source, lightweight platform for unified, multi‑cluster and cross‑version Elasticsearch governance, compares it with Kibana, details deployment options, enterprise‑level features such as monitoring, alerting and security, and analyzes cost advantages and practical migration scenarios.
This article explains how Tencent's WeChat team built the Astra platform on Ray to manage millions of AI compute nodes, addressing challenges of massive scale, heterogeneous GPU resources, low‑priority node instability, deployment complexity, and cost, while detailing architecture, scheduling strategies, and practical usage examples.
This guide explains the background of multi‑IDC Kubernetes clusters, why a unified platform like Rancher is needed, and provides detailed step‑by‑step instructions for single‑node, high‑availability RKE, lightweight K3s deployments, Helm installation, cert‑manager setup, ingress configuration, and best‑practice recommendations.
This comprehensive guide walks operations engineers through essential Kubernetes commands, covering cluster inspection, pod lifecycle, service and network handling, storage configuration, troubleshooting, performance monitoring, scaling, security, and automation, enabling efficient and expert management of containerized clusters.
This tutorial walks you through downloading the latest Kubernetes packages, preparing master and node services, adjusting nginx proxy settings, cordoning and draining nodes, replacing binaries and certificates, restarting services, and verifying the upgrade across a two‑node cluster.
This guide walks you through essential kubectl commands for viewing cluster status, inspecting resources, creating and modifying objects, labeling, annotating, and launching pods, providing practical examples and command syntax to help you manage Kubernetes clusters effectively.
The article provides a detailed technical overview of INFINI Console, an open‑source, lightweight governance platform that enables multi‑cluster, cross‑version management, dynamic registration, monitoring, alerting, and developer tools for Elasticsearch 9.X, comparing it with Kibana and highlighting deployment simplicity across various OS and CPU architectures.
This article introduces six indispensable tools—kubectl, Helm, Prometheus + Grafana, Istio, Velero, and K9s—that simplify Kubernetes cluster management by covering resource handling, monitoring, networking, security, backup, and interactive UI, helping readers efficiently operate production‑grade clusters.
The article explains what Elasticsearch coordinating nodes are, why dedicated coordinating‑only nodes can off‑load HTTP handling from data and master nodes to reduce load, lower latency and simplify client configuration, and outlines the associated hardware and cluster‑state costs, usage scenarios, deployment steps and monitoring tips.
This guide walks through upgrading a binary‑deployed Kubernetes cluster from v1.30.0 to v1.32.3, covering preparation, master and node upgrade procedures, deprecated API handling, validation, rollback, and best‑practice recommendations for production environments.
Kuboard is a web‑based visual tool for managing Kubernetes clusters, offering multi‑auth, multi‑cluster support, micro‑service layering, and storage integration; the guide explains Docker installation, adding clusters via KubeConfig, workload inspection, and how the UI simplifies complex command‑line operations.
This article provides a comprehensive overview of Ceph distributed storage, covering storage fundamentals, Ceph architecture, advantages, version lifecycle, and step‑by‑step deployment using ceph‑deploy, including environment preparation, monitor and OSD setup, manager configuration, and dashboard activation.
This article explains why high‑throughput producers and consumers can saturate CPU, memory, network and disk I/O in TDMQ Pulsar clusters, describes the built‑in cluster‑level distributed and topic‑partition rate‑limiting mechanisms, and provides practical guidance for configuration, monitoring, and troubleshooting.
This article explains three Elasticsearch data‑synchronization methods, compares their pros and cons, and then dives into ES cluster structure, node roles, shard allocation, distributed queries, split‑brain handling, and fault‑tolerance mechanisms, providing a comprehensive guide for developers and ops engineers.
The article explains two ways to recover access to INFINI Console when the password is lost: locating the original console_configuration.json file to retrieve the stored credentials, or using the built‑in Reset Password feature in the user management UI, with step‑by‑step instructions and screenshots.
Scaling Kubernetes across dozens or hundreds of clusters requires standardized core services—networking, security, observability, and automation—so organizations should adopt templated configurations, GitOps tools, centralized monitoring, and automated certificate management to reduce complexity, improve security, and lower operational overhead.
This article examines a recurring Kubernetes node NotReady issue where nodes become ready for only three minutes after a kubelet restart, detailing the underlying PLEG mechanism, component interactions, and diagnostic steps to resolve the problem.
To handle growing memory pressure across thousands of Redis servers, the platform implements an automated, daily resource‑balancing scheduler that selects overloaded hosts, chooses optimal nodes based on instance count, tier, and placement rules, then safely migrates them through a multi‑step process with rigorous validation.
This guide dissects the Elastic Certified Engineer 8.15 exam syllabus, explains each core topic—from searchable snapshots and async search to ILM policies and cross‑cluster replication—while offering a step‑by‑step study roadmap, hands‑on lab ideas, and resource recommendations to help candidates pass efficiently.
This article describes the design, architecture, and technical implementation of BMR's fault self‑healing platform, which automatically collects data, analyzes failures, defines decision rules, and executes safe recovery workflows to improve reliability and efficiency of massive, heterogeneous big‑data environments.
Bilibili's fault‑self‑healing platform for its massive BMR big‑data cluster—over 10,000 machines and 1 EB storage—adds near‑real‑time fault discovery, intelligent diagnosis, and automated workflow handling, dramatically cutting resolution time, improving stability across services, and scaling to dozens of daily automated repairs.
This article explains how Kubernetes Extended Resources let you define custom resource types, describes the creation, synchronization, and scheduling workflow, highlights the non‑real‑time allocatable status behavior, and discusses practical limitations and the role of Device Plugins and Operators.
Bilibili's One‑Stop Big Data Cluster Management Platform (BMR) unifies cluster, metadata, intelligent operations, and custom managers to oversee 50+ services, 10,000 machines, exabyte storage, and millions of cores, using cloud‑native containers, fault prediction, and resource‑sharing techniques to boost efficiency, stability, and cost savings.
This article analyzes Baidu's Baige 4.0 AI infrastructure, detailing its four‑layer architecture, XMAN 5.0 hardware, HPN network, BCCL communication library, and AIAK inference upgrades, and explains how these innovations address large‑model training and inference challenges while boosting performance, utilization, and cost efficiency.
This article examines the key pain points of massive AI compute clusters—including heterogeneous hardware compatibility, efficient scheduling, training and inference acceleration, and fault‑tolerant operations—while presenting practical management and performance‑tuning strategies, a cloud‑native AI platform implementation, and future directions for the ecosystem.
This article provides a comprehensive overview of Kubernetes (K8S), covering its origins, key problems it solves, master‑node architecture, core components such as kube‑apiserver, scheduler, controllers, node agents, and practical applications like CI/CD integration, multi‑tenant and micro‑service deployments.
This article explains ZooKeeper's hierarchical data model, node types, session mechanism, cluster roles and election process, ZAB protocol, watch mechanism, ACL permissions, and common distributed lock implementations, providing a comprehensive overview of its core concepts and practical usage.
Bilibili’s one‑stop Big Data Cluster Management Platform (BMR) consolidates HDFS, Spark, Flink, ClickHouse, Kafka and other services into a unified system that evolved through four stages—standardization, metadata‑driven construction, containerization, and observability—addressing node consistency, scaling, fault self‑healing, and resource optimization while delivering elastic scaling, automated start/stop, and future cost‑saving and stability enhancements.
This guide presents a comprehensive collection of the most important and frequently used kubectl commands, explaining how to retrieve version information, manage clusters, list resources, manipulate contexts, create, update, patch, scale, expose, delete, and debug Kubernetes objects, as well as format output and control verbosity, enabling DevOps engineers to efficiently operate Kubernetes clusters.
At the Create 2024 Baidu AI Developer Conference, Baidu unveiled its next‑generation intelligent computing operating system WanYuan, detailing its cluster‑scale management, GPU‑centric performance, integrated large‑model services, and a layered architecture that aims to simplify AI‑native application development and accelerate the AI era.
This curriculum provides a comprehensive, step‑by‑step exploration of Kubernetes internals—including kubeadm core source, Go module management, cobra libraries, kubeadm init/join processes, client‑go components, code generators, custom resources, operators, and practical deployment automation—aimed at mastering cluster setup, configuration, and advanced development.
This article explains the concept of kube‑on‑kube—creating a Kubernetes meta‑cluster to manage other clusters via declarative APIs—detailing its architecture, controller design, execution flow, and step‑by‑step code walkthrough including CRD definitions, Docker images, and deployment procedures.
The article recounts Yi Tay’s experience founding Reka and building large language models from scratch, highlighting the unpredictable quality of GPU clusters, the challenges of multi‑cluster orchestration, code‑base choices, and how startups must rely on fast, intuition‑driven experimentation to succeed.
After three years of hands‑on Kubernetes administration, the author shares ten practical lessons covering cloud‑hosted clusters, infrastructure‑as‑code, Helm chart usage, service mesh decisions, tool selection, resource limits, stateless design, HPA configuration, and upgrade strategies to help both newcomers and seasoned engineers manage clusters effectively.
This course provides comprehensive, hands‑on training on ElasticSearch, Logstash, Kibana, and the ElasticStack ecosystem, covering advanced development, cluster design, performance tuning, security, and real‑world integration techniques for large‑scale data processing.
This guide introduces Rancher as an open‑source container management platform and outlines step‑by‑step how to install Rancher, create clusters, add nodes, deploy applications, monitor resources, and manage user permissions for Kubernetes environments.
This guide compiles a comprehensive set of kubectl and Docker commands for retrieving logs, sorting pods, managing secrets, cleaning resources, debugging, port forwarding, and performing cluster maintenance tasks, helping administrators streamline Kubernetes operations and troubleshoot issues effectively.
Apache Pulsar, a cloud‑native distributed messaging platform, solves Didi Big Data’s DKafka bottlenecks by separating compute and storage, using sequential log writes, heterogeneous disks, multi‑level caching, bundle‑based load balancing and automatic scaling, dramatically improving stability while introducing richer monitoring complexity.
This article outlines how a large‑scale Kafka deployment of over a thousand machines across dozens of clusters was engineered for stability and efficiency through a custom Guardian controller that adds partition‑level throttling, automatic balancing, multi‑tenant isolation, cross‑IDC management, tiered storage, audit capabilities, and fully automated operational workflows.
This guide explains why HDFS enters safe mode after a DataNode failure, describes the safe‑mode state and its exit conditions, and provides step‑by‑step commands and troubleshooting procedures to analyze, fix, and recover from safe‑mode incidents in Hadoop clusters.
Explore nine indispensable Kubernetes tools—including Kubie, Kubespray, Helm, Minikube, K3s, Kustomize, KOps, Prometheus, and krew—that simplify cluster management, accelerate deployments, and enhance efficiency, helping you choose the right solution for smoother, more productive cloud‑native operations.
This article provides a step‑by‑step guide on how to replace OceanBase Cloud Platform (OCP) nodes using the ANTMAN tool, covering environment preparation, configuration adjustments, execution of management scripts, tenant migration, cleanup of old services, and troubleshooting tips for a seamless database cluster upgrade.
This guide explains what kubectl is, how it interacts with the Kubernetes API server, and provides a categorized list of essential commands for retrieving information, debugging, state management, scaling, deployment, and security, helping users efficiently operate and automate K8s clusters.
This article presents a comprehensive collection of 50 essential kubectl commands covering cluster, namespace, pod, deployment, service, ConfigMap, secret, volume, logging, debugging, scaling, configuration, and cleanup operations, providing testers with practical examples to efficiently manage and troubleshoot Kubernetes environments.
This article introduces Amiya, a self‑developed overcommit component that dynamically increases Yarn memory and vCore capacity on Bilibili's offline big‑data clusters, details its architecture, key implementation of overcommit, eviction and mixed‑deployment strategies, and evaluates its resource‑utilization impact.
Amiya, a self‑developed dynamic over‑commit component for Bilibili’s offline big‑data cluster, inflates reported resources on under‑utilized nodes and adjusts them when load rises, adding roughly 683 TB of memory and 137 k vCores, boosting per‑node memory by 15 % and CPU usage by over 20 % while keeping eviction rates below 3 %.
This article explains the motivations behind Kubernetes multi‑cluster deployments, outlines common use cases such as isolation and high‑availability, and analyzes core management elements including deployment models, control‑plane architectures, network connectivity, service discovery, cross‑cluster scheduling, application model extensions, and treating clusters as resources.
This article details how Zhaozhuan's DBA team transformed TiDB cluster management by addressing metadata, resource allocation, upgrade, and alert challenges through a comprehensive automation platform that streamlines work orders, node operations, scaling, monitoring, and alert handling, ultimately reducing manual effort and improving reliability.
This article explains the core concepts of Kubernetes—including its architecture, node communication, pod scheduling, data storage, service exposure, scaling, and controller coordination—through a series of clear questions and answers, helping beginners grasp why the platform feels complex.
This article provides a concise, question‑and‑answer overview of Kubernetes, explaining its role as a distributed container‑orchestration system, the architecture of master and worker nodes, core components such as etcd, kube‑apiserver, scheduler, controllers, and how services, pods, labels, and scaling operate within a cluster.
This article introduces Kubernetes fundamentals through a series of questions and answers, covering its architecture, node communication, pod scheduling, data storage, external access, scaling mechanisms, and component coordination, all illustrated with clear diagrams.
This article provides a concise, question‑driven overview of Kubernetes, covering its architecture, node and master communication, pod fundamentals, scheduling, storage via etcd, service exposure, scaling mechanisms, and the roles of core components such as kube‑apiserver, kubelet, kube‑proxy and controllers.
This guide explains why the Alertmanager configuration file in a TiDB cluster is repeatedly overwritten during reloads, analyzes error logs and TiUP documentation, and provides step‑by‑step instructions to edit the topology, set a custom config file, reload the service, and verify the fix.
This article introduces seven popular Kubernetes management solutions—including K9s, Rancher, the native Dashboard with Kubectl and Kubeadm, Helm, KubeSpray, Kontena Lens, and WKSctl—detailing their key features, usage scenarios, and how they help streamline cluster monitoring, deployment, scaling, and security across cloud‑native environments.
This article explains Elasticsearch’s fundamental building blocks, cluster roles, shard and replica strategies, master election, split‑brain prevention, inverted index structure, and the complete search and indexing lifecycle for handling large‑scale data efficiently.
This article details Meituan's large‑scale Kafka deployment—over 15,000 machines and petabyte‑level daily traffic—its operational challenges such as slow nodes, load imbalance, and resource contention, and the comprehensive read/write latency, system‑level, and cluster‑management optimizations implemented to improve performance and reliability.
This article explains Zookeeper's leader election mechanism by comparing it to human voting, detailing the four core concepts, the role of zxid, the step‑by‑step process during startup and runtime failures, and the key terms every interviewee should know.
This article details Meituan's large‑scale Kafka deployment, describing the current state, performance challenges such as slow nodes and disk imbalance, and the comprehensive optimizations applied—including read/write latency reductions, migration pipelines, fetcher isolation, SSD caching, RAID acceleration, cgroup isolation, full‑link monitoring, service lifecycle management, and TOR disaster recovery—to improve reliability and prepare for future growth.
This article details Meituan's real‑world challenges with a 15,000‑node Kafka deployment and explains the application‑layer and system‑layer optimizations—such as disk balancing, migration pipeline acceleration, fetcher isolation, RAID acceleration, cgroup isolation, and an SSD‑based cache—that together dramatically cut read/write latency and simplify large‑scale cluster management.
This article introduces essential Redis operational tools, covering real‑time monitoring with the INFO command and Prometheus‑exporter, data migration using Redis‑shake, consistency checking via Redis‑full‑check, and cluster management through CacheCloud, providing practical guidance for administrators.
This article demonstrates how to configure the open-source Orchestrator tool for automatic MySQL cluster failover, explains key parameters, and presents three test cases covering normal failover, lag‑induced prevention, and the effect of disabling global recoveries.
The vivo big‑data team details how they migrated massive real‑time workloads from Kafka to Apache Pulsar, describing cluster‑level bundle and ledger management, retention policies, a Prometheus‑Kafka‑Druid monitoring pipeline, load‑balancing tweaks, client tuning, rapid broker‑failure recovery, and future cloud‑native tracing and migration plans.
This article provides a comprehensive overview of the big data ecosystem, detailing nine essential technology categories—including data collection, storage, computation, analysis, resource management, retrieval, underlying infrastructure, and cluster installation—while comparing popular tools and illustrating their typical use‑cases with diagrams.
The article analyzes Meituan’s self‑designed Load Auto‑Regulator (LAR), detailing its tiered resource‑pool architecture, dynamic load‑to‑static‑resource mapping, and QoS mechanisms that together raise data‑center CPU utilization by 5‑10% while keeping online service quality stable, and discusses its deployment in online and mixed‑workload scenarios.
The article details Meituan's massive Kafka deployment—over 15,000 machines handling more than 30 PB of daily data—its performance and management challenges, and the comprehensive application‑layer, system‑layer, and hybrid‑layer optimizations Meituan implemented to reduce read/write latency and improve large‑scale cluster reliability.
This article details NetEase Interactive Entertainment's adoption of Apache Doris for large‑scale game data analytics, covering background, Doris architecture, cluster governance, tablet and compaction tuning, scaling strategies, monitoring, alerting, and fault‑handling practices to improve performance and stability.
Vivo replaced error‑prone manual Ansible playbooks with a custom Kubernetes Operator that uses declarative CRDs and modular Ansible scripts to automate the full lifecycle—deployment, scaling, upgrades, and recovery—of thousands of nodes across multiple data‑centers, supported by extensive CI testing and future kubeadm integration.
This article explains why Kafka suffers from broker‑side load imbalance, walks through manual replica migration examples, and then details how Cruise Control automates load balancing, supports resource‑group targeting, leader‑replica dispersion, and provides step‑by‑step deployment instructions.
Kafka’s server‑side load imbalance, caused by static replica placement on broker disks, makes manual replica migration infeasible at scale, but Cruise Control automates metric collection, analysis, and execution of fine‑grained rebalance plans—including broker de‑commissioning and leader dispersion—allowing large clusters to expand and operate efficiently.
This article details Bilibili's end‑to‑end Presto on Hadoop architecture, covering the multi‑engine SQL stack, dispatcher routing, cluster scale, stability enhancements like coordinator HA and real‑time punish, query limits, Hive UDF compatibility, insert‑overwrite support, Alluxio caching, multi‑datacenter routing, query result caching, Raptorx local cache, JDK upgrades, dynamic filtering, and future roadmap, illustrating how these innovations boosted query throughput and reduced latency.
This comprehensive guide explains what Elasticsearch does, its underlying Lucene engine, core concepts like clusters, shards, replicas, mappings, and provides practical steps for installation, configuration, indexing, storage mechanics, and performance optimization.
This article provides a comprehensive step‑by‑step guide for senior DBAs to upgrade an online TiDB 2.1.x cluster to version 4.0.13 via data migration, detailing environment assessment, configuration changes, component deployment, full and incremental data transfer, consistency verification, permission synchronization, and traffic switchover.
This article explains why Kubernetes single‑cluster scalability is limited to about 5,000 nodes, introduces the concept of multi‑cluster federation, compares the legacy kubefed project with the actively maintained Karmada solution, and shows how policies and replica‑scheduling enable flexible cross‑AZ deployments and failover.
This guide walks you through the hard‑way method for upgrading a Kubernetes cluster from version 1.22 to 1.23, covering prerequisites, master and worker node procedures, package handling, and verification steps to ensure a successful, fully controlled upgrade.
This article provides a comprehensive introduction to Elasticsearch, covering data types, Lucene fundamentals, inverted indexes, cluster components, node roles, shard and replica mechanisms, mapping, installation, health monitoring, write path, storage strategies, segment management, refresh and translog processes, as well as practical performance and JVM tuning tips.
This article presents Meituan's large‑scale Kafka deployment, describing the current state and challenges of massive data ingestion, detailing latency‑reduction techniques, cluster‑level optimizations, SSD‑based caching, isolation strategies, full‑link monitoring, lifecycle management, and future directions for high availability.
Discover the most popular Kubernetes management solutions—including K9s, Rancher, Dashboard, Helm, Kubespray, Lens, and WKSctl—detailing their features, deployment options, and how they streamline cluster monitoring, scaling, and security for cloud-native environments and improve operational efficiency.
This document provides a comprehensive technical overview of Elasticsearch, comparing it with Solr and ClickHouse, detailing common operational pain points and configuration solutions, describing containerized and ECK deployments, and outlining a company‑wide automation platform for cluster provisioning, monitoring, index and security management, with future directions for lifecycle and backup strategies.
This article explains the principles behind Elasticsearch searchable snapshots, details the DataTier model and node role optimizations, and provides a full practical walkthrough—including cluster setup, COS repository creation, ILM policy configuration, index templates, mounting strategies, and performance considerations—using ES 7.14.2.
This article explains how to manage Tencent Cloud Elasticsearch clusters by using key APIs to check health status, monitor pending tasks, retrieve metadata, view statistics, adjust shard allocation, modify cluster settings, and control tasks, providing practical command examples and detailed explanations for effective operations.
This article explains the design principles of Sealer's Clusterfile, details its configuration parameters, demonstrates how to inject additional settings and environment variables, and describes the supported plugins for customizing Kubernetes clusters, providing practical examples and code snippets.
This article explains how cloud‑native technologies enable a unified control plane for Alibaba Cloud ACK clusters and self‑built Kubernetes clusters, detailing the ACK registered‑cluster architecture, one‑way registration, non‑managed security mechanisms, step‑by‑step cluster onboarding, and consistent security governance across environments.
This article provides a comprehensive technical analysis of Kafka’s Controller component, covering its background, core responsibilities, data storage, election process, version‑specific improvements, monitoring techniques, and key source‑code excerpts to help engineers understand and manage Kafka clusters effectively.
This article shares a collection of powerful kubectl commands and tips—including API debugging, status‑based pod filtering and deletion, node‑specific pod listing, distribution counting with awk, and proxy usage—to help experienced Kubernetes users work more efficiently and avoid manual API client coding.
This article extends previous Elasticsearch cheat sheets with practical commands and step‑by‑step instructions for shard allocation, replica adjustment, cluster settings, slow‑log configuration, mapping routing, force merge, bulk writes, refresh intervals, translog durability, heap sizing, disk‑space monitoring, and troubleshooting strategies.
This article provides a comprehensive overview of Elasticsearch, covering its fundamental architecture, key concepts such as indices, shards and replicas, the complete write and search workflows, consistency mechanisms, master node election, and practical performance‑tuning recommendations for large‑scale deployments.
The first Shenzhen Elasticsearch meetup on August 21, 2021, jointly hosted by the ES Chinese community and Tencent Cloud, gathered experts from Tencent, Tapdata, ByteDance and Vivo to showcase rapid community growth, compression‑encoding optimizations, real‑time ES‑MongoDB data fusion, custom kernel extensions, large‑scale cluster practices, and concluded with extensive Q&A and networking.
This article explains the split‑brain phenomenon in distributed clusters, uses Zookeeper as a case study to illustrate how network partitions can create multiple leaders, and details Zookeeper's majority‑quorum mechanism, node count considerations, and common strategies for avoiding split‑brain scenarios.
The article examines Kubernetes' widespread adoption, outlines its scalability and multi‑cluster management constraints, discusses practical application scenarios such as deployment models, batch scheduling, and hard multi‑tenancy, and highlights the gaps that still limit its use in large‑scale production environments.
This article details JD's OLAP implementation using ClickHouse as the primary engine and Doris as a secondary engine, covering business scenarios, selection criteria, multi‑tenant deployment, high‑availability architecture, encountered challenges, and future roadmap for cloud‑native, scalable analytics.
This article details 58.com’s journey with Elasticsearch, covering the challenges of disparate deployments, common problems like disk exhaustion and write slowdown, the governance and automation platform they built, development standards, service architecture, real‑world application cases, and future plans for version upgrades and intelligent diagnostics.
