
Explore efficient management of large-scale etcd clusters using Tencent's open-source kstone platform. Learn about visualization, automated hazard detection, self-healing, and seamless migration for improved stability and reduced maintenance costs.

深入探讨CPU分析工具如何测量应用性能,介绍Linux perf、Golang pprof等工具的使用,并提出任务级CPU分析方法,有助于多租户服务的资源消耗评估。

Kube-OVN 集成多个 Kubernetes 网络创建统一网络平面,提高节点利用率,降低复杂性,支持数据中心级灾难恢复。演讲介绍构建跨 Kubernetes 网络平面并部署 TiDB 的方法。

使用开源工具构建云原生环境的网络安全工具包,保护初创企业的云原生环境。探讨如何利用生态系统中现有的开源工具创建安全工具集,为全生命周期提供保护。

Kubernetes数据保护工作组介绍:探讨当前状况、未来发展及如何参与。深入分析数据保护定义、用例、现有构建模块、缺失功能,以及应用程序备份和恢复的工作流程。

Explore volume health monitoring in Kubernetes for stateful workloads. Learn about current capabilities, ongoing improvements, and potential automatic correction methods for storage issues.

Explore CPU Burst feature to solve throttling issues, improve utilization, and enhance performance in Kubernetes environments without compromising resource limits.

Explore distributed GNN training using DGL and Kubernetes, improving resource utilization and scalability while reducing complexity. Learn about DGL Operator's implementation and future design.

探索AIOps在云基础设施智能分析中的应用,包括异常检测、资源预测、故障检测和根因分析,以提高云服务管理和运营效率。

探索Kubernetes优雅节点关闭功能的开发历程,从初学者视角介绍社区协作、功能实现和Pod优先级机制,展示Kubernetes生态系统的持续改进。

探索利用KServe加速联邦学习模型部署的实践。介绍Kubeflow、KFServing和推理服务工作流程,联邦学习基础知识,以及如何从水平训练的联邦学习模型创建服务。

Maximizing resource utilization through workload colocation on Kubernetes, featuring techniques like prediction, isolation, and interference detection for cost-effective, high-performance deployments.

Explore Bagua, a high-performance distributed deep learning project for Kubernetes, offering innovative communication algorithms and seamless integration for efficient training across various scenarios.

基于任务的并行计算和异步网络引擎,支持高并发请求处理。整合通信、计算、IO等异步资源,提供任务流概念实现复杂业务逻辑。跨平台、多协议,具备服务管理和负载均衡能力。

Explore how cloud-native technologies and Kubernetes accelerate robot application development, from containerization to simulation, deployment, and fleet operations.

Explore cross-vendor GPU computing with Vulkan and Kompute. Learn to write GPU-accelerated machine learning algorithms using Python and C++, applicable to various GPUs including AMD, Qualcomm, and NVIDIA.

探讨管理15k节点Kubernetes集群的挑战与优化策略,包括性能瓶颈识别、apiserver优化、etcd性能提升等,以满足大规模混合工作负载需求。

Explore Chaos Mesh 2.0, an open-source platform simplifying chaos engineering for cloud-native systems. Learn key features, conduct experiments, and integrate chaos testing into your workflow.

探讨OSPO在企业中的角色:统筹者还是阻碍者?分享华为OSPO的实践经验,解析OSPO的定位、职责和挑战,以及在中国推广开源文化的见解。

探讨如何整合FaaS、Dapr和Kubernetes技术,突破性能瓶颈,实现高密 度部署和高频创建删除,扩展FaaS边界,并大规模迁移现有应用到无服务器架构。

探索基于Tekton构建大规模云原生CI/CD系统,解决多集群跨区域部署挑战。分享ByteDance实践经验,包括性能优化和安全问题解决方案。