Giải pháp điều phối container trong môi trường production on Kubernetes

Babylon Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

A large number of Babylon's products leverage machine learning and artificial intelligence, and in 2019, there wasn't enough computing power in-house to run a particular experiment. The company was also growing (from 100 to 1,600 in three years) and planning expansion into other countries.

Solution

Babylon had migrated its user-facing applications to a Kubernetes platform in 2018, so the infrastructure team turned to Kubeflow, a toolkit for machine learning on Kubernetes. "We tried to create a Kubernetes core server, we deployed Kubeflow, and we orchestrated the whole experiment, which ended up being a really good success," says AI Infrastructure Lead Jérémie Vallée. The team began building a self-service AI training platform on top of Kubernetes.

Booz Allen Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

In 2017, Booz Allen Hamilton's Strategic Innovation Group worked with the federal government to relaunch the decade-old recreation.gov website, which provides information and real-time booking for more than 100,000 campsites and facilities on federal lands across the country. The infrastructure needed to be agile, reliable, and scalable—as well as repeatable for the other federal agencies that are among Booz Allen Hamilton's customers.

Solution

"The only way that we thought we could be successful with this problem across all the different agencies is to create a microservice architecture and containers, so that we could be very dynamic and very agile to any given agency for whatever requirements that they may have," says Booz Allen Hamilton Senior Lead Technologist Martin Folkoff. To meet those requirements, Folkoff's team looked to Kubernetes for orchestration.

Bose Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

A household name in high-quality audio equipment, Bose has offered connected products for more than five years, and as that demand grew, the infrastructure had to change to support it. "We needed to provide a mechanism for developers to rapidly prototype and deploy services all the way to production pretty fast," says Lead Cloud Engineer Josh West. In 2016, the company decided to start building a platform from scratch. The primary goal: "To be one to two steps ahead of the different product groups so that we are never scrambling to catch up with their scale," says Cloud Architecture Manager Dylan O'Mahony.

Booking.com Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

In 2016, Booking.com migrated to an OpenShift platform, which gave product developers faster access to infrastructure. But because Kubernetes was abstracted away from the developers, the infrastructure team became a "knowledge bottleneck" when challenges arose. Trying to scale that support wasn't sustainable.

Solution

After a year operating OpenShift, the platform team decided to build its own vanilla Kubernetes platform—and ask developers to learn some Kubernetes in order to use it. "This is not a magical platform," says Ben Tyler, Principal Developer, B Platform Track. "We're not claiming that you can just use it with your eyes closed. Developers need to do some learning, and we're going to do everything we can to make sure they have access to that knowledge."

AppDirect Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

AppDirect provides an end-to-end commerce platform for cloud-based products and services. When Director of Software Development Pierre-Alexandre Lacerte began working there in 2014, the company had a monolith application deployed on a "tomcat infrastructure, and the whole release process was complex for what it should be," he says. "There were a lot of manual steps involved, with one engineer building a feature, then another team picking up the change. So you had bottlenecks in the pipeline to ship a feature to production." At the same time, the engineering team was growing, and the company realized it needed a better infrastructure to both support that growth and increase velocity.

Denso Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

DENSO Corporation is one of the biggest automotive components suppliers in the world. With the advent of connected cars, the company launched a Digital Innovation Department to expand into software, working on vehicle edge and vehicle cloud products. But there were several technical challenges to creating an integrated vehicle edge/cloud platform: "the amount of computing resources, the occasional lack of mobile signal, and an enormous number of distributed vehicles," says R&D Product Manager Seiichi Koizumi.

Ocado Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

The world's largest online-only grocery retailer, Ocado developed the Ocado Smart Platform to manage its own operations, from websites to warehouses, and is now licensing the technology to other retailers such as Kroger. To set up the first warehouses for the platform, Ocado shifted from virtual machines and Puppet infrastructure to Docker containers, using CoreOS's fleet scheduler to provision all the services on its OpenStack-based private cloud on bare metal. As the Smart Platform grew and "fleet was going end-of-life," says Platform Engineer Mike Bryant, "we started looking for a more complete platform, with all of these disparate infrastructure services being brought together in one unified API."

Thuật ngữ chuẩn hóa

Mon, 01 Jan 0001 00:00:00 +0000

Các phiên bản được hỗ trợ của tài liệu Kubernetes

Mon, 01 Jan 0001 00:00:00 +0000

Trang web này lưu tài liệu của phiên bản hiện tại và bốn phiên bản trước của Kubernetes.

Cài đặt kubeadm

Mon, 01 Jan 0001 00:00:00 +0000

Trang này hướng dẫn cách cài đặt hộp công cụ kubeadm. Để biết thông tin về cách tạo một cụm với Kubeadm sau khi bạn đã thực hiện quy trình cài đặt này, xem trang Tạo một cụm với kubeadm.

Trang installation guide này dành cho Kubernetes v1.36. Nếu bạn muốn sử dụng phiên bản Kubernetes khác, vui lòng tham khảo các trang sau đây thay vì:

Cài đặt và cấu hình kubectl

Mon, 01 Jan 0001 00:00:00 +0000

Công cụ command-line trong Kubernetes, kubectl, cho phép bạn thực thi các câu lệnh trong Kubernetes clusters. Bạn có thể sử dụng kubectl để triển khai các ứng dụng, theo dõi và quản lý tài nguyên của cluster, và xem log. Để biết các thao tác của kubectl, truy cập tới Tổng quan về kubectl.

Trước khi bạn bắt đầu

Bạn cần phải sử dụng phiên bản kubectl sai lệch không quá một phiên bản với version của cluster. Ví dụ, một client v1.2 nên được hoạt động với master v1.1, v1.2 và v1.3. Sử dụng phiên bản mới nhất của kubectl giúp tránh được các vấn đề không lường trước được.

Cấp phát tài nguyên bộ nhớ cho Containers và Pods

Mon, 01 Jan 0001 00:00:00 +0000

Trang này hướng dẫn cách cấp phát bộ nhớ request (tối thiểu) và bộ nhớ limit (tối đa) cho một Container. Một Container được đảm bảo có đủ bộ nhớ như nó yêu cầu, nhưng không được phép sử dụng nhiều bộ nhớ hơn giới hạn của nó.

Trước khi bạn bắt đầu

Bạn cần có một cluster Kubernetes, và kubectl phải được cấu hình để giao tiếp với cluster của bạn. Khuyến nghị nên chạy hướng dẫn này trên một cluster có ít nhất hai node không đóng vai trò là máy chủ control plane. Nếu bạn chưa có cluster, bạn có thể tạo một cluster bằng cách sử dụng minikube hoặc sử dụng một trong các sân chơi Kubernetes sau:

Deployments

Mon, 01 Jan 0001 00:00:00 +0000

Trang này đang được dịch. Vui lòng xem phiên bản tiếng Anh để biết thông tin mới nhất.

Khám Phá Pods Và Nodes

Mon, 01 Jan 0001 00:00:00 +0000

Mục tiêu

Tìm hiểu Kubernetes Pods là gì?
Tìm hiểu Kubernetes Nodes là gì?
Khắc phục sự cố ứng dụng đã triển khai

Kubernetes Pods

Khi bạn triển khai ứng dụng thông qua Module 2, Kubernetes tạo ra Pod để lưu trữ phiên bản chạy của ứng dụng của bạn. Một Pod là một khái niệm trừu tượng của Kubernetes, đại diện cho một nhóm gồm một hoặc nhiều ứng dụng containers (ví dụ như Docker hoặc rkt) và một số tài nguyên được chia sẻ cho các containers đó. Những tài nguyên đó bao gồm:

Kubernetes là gì

Mon, 01 Jan 0001 00:00:00 +0000

Trang tổng quan của Kubernetes.

Kubernetes là một nền tảng nguồn mở, khả chuyển, có thể mở rộng để quản lý các ứng dụng được đóng gói và các service, giúp thuận lợi trong việc cấu hình và tự động hoá việc triển khai ứng dụng. Kubernetes là một hệ sinh thái lớn và phát triển nhanh chóng. Các dịch vụ, sự hỗ trợ và công cụ có sẵn rộng rãi.

Service

Mon, 01 Jan 0001 00:00:00 +0000

Trang này đang được dịch. Vui lòng xem phiên bản tiếng Anh để biết thông tin mới nhất.

Sử dụng kubectl để triển khai ứng dụng

Mon, 01 Jan 0001 00:00:00 +0000

Mục tiêu

Tìm hiểu về triển khai ứng dụng (Deployment).
Triển khai ứng dụng đầu tiên của bạn trên Kubernetes với kubectl.

Kubernetes Deployments

Giả sử bạn đã có một Kubernetes cluster đang hoạt động, bạn có thể triển khai ứng dụng của bạn trên cluster này. Để thực hiện điều đó, bạn cần tạo một kịch bản triển khai (Deployment). Kịch bản này sẽ giúp Kubernetes có thể tạo và cập nhật các phiên bản chạy (instances) của ứng dụng của bạn. Sau khi một kịch bản triển khai được tạo ra trong Kubernetes, node Master sẽ lập lịch để khởi chạy ứng dụng của bạn trên các Node của cluster.

Sử dụng Minikube để tạo một Cluster

Mon, 01 Jan 0001 00:00:00 +0000

Mục tiêu

Tìm hiểu Kubernetes cluster là gì?
Tìm hiểu Minikube là gì?
Khởi tạo một Kubernetes cluster sử dụng terminal trực tuyến.

Kubernetes Clusters

Kubernetes kết nối và điều phối các máy tính trong một cluster để chúng có thể hoạt động như một đơn vị thống nhất (unit). Nó cho phép bạn triển khai các ứng dụng trên Container mà không cần phải bận tâm chúng sẽ được khởi chạy trên chiếc máy tính cụ thể nào trong cluster. Để sử dụng mô hình triển khai của Kubernetes, các ứng dụng cần được đóng gói theo một cách linh động và không phụ thuộc vào từng máy tính cụ thể (host): tức là các ứng dụng được Container hóa. Các ứng dụng dạng Container có được sự khả chuyển và sẵn sàng cao hơn các mô hình triển khai được sử dụng trong quá khứ, ở đó chúng được cài đặt trực tiếp trên các máy tính cụ thể và gắn chặt với các bộ thư viện trên đó. Kubernetes phân bổ và điều phối các ứng dụng hoàn toàn tự động xuyên suốt cluster theo một cách hiệu quả. Ngoài ra Kubernetes là mã nguồn mở và sẵn sàng để sử dụng trong môi trường triển khai thực tế (production).

Sử dụng Service để công khai ứng dụng

Mon, 01 Jan 0001 00:00:00 +0000

Mục tiêu

Tìm hiểu về Service trong Kubernetes
Hiểu mối quan hệ giữa labels và selectors với Service
Công khai một ứng dụng ra bên ngoài Kubernetes cluster

Tổng quan về Service trong Kubernetes

Pods trong Kubernetes có tính tạm thời. Pods có một vòng đời nhất định. Khi một worker node ngừng hoạt động, các Pod đang chạy trên Node đó cũng bị mất. Một ReplicaSet có thể tự động điều chỉnh cluster về trạng thái mong muốn bằng cách tạo các Pod mới để giữ cho ứng dụng tiếp tục hoạt động. Ví dụ khác, hãy xem xét một backend xử lý container image với 3 bản sao. Những bản sao này có thể thay thế lẫn nhau; hệ thống frontend không cần quan tâm đến các bản sao backend hoặc việc một Pod bị mất và được tạo lại. Tuy nhiên, mỗi Pod trong Kubernetes cluster đều có một địa chỉ IP duy nhất, kể cả các Pod trên cùng một Node, vì vậy cần có cơ chế tự động điều phối các thay đổi giữa các Pod để ứng dụng có thể tiếp tục hoạt động.

Các biến môi trường của Container

Mon, 01 Jan 0001 00:00:00 +0000

Trang này mô tả các tài nguyên có sẵn cho các Containers trong môi trường Container.

Môi trường container

Môi trường Container trong Kubernetes cung cấp một số tài nguyên quan trọng cho Container:

Một hệ thống tệp tin (filesystem), là sự kết hợp của một image và một hoặc nhiều volumes.
Thông tin về chính container đó.
Thông tin về các đối tượng (object) khác trong cluster.

Thông tin container

Hostname của một Container là tên của Pod mà Container đang chạy trong đó. Có thể lấy thông tin qua lệnh hostname hoặc lệnh gọi hàm gethostname trong libc.

Cài đặt Minikube

Mon, 01 Jan 0001 00:00:00 +0000

Tài liệu này sẽ hướng dẫn các bạn cách cài đặt Minikube, một công cụ chạy một Kubernetes cluster chỉ gồm một node trong một máy ảo (VM) trên máy tính của bạn.

Trước khi bạn bắt đầu

Để kiểm tra xem việc ảo hóa (virtualization) có được hỗ trợ trên Linux không, chạy lệnh sau và chắc chắn rằng kết quả trả về là non-empty:

Hướng dẫn tương tác - Khám phá ứng dụng

Mon, 01 Jan 0001 00:00:00 +0000

Để tương tác với Terminal, hãy sử dụng phiên bản dành cho desktop/tablet

Tiếp tục với Module 4›

Hướng dẫn tương tác - Tạo một Cluster

Mon, 01 Jan 0001 00:00:00 +0000

Để tương tác với Terminal, hãy dùng phiên bản dành cho desktop/tablet

Tiếp tục Module 2

Hướng dẫn tương tác - Triển khai một ứng dụng

Mon, 01 Jan 0001 00:00:00 +0000

Để tương tác với Terminal, hãy sử dụng phiên bản dành cho desktop/tablet

Tiếp tục với Module 3\u203a

Persistent Volumes

Mon, 01 Jan 0001 00:00:00 +0000

Trang này đang được dịch. Vui lòng xem phiên bản tiếng Anh để biết thông tin mới nhất.

Container Lifecycle Hooks

Mon, 01 Jan 0001 00:00:00 +0000

Trang này mô tả cách mà kubelet quản lý các Container có thể sử dụng framework Container lifecycle hook để chạy mã nguồn được kích hoạt bởi các sự kiện trong lifecycle của nó.

Tổng quan

Tương tự như nhiều framework ngôn ngữ lập trình có thành phần các lifecycle hooks, như là Angular, Kubernetes cung cấp các Container cùng với các lifecycle hook. Các hooks cho phép các Container nhận thức được các sự kiện trong lifecycle của chúng và chạy mã nguồn được triển khai trong một trình xử lý khi lifecycle hook tương ứng được thực thi.

Leases

Mon, 01 Jan 0001 00:00:00 +0000

Trong các hệ thống phân tán, Kubernetes sử dụng cơ chế leases (giữ quyền tạm thời) để khóa tài nguyên dùng chung và điều phối hoạt động giữa các thành phần trong cụm. Trong Kubernetes, lease được biểu diễn bằng các đối tượng Lease thuộc API group coordination.k8s.io API Group, Những đối tượng này đóng vai trò quan trọng trong hệ thống, ví dụ như theo dõi trạng thái node (heartbeat) và cơ chế bầu chọn leader giữa các thành phần nội bộ.

Pinterest Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

After eight years in existence, Pinterest had grown into 1,000 microservices and multiple layers of infrastructure and diverse set-up tools and platforms. In 2016 the company launched a roadmap towards a new compute platform, led by the vision of creating the fastest path from an idea to production, without making engineers worry about the underlying infrastructure.

Solution

The first phase involved moving services to Docker containers. Once these services went into production in early 2017, the team began looking at orchestration to help create efficiencies and manage them in a decentralized way. After an evaluation of various solutions, Pinterest went with Kubernetes.

Secrets

Mon, 01 Jan 0001 00:00:00 +0000

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Các khái niệm nền tảng của Cloud Controller Manager

Mon, 01 Jan 0001 00:00:00 +0000

Khái niệm Cloud Controller Manager (CCM) (để tránh nhầm lẫn với bản binary build cùng tên) được định nghĩa riêng biệt để cho phép các bên cung cấp dịch vụ cloud và thành phần chính của Kubernetes phát triển độc lập với nhau. CCM chạy đồng thời với những thành phần khác thuộc máy chủ của một cluster như Controller Manager của Kubernetes, API server, và Scheduler. Nó cũng có thể đóng vai trò như một addon cho Kubernetes.

Adform Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Adform's mission is to provide a secure and transparent full stack of advertising technology to enable digital ads across devices. The company has a large infrastructure: OpenStack-based private clouds running on 1,100 physical servers in 7 data centers around the world, 3 of which were opened in the past year. With the company's growth, the infrastructure team felt that "our private cloud was not really flexible enough," says IT System Engineer Edgaras Apšega. "The biggest pain point is that our developers need to maintain their virtual machines, so rolling out technology and new software takes time. We were really struggling with our releases, and we didn't have self-healing infrastructure."

Ygrene Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

A PACE (Property Assessed Clean Energy) financing company, Ygrene has funded more than $1 billion in loans since 2010. In order to approve and process those loans, "We have lots of data sources that are being aggregated, and we also have lots of systems that need to churn on that data," says Ygrene Development Manager Austin Adams. The company was utilizing massive servers, and "we just reached the limit of being able to scale them vertically. We had a really unstable system that became overwhelmed with requests just for doing background data processing in real time. The performance the users saw was very poor. We needed a solution that wouldn't require us to make huge refactors to the code base." As a finance company, Ygrene also needed to ensure that they were shipping their applications securely.

SlingTV Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Launched by DISH Network in 2015, Sling TV experienced great customer growth from the beginning. After just a year, "we were going through some growing pains of some of the legacy systems and trying to find the right architecture to enable our future," says Brad Linder, Sling TV's Cloud Native & Big Data Evangelist. The company has particular challenges: "We take live TV and distribute it over the internet out to a user's device that we do not control," says Linder. "In a lot of ways, we are working in the Wild West: The internet is what it is going to be, and if a customer's service does not work for whatever reason, they do not care why. They just want things to work. Those are the variables of the equation that we have to try to solve. We really have to try to enable optionality and good customer experience at web scale."

Các tùy chọn cho kiến trúc có tính Sẵn sàng cao

Mon, 01 Jan 0001 00:00:00 +0000

Trang này giải thích hai lựa chọn cho việc cấu hình kiến trúc cho các cụm Kubernetes có tính sẵn sàng cao (HA) của bạn.

Bạn có thể thiết lập một cụm HA:

Với các control plane node xếp chồng, nơi các etcd node được đặt cùng vị trí với các control plane node
Với các etcd node bên ngoài, nơi etcd chạy trên từng node riêng biệt so với các control plane node

Bạn nên cân nhắc kỹ lưỡng những ưu điểm và nhược điểm của từng kiến trúc trước khi thiết lập một cụm HA.

ING Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

After undergoing an agile transformation, ING realized it needed a standardized platform to support the work their developers were doing. "Our DevOps teams got empowered to be autonomous," says Infrastructure Architect Thijs Ebbers. "It has benefits; you get all kinds of ideas. But a lot of teams are going to devise the same wheel. Teams started tinkering with Docker, Docker Swarm, Kubernetes, Mesos. Well, it's not really useful for a company to have one hundred wheels, instead of one good wheel.

Jobs

Mon, 01 Jan 0001 00:00:00 +0000

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Kubernetes - Khả năng tự phục hồi (Self-Healing)

Mon, 01 Jan 0001 00:00:00 +0000

Kubernetes được thiết kế với khả năng tự phục hồi giúp duy trì tình trạng khỏe mạnh và tính khả dụng của các workload. Nó tự động thay thế các container bị lỗi, lập lịch lại các workload khi node trở nên không khả dụng, và đảm bảo rằng trạng thái mong muốn của hệ thống được duy trì.

Khả năng tự phục hồi

Khởi động lại ở cấp độ container: Nếu một container bên trong Pod bị lỗi, Kubernetes sẽ khởi động lại nó dựa trên restartPolicy.

Quản lý tài nguyên cho Containers

Mon, 01 Jan 0001 00:00:00 +0000

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Tạo các cụm có tính Sẵn sàng cao với kubeadm

Mon, 01 Jan 0001 00:00:00 +0000

Trang này giải thích hai cách tiếp cận khác nhau để thiết lập một cụm Kubernetes sẵn sàng cao sử dụng kubeadm:

Với các control plane node xếp chồng. Cách tiếp cận này yêu cầu ít cơ sở hạ tầng. Các etcd member và control plane node nằm cùng vị trí.
Với một cụm etcd bên ngoài. Cách tiếp cận này yêu cầu nhiều cơ sở hạ tầng hơn. Các control plane node và etcd member được tách biệt.

Trước khi tiến hành, bạn nên cân nhắc kỹ lưỡng cách tiếp cận nào đáp ứng tốt nhất nhu cầu của các ứng dụng và môi trường của bạn. Các tùy chọn cho kiến trúc có tính Sẵn sàng cao chỉ ra các ưu điểm và nhược điểm của từng cách đó.

Thiết lập một cụm etcd có tính Sẵn sàng cao (High Availability) với kubeadm

Mon, 01 Jan 0001 00:00:00 +0000

Mặc định, kubeadm chạy một instance etcd cục bộ trên từng node control plane. Bạn cũng có thể thiết lập cụm etcd bên ngoài và cung cấp các etcd instance trên các máy chủ riêng biệt. Những sự khác biệt giữa hai cách tiếp cận này được trình bày trong trang Các tùy chọn cho kiến trúc có tính Sẵn sàng cao.

Tác vụ này hướng dẫn quy trình tạo một cụm etcd bên ngoài có tính sẵn sàng cao gồm ba member mà kubeadm có thể sử dụng trong quá trình tạo cụm.

Horizontal Pod Autoscaling

Mon, 01 Jan 0001 00:00:00 +0000

Trang này đang được dịch. Vui lòng xem phiên bản tiếng Anh để biết thông tin mới nhất.

IPv4/IPv6 dual-stack

Mon, 01 Jan 0001 00:00:00 +0000

Trang này đang được dịch. Vui lòng xem phiên bản tiếng Anh để biết thông tin mới nhất.

Proxy Đa Phiên Bản (Mixed Version Proxy)

Mon, 01 Jan 0001 00:00:00 +0000

TRẠNG THÁI TÍNH NĂNG: Kubernetes v1.36 [beta](enabled by default)

Kubernetes 1.36 giới thiệu một tính năng alpha cho phép API Server proxy các yêu cầu tài nguyên đến các API server ngang hàng khác. Tính năng này đặc biệt hữu ích khi trong một cụm có nhiều API server đang chạy các phiên bản Kubernetes khác nhau (ví dụ: trong quá trình nâng cấp cụm kéo dài sang phiên bản mới).

Mon, 01 Jan 0001 00:00:00 +0000

Quy tắc ứng xử cộng đồng CNCF v1.0

Quy tắc ứng xử người đóng góp

Là người đóng góp và duy trì dự án này, và vì lợi ích thúc đẩy một cộng đồng mở, chúng tôi cam kết tôn trọng tất cả những người đóng góp thông qua việc báo cáo các vấn đề, các tính năng yêu cầu, cập nhật tài liệu, gửi PRs hay patches, và các hoạt động khác.

Mon, 01 Jan 0001 00:00:00 +0000

Tài liệu trong thư mục này được lấy từ nguồn khác. Vui lòng không trực tiếp sửa chúng, ngoại trừ việc thay thế chúng với phiên bản khác.

Mon, 01 Jan 0001 00:00:00 +0000

Tài liệu Kubernetes

Kho lưu trữ này chứa các tài sản cần thiết để xây dựng trang web và tài liệu Kubernetes. Chúng tôi rất vui mừng khi bạn muốn đóng góp!

Đóng góp vào tài liệu
READMEs đa ngôn ngữ

Sử dụng kho lưu trữ này

Bạn có thể chạy trang web này ở chế độ local bằng cách sử dụng Hugo (Phiên bản mở rộng), hoặc bạn có thể chạy nó trong một container runtime. Chúng tôi khuyến nghị sử dụng container runtime, vì nó mang lại tính nhất quán trong triển khai so với trang web thực tế.

adidas Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

In recent years, the adidas team was happy with its software choices from a technology perspective—but accessing all of the tools was a problem. For instance, "just to get a developer VM, you had to send a request form, give the purpose, give the title of the project, who's responsible, give the internal cost center a call so that they can do recharges," says Daniel Eichten, Senior Director of Platform Engineering. "The best case is you got your machine in half an hour. Worst case is half a week or sometimes even a week."

Amadeus Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

In the past few years, Amadeus, which provides IT solutions to the travel industry around the world, found itself in need of a new platform for the 5,000 services supported by its service-oriented architecture. The 30-year-old company operates its own data center in Germany, and there were growing demands internally and externally for solutions that needed to be geographically dispersed. And more generally, "we had objectives of being even more highly available," says Eric Mountain, Senior Expert, Distributed Systems at Amadeus. Among the company's goals: to increase automation in managing its infrastructure, optimize the distribution of workloads, use data center resources more efficiently, and adopt new technologies more easily.

Ancestry Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Ancestry, the global leader in family history and consumer genomics, uses sophisticated engineering and technology to help everyone, everywhere discover the story of what led to them. The company has spent more than 30 years innovating and building products and technologies that at their core, result in real and emotional human responses. Ancestry currently serves more than 2.6 million paying subscribers, holds 20 billion historical records, 90 million family trees and more than four million people are in its AncestryDNA network, making it the largest consumer genomics DNA network in the world. The company's popular website, ancestry.com, has been working with big data long before the term was popularized. The site was built on hundreds of services, technologies and a traditional deployment methodology. "It's worked well for us in the past," says Paul MacKay, software engineer and architect at Ancestry, "but had become quite cumbersome in its processing and is time-consuming. As a primarily online service, we are constantly looking for ways to accelerate to be more agile in delivering our solutions and our products."

Ant Financial Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Officially founded in October 2014, Ant Financial originated from Alipay, the world's largest online payment platform that launched in 2004. The company also offers numerous other services leveraging technology innovation. With the volume of transactions Alipay handles for its 900+ million users worldwide (through its local and global partners)—256,000 transactions per second at the peak of Double 11 Singles Day 2017, and total gross merchandise value of $31 billion for Singles Day 2018—not to mention that of its other services, Ant Financial faces "data processing challenge in a whole new way," says Haojie Hang, who is responsible for Product Management for the Storage and Compute Group. "We see three major problems of operating at that scale: how to provide real-time compute, storage, and processing capability, for instance to make real-time recommendations for fraud detection; how to provide intelligence on top of this data, because there's too much data and then we're not getting enough insight; and how to apply security in the application level, in the middleware level, the system level, even the chip level." In order to provide reliable and consistent services to its customers, Ant Financial embraced containers in early 2014, and soon needed an orchestration solution for the tens-of-thousands-of-node clusters in its data centers.

BlaBlaCar Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

The world's largest long-distance carpooling community, BlaBlaCar, connects 40 million members across 22 countries. The company has been experiencing exponential growth since 2012 and needed its infrastructure to keep up. "When you're thinking about doubling the number of servers, you start thinking, 'What should I do to be more efficient?'" says Simon Lallemand, Infrastructure Engineer at BlaBlaCar. "The answer is not to hire more and more people just to deal with the servers and installation." The team knew they had to scale the platform, but wanted to stay on their own bare metal servers.

BlackRock Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

The world's largest asset manager, BlackRock operates a very controlled static deployment scheme, which has allowed for scalability over the years. But in their data science division, there was a need for more dynamic access to resources. "We want to be able to give every investor access to data science, meaning Python notebooks, or even something much more advanced, like a MapReduce engine based on Spark," says Michael Francis, a Managing Director in BlackRock's Product Group, which runs the company's investment management platform. "Managing complex Python installations on users' desktops is really hard because everyone ends up with slightly different environments. We have existing environments that do these things, but we needed to make it real, expansive and scalable. Being able to spin that up on demand, tear it down, make that much more dynamic, became a critical thought process for us. It's not so much that we had to solve our main core production problem, it's how do we extend that? How do we evolve?"

Box Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Founded in 2005, the enterprise content management company allows its more than 50 million users to manage content in the cloud. Box was built primarily with bare metal inside the company's own data centers, with a monolithic PHP code base. As the company was expanding globally, it needed to focus on "how we run our workload across many different cloud infrastructures from bare metal to public cloud," says Sam Ghods, Cofounder and Services Architect of Box. "It's been a huge challenge because of different clouds, especially bare metal, have very different interfaces."

Buffer Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

With a small but fully distributed team of 80 working across almost a dozen time zones, Buffer—which offers social media management to agencies and marketers—was looking to solve its "classic monolithic code base problem," says Architect Dan Farrelly. "We wanted to have the kind of liquid infrastructure where a developer could create an app and deploy it and scale it horizontally as necessary."

Solution

Embracing containerization, Buffer moved its infrastructure from Amazon Web Services' Elastic Beanstalk to Docker on AWS, orchestrated with Kubernetes.

Capital One Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

The team set out to build a provisioning platform for Capital One applications deployed on AWS that use streaming, big-data decisioning, and machine learning. One of these applications handles millions of transactions a day; some deal with critical functions like fraud detection and credit decisioning. The key considerations: resilience and speed—as well as full rehydration of the cluster from base AMIs.

Solution

The decision to run Kubernetes "is very strategic for us," says John Swift, Senior Director Software Engineering. "We use Kubernetes as a substrate or an operating system, if you will. There's a degree of affinity in our product development."

CERN Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

At CERN, the European Organization for Nuclear Research, physicists conduct experiments to learn about fundamental science. In its particle accelerators, "we accelerate protons to very high energy, close to the speed of light, and we make the two beams of protons collide," says CERN Software Engineer Ricardo Rocha. "The end result is a lot of data that we have to process." CERN currently stores 330 petabytes of data in its data centers, and an upgrade of its accelerators expected in the next few years will drive that number up by 10x. Additionally, the organization experiences extreme peaks in its workloads during periods prior to big conferences, and needs its infrastructure to scale to those peaks. "We want to have a more hybrid infrastructure, where we have our on premise infrastructure but can make use of public clouds temporarily when these peaks come up," says Rocha. "We've been looking to new technologies that can help improve our efficiency in our infrastructure so that we can dedicate more of our resources to the actual processing of the data."

China Unicom Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

China Unicom is one of the top three telecom operators in China, and to serve its 300 million users, the company runs several data centers with thousands of servers in each, using Docker containerization and VMWare and OpenStack infrastructure since 2016. Unfortunately, "the resource utilization rate was relatively low," says Chengyu Zhang, Group Leader of Platform Technology R&D, "and we didn't have a cloud platform to accommodate our hundreds of applications." Formerly an entirely state-owned company, China Unicom has in recent years taken private investment from BAT (Baidu, Alibaba, Tencent) and JD.com, and is now focusing on internal development using open source technology, rather than commercial products. As such, Zhang's China Unicom Lab team began looking for open source orchestration for its cloud infrastructure.

Chính sách về độ lệch phiên bản

Mon, 01 Jan 0001 00:00:00 +0000

Độ lệch phiên bản (version skew) đề cập đến sự khác biệt về phiên bản giữa các thành phần khác nhau trong cụm Kubernetes. Điều quan trọng là phải quản lý độ lệch phiên bản để đảm bảo khả năng tương thích và tính ổn định trong cụm.

Tài liệu này mô tả độ lệch phiên bản tối đa được hỗ trợ giữa các thành phần Kubernetes khác nhau.

City of Montreal Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Like many governments, Montréal has a number of legacy systems, and "we have systems that are older than some developers working here," says the city's CTO, Jean-Martin Thibault. "We have mainframes, all flavors of Windows, various flavors of Linux, old and new Oracle systems, Sun servers, all kinds of databases. Like all big corporations, some of the most important systems, like Budget and Human Resources, were developed on mainframes in-house over the past 30 years." There are over 1,000 applications in all, and most of them were running on different ecosystems. In 2015, a new management team decided to break down those silos, and invest in IT in order to move toward a more integrated governance for the city. They needed to figure out how to modernize the architecture.

Community

Mon, 01 Jan 0001 00:00:00 +0000

Quy tắc ứng xử cộng đồng Kubernetes

Kubernetes tuân theo quy tắc ứng xử CNCF. Văn bản của CNCF CoC được sao chép dưới đây, kể từ commit 214585e. Nếu bạn nhận thấy rằng điều này đã lỗi thời, xin vui lòng gửi một vấn đề.

Nếu bạn nhận thấy vi phạm Quy tắc ứng xử tại một sự kiện hoặc cuộc họp, trong Slack, hoặc trong một cơ chế giao tiếp khác, hãy liên lạc với Ủy ban Quy tắc ứng xử Kubernetes. Bạn có thể liên hệ với chúng tôi qua email tại conduct@kubernetes.io. Sự ẩn danh của bạn sẽ được bảo vệ.

Crowdfire Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Crowdfire helps content creators create their content anywhere on the Internet and publish it everywhere else in the right format. Since its launch in 2010, it has grown to 16 million users. The product began as a monolith app running on Google App Engine, and in 2015, the company began a transformation to microservices running on Amazon Web Services Elastic Beanstalk. "It was okay for our use cases initially, but as the number of services, development teams and scale increased, the deploy times, self-healing capabilities and resource utilization started to become problems for us," says Software Engineer Amanpreet Singh, who leads the infrastructure team for Crowdfire.

DaoCloud Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenges

DaoCloud, founded in 2014, is an innovation leader in the field of cloud native. It boasts independent intellectual property rights of core technologies for crafting an open cloud platform to empower the digital transformation of enterprises.

DaoCloud has been engaged in cloud native since its inception. As containerization is crucial for cloud native business, a cloud platform that does not have containers as infrastructure is unlikely to attract its potential users. Therefore, the first challenge confronting DaoCloud is how to efficiently manage and schedule numerous containers while maintaining stable connectivity between them.

Ghi chú

Mon, 01 Jan 0001 00:00:00 +0000

Bạn có thể tìm thấy ghi chú về bản phát hành (Release Note) của phiên bản Kubernetes bạn đang sử dụng thông qua trang Changelog trong repo Kubernetes trên GitHub. Ví dụ, ghi chú về bản phát hành 1.36 tại Changelog Kubernetes.

Ngoài ra, bạn cũng có thể tìm kiếm ghi chú về bản phát hành một cách trực tiếp thông qua: relnotes.k8s.io. Ví dụ, ghi chú về bản phát hành 1.36 tại relnotes.k8s.io.

GolfNow Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

A member of the NBC Sports Group, GolfNow is the golf industry's technology and services leader, managing 10 different products, as well as the largest e-commerce tee time marketplace in the world. As its business began expanding rapidly and globally, GolfNow's monolithic application became problematic. "We kept growing our infrastructure vertically rather than horizontally, and the cost of doing business became problematic," says Sheriff Mohamed, GolfNow's Director, Architecture. "We wanted the ability to more easily expand globally."

Haufe Group Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Founded in 1930 as a traditional publisher, Haufe Group has grown into a media and software company with 95 percent of its sales from digital products. Over the years, the company has gone from having "hardware in the basement" to outsourcing its infrastructure operations and IT. More recently, the development of new products, from Internet portals for tax experts to personnel training software, has created demands for increased speed, reliability and scalability. "We need to be able to move faster," says Solution Architect Martin Danielsson. "Adapting workloads is something that we really want to be able to do."

Huawei Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

A multinational company that's the largest telecommunications equipment manufacturer in the world, Huawei has more than 180,000 employees. In order to support its fast business development around the globe, Huawei has eight data centers for its internal I.T. department, which have been running 800+ applications in 100K+ VMs to serve these 180,000 users. With the rapid increase of new applications, the cost and efficiency of management and deployment of VM-based apps all became critical challenges for business agility. "It's very much a distributed system so we found that managing all of the tasks in a more consistent way is always a challenge," says Peixin Hou, the company's Chief Software Architect and Community Director for Open Source. "We wanted to move into a more agile and decent practice."

IBM Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

IBM Cloud offers public, private, and hybrid cloud functionality across a diverse set of runtimes from its OpenWhisk-based function as a service (FaaS) offering, managed Kubernetes and containers, to Cloud Foundry platform as a service (PaaS). These runtimes are combined with the power of the company's enterprise technologies, such as MQ and DB2, its modern artificial intelligence (AI) Watson, and data analytics services. Users of IBM Cloud can exploit capabilities from more than 170 different cloud native services in its catalog, including capabilities such as IBM's Weather Company API and data services. In the later part of 2017, the IBM Cloud Container Registry team wanted to build out an image trust service.

JD.com Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

With more than 300 million active users and total 2017 revenue of more than $55 billion, JD.com is China's largest retailer, and its operations are the epitome of hyperscale. For example, there are more than a trillion images in JD.com's product databases—with 100 million being added daily—and this enormous amount of data needs to be instantly accessible. In 2014, JD.com moved its applications to containers running on bare metal machines using OpenStack and Docker to "speed up the delivery of our computing resources and make the operations much simpler," says Haifeng Liu, JD.com's Chief Architect. But by the end of 2015, with tens of thousands of nodes running in multiple data centers, "we encountered a lot of problems because our platform was not strong enough, and we suffered from bottlenecks and scalability issues," says Liu. "We needed infrastructure for the next five years of development, now."

kubectl Cheat Sheet

Mon, 01 Jan 0001 00:00:00 +0000

Xem thêm: Kubectl Overview và JsonPath Guide.

Trang này là trang tổng quan của lệnh kubectl.

kubectl - Cheat Sheet

Kubectl Autocomplete

BASH

source <(kubectl completion bash) # thiết lập autocomplete trong bash vào shell hiện tại, gói bash-completion nên được cài đặt trước tiên 
echo "source <(kubectl completion bash)" >> ~/.bashrc # thêm vĩnh viễn autocomplete vào trong bash shell

Bạn có thể dùng một alias cho kubectl cũng hoạt động với completion:

NAIC Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

The National Association of Insurance Commissioners (NAIC), the U.S. standard-setting and regulatory support organization, was looking for a way to deliver new services faster to provide more value for members and staff. It also needed greater agility to improve productivity internally.

Solution

Beginning in 2016, they started using Cloud Native Computing Foundation (CNCF) tools such as Prometheus. NAIC began hosting internal systems and development systems on Kubernetes at the beginning of 2018, as part of a broad move toward the public cloud. "Our culture and technology transition is a strategy embraced by our top leaders," says Dan Barker, Chief Enterprise Architect. "It has already proven successful by allowing us to accelerate our value pipeline by more than double while decreasing our costs by more than half. We are also seeing customer satisfaction increase as we add more and more applications to these new technologies."

Nav Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Founded in 2012, Nav provides small business owners with access to their business credit scores from all three major commercial credit bureaus—Equifax, Experian and Dun & Bradstreet—and financing options that best fit their needs. Five years in, the startup was growing rapidly, and "our cloud environments were getting very large, and our usage of those environments was extremely low, like under 1%," says Director of Engineering Travis Jeppson. "We wanted our usage of cloud environments to be more tightly coupled with what we actually needed, so we started looking at containerization and orchestration to help us be able to run workloads that were distinct from one another but could share a similar resource pool."

NetEase Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Its gaming business is one of the largest in the world, but that's not all that NetEase provides to Chinese consumers. The company also operates e-commerce, advertising, music streaming, online education, and email platforms; the last of which serves almost a billion users with free email services through sites like 163.com. In 2015, the NetEase Cloud team providing the infrastructure for all of these systems realized that their R&D process was slowing down developers. "Our users needed to prepare all of the infrastructure by themselves," says Feng Changjian, Architect for NetEase Cloud and Container Service. "We were eager to provide the infrastructure and tools for our users automatically via serverless container service."

New York Times Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

When the company decided a few years ago to move out of its data centers, its first deployments on the public cloud were smaller, less critical applications managed on virtual machines. "We started building more and more tools, and at some point we realized that we were doing a disservice by treating Amazon as another data center," says Deep Kapadia, Executive Director, Engineering at The New York Times. Kapadia was tapped to lead a Delivery Engineering Team that would "design for the abstractions that cloud providers offer us."

Nokia Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Nokia's core business is building telecom networks end-to-end; its main products are related to the infrastructure, such as antennas, switching equipment, and routing equipment. "As telecom vendors, we have to deliver our software to several telecom operators and put the software into their infrastructure, and each of the operators have a bit different infrastructure," says Gergely Csatari, Senior Open Source Engineer. "There are operators who are running on bare metal. There are operators who are running on virtual machines. There are operators who are running on VMware Cloud and OpenStack Cloud. We want to run the same product on all of these different infrastructures without changing the product itself."

Nordstrom Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Nordstrom wanted to increase the efficiency and speed of its technology operations, which includes the Nordstrom.com e-commerce site. At the same time, Nordstrom Technology was looking for ways to tighten its technology operational costs.

Solution

After embracing a DevOps transformation and launching a continuous integration/continuous deployment (CI/CD) project four years ago, the company reduced its deployment time from three months to 30 minutes. But they wanted to go even faster across environments, so they began their cloud native journey, adopting Docker containers orchestrated with Kubernetes.

Northwestern Mutual Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

In the spring of 2015, Northwestern Mutual acquired a fintech startup, LearnVest, and decided to take "Northwestern Mutual's leading products and services and meld it with LearnVest's digital experience and innovative financial planning platform," says Brad Williams, Director of Engineering for Client Experience, Northwestern Mutual. The company's existing infrastructure had been optimized for batch workflows hosted on on-prem networks; deployments were very traditional, focused on following a process instead of providing deployment agility. "We had to build a platform that was elastically scalable, but also much more responsive, so we could quickly get data to the client website so our end-customers have the experience they expect," says Williams.

OpenAI Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

An artificial intelligence research lab, OpenAI needed infrastructure for deep learning that would allow experiments to be run either in the cloud or in its own data center, and to easily scale. Portability, speed, and cost were the main drivers.

Solution

OpenAI began running Kubernetes on top of AWS in 2016, and in early 2017 migrated to Azure. OpenAI runs key experiments in fields including robotics and gaming both in Azure and in its own data centers, depending on which cluster has free capacity. "We use Kubernetes mainly as a batch scheduling system and rely on our autoscaler to dynamically scale up and down our cluster," says Christopher Berner, Head of Infrastructure. "This lets us significantly reduce costs for idle nodes, while still providing low latency and rapid iteration."

Pear Deck Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

The three-year-old startup provides a web app for teachers to interact with their students in the classroom. The JavaScript app was built on Google's web app development platform Firebase, using Heroku. As the user base steadily grew, so did the development team. "We outgrew Heroku when we started wanting to have multiple services, and the deploying story got pretty horrendous. We were frustrated that we couldn't have the developers quickly stage a version," says CEO Riley Eynon-Lynch. "Tracing and monitoring became basically impossible." On top of that, many of Pear Deck's customers are behind government firewalls and connect through Firebase, not Pear Deck's servers, making troubleshooting even more difficult.

Pearson Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

A global education company serving 75 million learners, Pearson set a goal to more than double that number, to 200 million, by 2025. A key part of this growth is in digital learning experiences, and Pearson was having difficulty in scaling and adapting to its growing online audience. They needed an infrastructure platform that would be able to scale quickly and deliver products to market faster.

Solution

"To transform our infrastructure, we had to think beyond simply enabling automated provisioning," says Chris Jackson, Director for Cloud Platforms & SRE at Pearson. "We realized we had to build a platform that would allow Pearson developers to build, manage and deploy applications in a completely different way." The team chose Docker container technology and Kubernetes orchestration "because of its flexibility, ease of management and the way it would improve our engineers' productivity."

pingcap Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

PingCAP is the company leading the development of the popular open source NewSQL database TiDB, which is MySQL-compatible, can handle hybrid transactional and analytical processing (HTAP) workloads, and has a cloud native architectural design. "Having a hybrid multi-cloud product is an important part of our global go-to-market strategy," says Kevin Xu, General Manager of Global Strategy and Operations. In order to achieve that, the team had to address two challenges: "how to deploy, run, and manage a distributed stateful application, such as a distributed database like TiDB, in a containerized world," Xu says, and "how to deliver an easy-to-use, consistent, and reliable experience for our customers when they use TiDB in the cloud, any cloud, whether that's one cloud provider or a combination of different cloud environments." Knowing that using a distributed system isn't easy, they began looking for the right orchestration layer to help reduce some of that complexity for end users.

Prowise Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Nerdalize offers affordable cloud hosting for customers—and free heat and hot water for people who sign up to house the heating devices that contain the company's servers. The savings Nerdalize realizes by not running data centers are passed on to its customers. When the team began using Docker to make its software more portable, it realized it also needed a container orchestration solution. "As a cloud provider, we have internal services for hosting our backends and billing our customers, but we also need to offer our compute to our end users," says Digital Product Engineer Ad van der Veer. "Since we have these heating devices spread across the Netherlands, we need some way of tying that all together."

Prowise Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

A Dutch company that produces educational devices and software used around the world, Prowise had an infrastructure based on Linux services with multiple availability zones in Europe, Australia, and the U.S. "We've grown a lot in the past couple of years, and we started to encounter problems with versioning and flexible scaling," says Senior DevOps Engineer Victor van den Bosch, "not only scaling in demands, but also in being able to deploy multiple products which all have their own versions, their own development teams, and their own problems that they're trying to solve. To be able to put that all on the same platform without much resistance is what we were looking for. We wanted to future proof our infrastructure, and also solve some of the problems that are associated with just running a normal Linux service."

Quản lý phát hành

Mon, 01 Jan 0001 00:00:00 +0000

"Người quản lý phát hành" là thuật ngữ chung bao gồm nhóm những người đóng góp cho Kubernetes chịu trách nhiệm duy trì các nhánh phát hành và tạo các bản phát hành bằng cách sử dụng các công cụ mà SIG Release cung cấp.

Vai trò của từng nhóm được thể hiện như sau

Thông tin liên hệ
- Chính sách cấm chia sẻ thông tin an ninh
Handbooks
Nhóm quản lý phát hành
- Tham gia nhóm quản lý phát hành
Nhóm dự bị quản lý phát hành
- Tham gia nhóm dự bị quản lý phát hành
SIG Release Leads
- Chairs
- Technical Leads

Thông tin liên hệ

Mailing List	Slack	Visibility	Mục đích	Thành viên
release-managers@kubernetes.io	#release-management (channel) / @release-managers (user group)	Public	Nơi thảo luận công khai của nhóm quản lý phát hành	Tất cả thành viên (bao gồm cả nhóm trợ lý, và SIG Chairs)
release-managers-private@kubernetes.io	N/A	Private	Nơi thảo luận riêng cho các quản trị viên đặc quyền	Nhóm quản trị phát hành, leader tại SIG Release
security-release-team@kubernetes.io	#security-release-team (channel) / @security-rel-team (user group)	Private	Nhóm an ninh và nhóm ứng phó sự cố an ninh	security-discuss-private@kubernetes.io, release-managers-private@kubernetes.io

Chính sách cấm chia sẻ thông tin an ninh

Một số thông tin về bản phát hành có thể không được công khai và chúng tôi đã xác định chính sách về cách thiết lập lệnh cấm công khai đó. Tham khảo thêm tại Chính sách cấm chia sẻ thông tin an ninh.

ReplicaSet

Mon, 01 Jan 0001 00:00:00 +0000

Trang này đang được dịch. Vui lòng xem phiên bản tiếng Anh để biết thông tin mới nhất.

ricardo.ch Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

A Swiss online marketplace, ricardo.ch was experiencing problems with velocity, as well as a "classic gap" between Development and Operations, with the two sides unable to work well together. "They wanted to, but they didn't have common ground," says Cedric Meury, Head of Platform Engineering. "This was one of the root causes that slowed us down." The company began breaking down the legacy monolith into microservices, and needed orchestration to support the new architecture in its own data centers—as well as bring together Dev and Ops.

Slamtec Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Founded in 2013, SLAMTEC provides service robot autonomous localization and navigation solutions. The company's strength lies in its R&D team's ability to quickly introduce, and continually iterate on, its core products. In the past few years, the company, which had a legacy infrastructure based on Alibaba Cloud and VMware vSphere, began looking to build its own stable and reliable container cloud platform to host its Internet of Things applications. "Our needs for the cloud platform included high availability, scalability and security; multi-granularity monitoring alarm capability; friendliness to containers and microservices; and perfect CI/CD support," says Benniu Ji, Director of Cloud Computing Business Division.

SOS International Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

For the past six decades, SOS International has been providing reliable medical and travel assistance in the Nordic region. In recent years, the company's business strategy has required increasingly intense development in the digital space, but when it came to its IT systems, "SOS has a very fragmented legacy," with three traditional monoliths (Java, .NET, and IBM's AS/400) and a waterfall approach, says Martin Ahrentsen, Head of Enterprise Architecture. "We have been forced to institute both new technology and new ways of working, so we could be more efficient with a shorter time to market. It was a much more agile approach, and we needed to have a platform that can help us deliver that to the business."

Spotify Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Launched in 2008, the audio-streaming platform has grown to over 200 million monthly active users across the world. "Our goal is to empower creators and enable a really immersive listening experience for all of the consumers that we have today—and hopefully the consumers we'll have in the future," says Jai Chakrabarti, Director of Engineering, Infrastructure and Operations. An early adopter of microservices and Docker, Spotify had containerized microservices running across its fleet of VMs with a homegrown container orchestration system called Helios. By late 2017, it became clear that "having a small team working on the features was just not as efficient as adopting something that was supported by a much bigger community," he says.

Squarespace Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Moving from a monolith to microservices in 2014 "solved a problem on the development side, but it pushed that problem to the infrastructure team," says Kevin Lynch, Staff Engineer on the Site Reliability team at Squarespace. "The infrastructure deployment process on our 5,000 VM hosts was slowing everyone down."

Solution

The team experimented with container orchestration platforms, and found that Kubernetes "answered all the questions that we had," says Lynch. The company began running Kubernetes in its data centers in 2016.

Tải xuống Kubernetes

Mon, 01 Jan 0001 00:00:00 +0000

Kubernetes cung cấp các tệp nhị phân cho từng thành phần cũng như một bộ các công cụ chuẩn để khởi động hoặc tương tác với một cụm. Các thành phần như máy chủ API (kube-apiserver) có khả năng chạy trong container image (tương tự một ứng dụng trên Kubernetes) bên trong một cụm. Các thành phần như vậy được đóng gói dưới dạng container image như một phần của quy trình phát hành chính thức. Tất cả các tệp nhị phân cũng như container image được phát hành tương thích cho nhiều hệ điều hành cũng như phần cứng.

ThredUp Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

The largest online consignment store for women's and children's clothes, ThredUP launched in 2009 with a monolithic application running on Amazon Web Services. Though the company began breaking up the monolith into microservices a few years ago, the infrastructure team was still dealing with handcrafted servers, which hampered productivity. "We've configured them just to get them out as fast as we could, but there was no standardization, and as we kept growing, that became a bigger and bigger chore to manage," says Cofounder/CTO Chris Homer. The infrastructure, they realized, needed to be modernized to enable the velocity the company needed. "It's really important to a company like us who's disrupting the retail industry to make sure that as we're building software and getting it out in front of our users, we can do it on a fast cycle and learn a ton as we experiment," adds Homer. "We wanted to make sure that our engineers could embrace the DevOps mindset as they built software. It was really important to us that they could own the life cycle from end to end, from conception at design, through shipping it and running it in production, from marketing to ecommerce, the user experience and our internal distribution center operations."

vsco Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

After moving from Rackspace to AWS in 2015, VSCO began building Node.js and Go microservices in addition to running its PHP monolith. The team containerized the microservices using Docker, but "they were all in separate groups of EC2 instances that were dedicated per service," says Melinda Lu, Engineering Manager for the Machine Learning Team. Adds Naveen Gattu, Senior Software Engineer on the Community Team: "That yielded a lot of wasted resources. We started looking for a way to consolidate and be more efficient in the AWS EC2 instances."

Wikimedia Case Study

Mon, 01 Jan 0001 00:00:00 +0000

The non-profit Wikimedia Foundation operates some of the largest collaboratively edited reference projects in the world, including Wikipedia. To help users maintain and use wikis, it runs Wikimedia Tool Labs, a hosting environment for community developers working on tools and bots to help editors and other volunteers do their work, including reducing vandalism. The community around Wikimedia Tool Labs began forming nearly 10 years ago.

"Wikimedia Tool Labs is vital for making sure wikis all around the world work as well as they possibly can. Because it's grown organically for almost 10 years, it has become an extremely challenging environment and difficult to maintain. It's like a big ball of mud — you really can't see through it. With Kubernetes, we're simplifying the environment and making it easier for developers to build the tools that make wikis run better." — Yuvi Panda, operations engineer at Wikimedia Foundation and Wikimedia Tool Labs

Challenges

Simplify a complex, difficult-to-manage infrastructure
Allow developers to continue writing tools and bots using existing techniques

Why Kubernetes

Wikimedia Tool Labs chose Kubernetes because it can mimic existing workflows, while reducing complexity

Approach

Migrate old systems and a complex infrastructure to Kubernetes

Results

20 percent of web tools that account for more than 40 percent of web traffic now run on Kubernetes
A 25-node cluster that keeps up with each new Kubernetes release
Thousands of lines of old code have been deleted, thanks to Kubernetes

Using Kubernetes to provide tools for maintaining wikis

Wikimedia Tool Labs is run by a staff of four-and-a-half paid employees and two volunteers. The infrastructure didn't make it easy or intuitive for developers to build bots and other tools to make wikis work more easily. Yuvi says, "It's incredibly chaotic. We have lots of Perl and Bash duct tape on top of it. Everything is super fragile."

Wink Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Building a low-latency, highly reliable infrastructure to serve communications between millions of connected smart-home devices and the company's consumer hubs and mobile app, with an emphasis on horizontal scalability, the ability to encrypt everything quickly and connections that could be easily brought back up if anything went wrong.

Solution

Across-the-board use of a Kubernetes-Docker-CoreOS Container Linux stack.

Impact

"Two of the biggest American retailers [Home Depot and Walmart] are carrying and promoting the brand and the hardware," Wink Head of Engineering Kit Klein says proudly – though he adds that "it really comes with a lot of pressure. It's not a retail situation where you have a lot of tech enthusiasts. These are everyday people who want something that works and have no tolerance for technical excuses." And that's further testament to how much faith Klein has in the infrastructure that the Wink team has built. With 80 percent of Wink's workload running on a unified stack of Kubernetes-Docker-CoreOS, the company has put itself in a position to continually innovate and improve its products and services. Committing to this technology, says Klein, "makes building on top of the infrastructure relatively easy."

Woorank Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Founded in 2011, Woorank embraced microservices and containerization early on, so its core product, a tool that helps digital marketers improve their websites' visibility on the internet, consists of 50 applications developed and maintained by a technical team of 12. For two years, the infrastructure ran smoothly on Mesos, but "there were still lots of our own libraries that we had to roll and applications that we had to bring in, so it was very cumbersome for us as a small team to keep those things alive and to update them," says CTO/Cofounder Nils De Moor. So he began looking for a new solution with more automation and self-healing built in, that would better suit the company's human resources.

Yahoo! Japan

Mon, 01 Jan 0001 00:00:00 +0000

Zalando Case Study

Mon, 01 Jan 0001 00:00:00 +0000

Challenge

Zalando, Europe's leading online fashion platform, has experienced exponential growth since it was founded in 2008. In 2015, with plans to further expand its original e-commerce site to include new services and products, Zalando embarked on a radical transformation resulting in autonomous self-organizing teams. This change requires an infrastructure that could scale with the growth of the engineering organization. Zalando's technology department began rewriting its applications to be cloud-ready and started moving its infrastructure from on-premise data centers to the cloud. While orchestration wasn't immediately considered, as teams migrated to Amazon Web Services (AWS): "We saw the pain teams were having with infrastructure and Cloud Formation on AWS," says Henning Jacobs, Head of Developer Productivity. "There's still too much operational overhead for the teams and compliance. " To provide better support, cluster management was brought into play.