1. Overview of Cloud Computing Technology Application System
Cloud computing technology is an Internet-based computing model that provides computing resources (such as servers, storage, databases, networks, software, etc.) as a service, enabling users to obtain and use these resources on demand without owning and Manage actual physical devices. Cloud computing technology has been widely used in various fields, including enterprises, scientific research institutions, governments, individuals, etc. The following is an overview of cloud computing technology application systems:
1. Infrastructure as a Service (IaaS) : This is the most basic level of cloud computing. It provides virtualized computing resources. Users can obtain virtual machines, storage space, network and other infrastructure through the cloud platform to build their own applications and Serve.
2. Platform as a Service (PaaS) : At this level, the cloud platform not only provides infrastructure, but also provides tools and platforms to develop, deploy and manage applications. Developers can use these platforms to build and host their own applications without having to worry about the underlying infrastructure.
3. Software as a Service (SaaS) : This is the highest level of cloud computing service. Users can directly use various applications that have been deployed on the cloud through the cloud platform, such as office software, customer relationship management systems, enterprise resource planning systems, etc. , no need to download and install.
4. Hybrid cloud and multi-cloud : Many organizations adopt hybrid cloud and multi-cloud strategies, combining different cloud services with their own IT infrastructure to meet different needs and improve flexibility and availability.
5. Big data processing : Cloud computing provides powerful computing and storage resources and can support large-scale data processing and analysis. Many enterprises and scientific research institutions use cloud computing to process massive amounts of data and perform data mining, machine learning and other tasks.
6. Auto-scaling : Cloud computing allows the scale of resources to be automatically adjusted according to demand, and computing resources can be automatically expanded or reduced according to changes in traffic and load, thereby improving efficiency and cost control.
7. Disaster recovery and backup : Many organizations use cloud platforms to establish disaster recovery and backup solutions to ensure data security and availability.
In general, cloud computing technology application systems cover a wide range of fields, providing users with more efficient, flexible and economical computing resources and services. It has become an integral part of modern information technology architecture.
2. Introduction to the Cloud Computing Technology Application Training Room
The cloud computing technology application training room is a practical operating environment for training and practicing cloud computing technology. This lab typically provides a range of cloud computing platforms, tools, and resources that allow students, developers, and professionals to learn and practice various aspects of cloud computing. The following is an introduction to a typical cloud computing technology application training room:
Hardware facilities : Training rooms are usually equipped with a certain number of computing servers, storage devices and network devices to simulate the infrastructure of a cloud computing environment. These devices can be used to build private clouds, virtualized environments and containerized clusters.
Virtualization technology : The training room may provide virtualization platforms, such as VMware, Microsoft Hyper-V, KVM, etc., so that students can learn and practice the creation, management and migration of virtual machines.
Container technology : Containerization has become an important way to deploy modern applications. The training room can provide Docker, Kubernetes and other container-related platforms and resources to help students master the use and management of containers.
Cloud platform : The training room can provide access to public cloud platforms (such as Amazon Web Services, Microsoft Azure, Google Cloud Platform, etc.), allowing students to practice creating virtual machines, storage, network settings, and application deployment in a real cloud environment and so on.
Practical projects : The training room usually designs some practical projects, ranging from basic cloud resource management to complex application deployment and big data processing. These projects help students apply theoretical knowledge to practical scenarios.
Security drill : The training room can simulate security vulnerabilities and attacks, allowing students to learn how to protect the security of the cloud environment, including practices in access control, data encryption, and vulnerability repair.
Experimental environment and monitoring : In order to facilitate students' practice, the training room usually provides an easy-to-use experimental environment, and may have monitoring tools to allow students to observe and understand resource usage and performance.
In general, the cloud computing technology application training room is a learning environment combining theory and practice, which helps students master cloud computing technology and provides them with valuable experience in applying cloud computing in practical work.
3. Composition of cloud computing technology application professional training room
3.1 Cloud computing technology application professional training platform
The platform adopts a B/S structure and uses spring cloud microservice technology to build multiple stable and efficient service modules, provide SSO single sign-on service, and use unified identity authentication. Based on k8s, the platform implements multiple deployment methods of public cloud, hybrid cloud, and private cloud. It adopts MySQL cluster and MongoDB cluster. It can provide KVM and containers according to teaching needs to meet the virtualization requirements of cloud computing teaching. It can also allocate CPU, Memory resources provide highly reliable, dynamically scalable, and extensive teaching services for teaching practice. The main modules include course creation tools, assignments, activities, cloud disks, shared courses, my courses, and cloud preferred courses.
Multi-architecture cloud hosts: Cloud hosts with X86 and ARM architectures can be provided. Cloud hosts with corresponding architectures can be configured for different users according to user needs to meet different user needs.
Multiple virtualization technologies: The bottom layer integrates two virtualization technologies, docker and openstack, giving users more choices. Different virtualization technologies can be selected according to different technical needs.
Automatic scheduling of platform resources: Through background resource monitoring, the platform automatically suspends the virtualized resources of users who are inactive within a specified period and restores them when they are in use, achieving elastic automatic scheduling of virtualized resources and using less hardware resources to meet the needs of users. The training needs of more students.
Convenient experiment production tools: Allow teachers to easily mix and arrange texts, pictures, audios, videos, hyperlinks, etc. in different formats such as pdf, ppt, word, and excel, and automatically generate dynamic experiment catalogs to achieve different cloud computing training Resources are displayed on the same screen.
Online Q&A to answer students’ questions in a timely manner: The platform provides online questions for experiments. During the training process, students can communicate with teachers in a timely manner through online Q&A to improve learning efficiency.
Command detection, real-time experiment progress: The platform automatically detects the commands entered by users during cloud computing training, and compares them with the experimental documents to realize the user's experimental progress for the experiment. Every time a command is entered, the platform It will be detected and then displayed on the experiment page in real time. The teacher's classroom page can also view the experimental progress of each cloud computing experiment of students, so as to control the overall learning progress of students.
Automatic generation of experiment reports: For users' experiment reports, the platform records the user's operations during operation of the cloud host, and then automatically generates an experiment report, which teachers can directly view and give corresponding ratings.
Classroom resource recycling: When users create a classroom for practical training, the platform will select the corresponding hardware configuration of the cloud host for each student, which will occupy the CPU resources and memory resources within the resource pool of the institution. When the practical training has completed At the end, users can release the corresponding CPU and memory resources through the classroom release resources, and the training data and records are still saved.
Experiment notes that can record learning situations: The cloud platform provides users with an experiment note function on the experiment page. Users can record their own notes during the experiment.
Supports public resource courses and is easy for teachers to use: the practical training module can be built with rich practical training resources, including practical training documents and experimental images, which users can use directly.
Personal cloud disk, resources will not be lost: The platform will provide users with cloud disk services. All files in the cloud disk will be separated according to different file types, making it easier for users to view and operate.
The platform supports experiments such as Linux, virtualization technology, OpenStack, docker, cloud platform, cloud data center construction and operation and maintenance, cloud storage product configuration, big data platform and big data analysis, and cloud security product configuration.
The platform supports integrated online software development environment, which can be used out of the box, reducing the trouble of users switching back and forth and improving user experience.
The platform can be seamlessly combined with practical modules such as teaching modules, examination modules, homework modules, skills competition modules, artificial intelligence, computer network simulation, Internet of Things, Web front-end, java and python development, etc. to complete the whole process of teaching.
3.2 Cloud computing technology application professional teaching cloud platform
The platform is based on the spring cloud microservice architecture, provides convenient SSO single sign-on, and uses kubernetes for deployment. It can support public cloud, hybrid cloud, and private cloud installation modes. The data layer uses MySQL cluster and MongoDB cluster to realize full-process EdvOps automation. Operation and maintenance has the characteristics of high cohesion, loose coupling, single business, high performance, high concurrency, high possibility, cross-platform, and cross-language. The main modules include course creation tools, cloud disks, shared courses, my courses, cloud preferred courses, cloud video library, and 3D model library.
Course production tools: The platform provides dedicated microservice modules for support, using websocket two-way communication technology, and the underlying storage adopts a three-layer progressive caching method in order to speed up the loading of course resources. Independently develop video transcoding and online video editing functions. It supports direct import from word documents and automatically generates a table of contents based on the title type, which is convenient and fast. At the same time, it supports the insertion of ppt, excel, pictures, hyperlinks, videos, audios, 3D models, chapter tests and other content to realize the same-screen display of multiple hypertext files.
Shared courses: Use the concept of order distribution or campus sharing to share course resources to a greater extent.
My Class: Supports "generating a copy" directly from shared class resources and importing them into My Class, and also supports self-creation. All course resources support the export function and can be exported to local offline files. The exported files are encrypted files with the suffix wz. The course resources can be directly generated by secondary import using the platform to facilitate online dissemination.
Cloud Selected Courses: Learning resources collected and organized on the Internet by senior industry practitioners, including a series of learning videos and knowledge point learning videos for teachers and students to learn independently.
Cloud video library: The platform provides hundreds of micro-lecture videos covering various majors, which can be directly referenced into course resources.
3D model library: Using three.js technology to load 3D models online, providing a more intuitive teaching experience.
The platform can be seamlessly combined with examination modules, homework modules, skills competition modules, artificial intelligence, cloud computing, big data, software development and other practical modules to fully complete the teaching of computer network professional groups.
3.3 Python basic teaching resource package
Chapter 1 Basic Grammar;
Chapter 2 Functions;
Chapter 3 File Operation;
Chapter 4 Exception Handling;
Chapter 5 Modules and Packages;
Chapter 6 Object Oriented;
Chapter 7 Network Programming;
Chapter 8 Regular Expressions;
Chapter 9 XML and Json.
3.4 Docker Getting Started and Practical Teaching Resource Package
Chapter 1 Docker and Containers;
Chapter 2 Core Concepts and Installation Configuration;
Chapter 3 Using Docker Images;
Chapter 4 Operating Docker Containers;
Chapter 5: Accessing the Docker repository;
Chapter 6 uses Dockerfile to create images;
Chapter 7 Using Docker API;
Chapter 8 Core Implementation Technology;
Chapter 9 Configure private warehouse;
Chapter 10 Security Protection and Configuration;
Chapter 11 Docker Machine;
Chapter 12 Docker Compose;
Chapter 13 Docker Swarm;
Chapter 14 Cluster Resource Scheduling Platform—Mesos;
Chapter 15: Production-grade container cluster platform—Kubernetes;
Chapter 16 Other related projects;
Chapter 17 Network Basic Configuration;
Chapter 18 Advanced Network Configuration.
3.5OpenStack Getting Started and Practical Teaching Resource Package
Chapter 1 The concept and development of cloud computing;
Chapter 2 CentOS basic environment configuration;
Chapter 3 Basic operations of data in MySQL database;
Chapter 4: Project development knowledge and skills training;
Chapter 5 OpenStack basic configuration;
Chapter 6 Installing OpenStack services;
Chapter 7 OpenStack daily operation and maintenance;
Chapter 8 Comprehensive Cases.
3.6 Software development training resource package
C language course; Web development basic course; Java programming course; SQLSERVER database course; JavaWeb application design course.
3.7 Cloud Computing Basic Training Resource Package
Practical training resources include:
Web design courses; Java programming courses; MySQL database courses; Linux network operating system courses; Python programming courses; JavaWeb application design courses; Cloud computing comprehensive operation and maintenance management courses; Cloud storage technology courses.
3.8 java programming resource package
Practical training resources include:
Experiment 1 Know Java;
Experiment 2 Java language foundation;
Experiment 3 Java operators;
Experiment 4 Java control statement;
Experiment 5 Java array;
Experiment 6 Java method;
Experiment 7 Java classes and objects;
Experiment 8 Java encapsulation and inheritance;
Experiment 9 Java polymorphism;
Experiment 10 singleton mode;
Experiment 11 string and packaging class;
Experiment 12 error handling;
Experiment 13 enumeration and generics;
Experiment 14 Java collection framework;
Experiment 15 java.io package - character stream;
Experiment 16 java.io package - byte stream;
Experiment 17 Know JDBC;
Experiment 18 JDBC Basics;
Experiment 19 JDBC interface;
Experiment 20 JDBC result set;
Experiment 21 JDBC data types and transactions;
Experiment 22 JDBC exception handling.
3.9 Linux operating system training resource package
Practical training resources include:
Experiment 1 Linux startup, login and exit;
Experiment 2: Practical training on common Linux commands;
Experiment 3: Be proficient in the use of vi editor;
Experiment 4 Linux package management;
Experiment 5 Understand the basic concepts of users and groups;
Experiment 6 Understand user configuration files and master user management commands;
Experiment 7: Understand group configuration files and master group management commands;
Experiment 8 Understand disk partitions and file systems;
Experiment 9 Disk quota management;
Experiment 10 Management of logical volumes LVM;
Experiment 11: Familiar with relevant network configuration files;
Experiment 12 Basic network configuration commands;
Experiment 13: Familiar with network test commands;
Experiment 14 Understand the principles of DHCP;
Experiment 15 Configure DHCP server;
Experiment 16 Configure DHCP client;
Experiment 17 Understand the domain name space and DNS principles;
Experiment 18 Install DNS software and understand DNS configuration files;
Experiment 19 DNS server configuration;
Experiment 20 Configure vsftpd server;
Experiment 21 Client accesses FTP server;
Experiment 22 Understand the working principles of WWW services and Web services;
3.10 MySQL training resource package
3.11 Python programming training resource package
Practical training resources include:
Experiment 1 Python overview;
Experiment 2 Python’s simple data types;
Experiment 3 python advanced data types;
Experiment 4 Python program structure;
Experiment 5 Python function;
Experiment 6 Python object-oriented;
Experiment 7 Python file operation;
Experiment 8 Python exceptions, debugging, and testing;
Experiment 9 Python network programming;
Experiment 10 Python regular expressions;
Experiment 11 XML and json.
4. Construction diagram of cloud computing technology application professional training room
5. Plan list of cloud computing technology application professional training room
6. The value of the professional training room program for cloud computing technology application
6.1 Professional teaching support
6.2 1+X authentication service
6.2.1 Cloud computing development and operation and maintenance 1+X certificate
6.2.2 Cloud Computing Application Development 1+X Certificate
6.3 Skills competition support
6.3.1 Cloud computing technology and application
7. Action plan for co-educating digital talents between schools and enterprises based on Huawei’s ecological ecosystem
