What is the relationship between Linux and big data cloud computing?

1. Linux cloud computing is based on people's needs, from big data at a speed, easy way to find out the information people need. And find out the patterns between the related information, as well as the possible results of information changes.

2. From a technical point of view, the relationship between big data and cloud computing is as inseparable as the positive and negative sides of a coin. Big data cannot necessarily be processed by a single computer, and a distributed computing architecture must be adopted. It is characterized by the mining of massive amounts of data, but it must rely on the distributed processing, distributed database, cloud storage and virtualization technology of cloud computing.

3. The key word of Linux cloud computing is "integration", whether you are through the traditional virtual machine slicing technology that is now very mature, or through the massive node aggregation technology used by Google later, he is through the integration of massive server resources through the network, scheduling and distribution to users, so as to solve the problems caused by insufficient storage and computing resources.

4. Big data is a new topic brought about by the explosive growth of data, how to store the massive data generated in today's Internet era, how to effectively use and analyze these data, etc.

5. You can understand the relationship between the two in this way, cloud computing technology is a container, big data is the water stored in this container, and big data relies on cloud computing technology for storage and calculation.

The rapid development of the Internet industry has promoted the formation and rapid development of cloud computing and big data industries.

According to the research of the Linux Association, 86% of enterprises have used the Linux operating system for cloud computing and big data platform construction, and at present, Linux has begun to replace UNIX as the most popular cloud computing and big data platform operating system.

According to people's needs, Linux cloud computing can make it easier for people to find out the information they need from big data, and find out the laws between related information, as well as the possible results of information changes.

From a technical point of view, the relationship between big data and cloud computing is like the positive and negative sides of a coin, and there is an indistinguishable relationship. Big data cannot be processed by a single computer, and must be structured in a distributed computing structure. The characteristic is that the mining of massive data must rely on cloud computing distributed processing, distributed databases, cloud storage and virtualization technology.

What is the relationship between cloud computing and linux? Cloud computing and storage go over the internet to convert physical resources into usable shared resources.

While virtualization is not a new concept, relying on server virtualization to share physical systems makes cloud computing and storage more efficient and scalable, allowing users to access vast amounts of compute and storage resources without having to worry about their location and configuration.

Cloud computing technology is a container, and big data is the water stored in this container, and big data relies on cloud computing technology for storage and computing.

Open source projects such as OpenStack Docker KVM are all based on Linux systems, and domestic friends engaged in cloud computing development are inseparable from open source projects and transplant secondary development;

To learn cloud computing by yourself, you should also build a set of Linux system environment by yourself and test it slowly; If you are interested in development, if you have a programming foundation, you should compile the source code of the project by yourself and modify it yourself to participate in the development.

Cloud computing is a commercial, large-scale, distributed computing technology. In other words, users can automatically divide the required large computational processors into multiple smaller subroutines through the existing network, and then submit them to a larger system composed of multiple servers, search, calculate, analyze, and pass the results to the user. Basic cloud computing technologies are already ubiquitous in web services and are well known to us, such as search engines, webmails, etc.

Users can get a lot of information by simply entering a simple command.

If you want to learn cloud computing technology, you must learn Linux basics, Python automation, cloud computing, OpenStack, Docker containers, and other technologies. In cloud computing, the "cloud" is not only a source of information, but also a series of virtual computing resources that can be maintained and managed by themselves. Cloud computing centralizes all information and computing resources and is automatically managed by software without human intervention.

The user only needs to come up with the goal and leave all the transactional matters to the "cloud computing". It can be seen that cloud computing is not a pure product or a brand-new technology, but a new way to generate and acquire computing power.

Linux Cloud Computing Main Learning Content:

Stage 1 - Computer Network Fundamentals - Cloud Computing Networks, Computer Networks.

Phase 2: Linux Fundamentals - Linux Operating System, Linux Advanced Management, Linux Security and Monitoring.

Phase 3: Linux O&M Automation - Shell Script Programming, Python Basics, Python Advanced, Web Development Technology Practice, DevOps O&M Automation.

Phase 4: Database O&M Management - Database Management and O&M, Database Security and High Availability, and NoSQL Database Technology.

The fifth stage: enterprise-level cloud architecture management and comprehensive practice (PaaS+IaaS) - KVM virtualization technology, high-concurrency web platform architecture technology, large-scale cloud architecture deployment and management, docker container cluster construction and management, cloud architecture automatic configuration and monitoring.

Stage 6: Career Guidance.