Shulou(Shulou.com)06/02 Report--

With the development of technology, cloud computing technology continues to progress, and its purpose is also changing. In the current new normal, there are five main cloud computing elements, which are critical for organizations that want to remain competitive and relevant: cloud native applications, deploying multi-cloud strategies, integrating mobile applications into the cloud, building viable data lakes, and democratizing the use of data. These analytical tools are essential to help industry sectors become artificial intelligence-driven enterprises. Artificial intelligence is not only a technology, but also a change of business model that can not be ignored.

Research firm Gartner points out that 80% of internally deployed development software now supports cloud computing or cloud native, and the growing cloud computing ecosystem enables enterprises to operate faster, more flexibly, and in more real time, creating competitive pressure. Accepting cloud native and multi-cloud approaches as the new normal means that enterprises can avoid lock-in by cloud computing vendors and provide a response rate of more than five nines (99.999%) to avoid an average loss of millions of dollars per downtime.

Since 68% of organizations have developed or are implementing digital transformation strategies, the vast majority of organizations regard cloud computing as an important part of their change strategies. so the debate about the term "digital transformation" continues, because the nature of what companies have to do is always in the cloud. In short, companies need to embrace these five major cloud computing elements in order to remain relevant in the intense digital space of all industries.

In addition, the three artificial intelligence technologies that are crucial to enterprises in 2019 are vision, language and dialogue. Industry leaders need to leverage these services in their own environments, introduce artificial intelligence in cloud computing into existing applications, and enable companies to use data science that is in short supply. Therefore, having a viable data lake and tagging and receiving data in the right way is more effective than simply investing in analytical services.

Cloudy clouds drive digital transformation

A recent study by the Cloud Computing Industry Forum (CIF) found that organizations are more open to multi-cloud environments, and 3/4 of organizations use a variety of cloud computing services to drive their digital transformation. Business managers finally realize that locking in cloud computing vendors hinders the creativity, availability, and mobility of a multi-cloud approach.

More and more enterprises are using hybrid and multi-cloud environments from large vendors such as AWS, Google, Microsoft Azure, and so on. Cloud providers have also encouraged this trend by creating managed versions of open source stacks such as Apache Kafka for some features. This makes it easier to move from one cloud platform to another, which is the key to avoiding vendor locking while still allowing enterprises to focus on digital transformation.

The standardization of cloud computing means that multi-cloud provides enterprises with more cost-effective services to run workloads, and the cloud service prices of cloud computing service providers often change. For enterprises with critical workloads and cloud experiences, multi-cloud can improve uptime and competitiveness.

Companies can maximize IT spending through a multi-cloud strategy, because the standardization of cloud native technologies allows enterprises to use the right cloud computing vendors to get the right products. For example, microservices implement event-driven extensions (such as Black Friday) through containerization (such as Docker) and orchestration (such as Kubernetes). Ultra-large-scale configuration through cloud computing infrastructure, such as thin clients (web applications, native mobile applications, Alexa skills), which use multiple micro services, provide strong resilience and flexibility, and self-healing capabilities and design. Container orchestration, combined with cloud computing provider structures and regional functions, helps to withstand some cloud disruptions.

Will native applications die?

Migrating native mobile applications to the cloud is also critical to achieving the Internet of things (IoT), artificial intelligence, and virtual reality, which means native applications need to be synchronized. If it is not part of the cloud computing portfolio, the cost of migrating applications can be high. Finally, there is a need to create a viable data lake to manage information in a pragmatic manner and avoid turning it into a swamp, which is critical to maintaining a competitive advantage when introducing artificial intelligence and machine learning (ML) into the data science tool portfolio. So for companies to remain relevant, they must accept artificial intelligence because it is not just a technology; it is a business model shift that cannot be ignored.

These cloud computing trends will continue to play a role in the enterprise's digital transformation strategy and will help become an artificial intelligence-driven business, including an in-depth understanding of how the role of applications, data, analytics, and identity management will drive enterprises to improve efficiency and compliance.

Create feasible data lakes

In the past five years, the number of Internet users has increased by more than 82%, while research firm Gartner expects data to grow by 800% by 2022, 80% of which is unstructured data.

As enterprises continue to deploy cloud services, 2019 is critical for enterprises to build available data lakes in their organizations. Enterprises can add a set of intelligently discoverable metadata tag data to all systems, devices, and services to extract value from the large amounts of structured and unstructured data generated every day. will enable them to run analytics, business intelligence, machine learning and artificial intelligence, and gain important insights into new efficiencies to gain a competitive advantage.

Compared with traditional data warehouse methods, a key principle of the data lake architecture is to provide a place to place all the original data without conversion or loss, so that any conversion to the data can be replayed at will. The challenge for this approach in enterprises is to maintain a level of control over data landings so that quantity and accuracy do not become too large or become data swamps.

By leveraging the Lambda architecture, enterprises can reap the benefits of using streaming data in near real time, and important events can be seen almost immediately. This is a major step forward compared with the traditional data warehouse method, which has to wait 24 hours. Then, enterprises need practical methods to understand data, such as storing taxonomies, managing data workloads through classification (for example, data security and who has access), and data science tools. to help data scientists create / apply good equations to data pools to improve future analysis.

Realize the democratization of data science

Artificial intelligence is a change of business model that can not be ignored. In 2018, artificial intelligence and machine learning began to gain more appeal, especially when dealing with structured and unstructured data to help companies make intelligent decisions and identify trends. Today, cloud computing artificial intelligence can provide large-scale intelligent functions, scanning a large number of images, audio, video or text files to track patterns and anomalies. The level of operation of some artificial intelligence could not have been achieved even two years ago and would produce unparalleled commercial value. Nowadays, people are increasingly aware of how cloud computing artificial intelligence will revolutionize the business model in the cloud native ecosystem.

In 2019, more and more enterprises incorporate artificial intelligence into their digital strategies. The biggest gain will be to use cloud computing artificial intelligence to replace human beings to accomplish more trivial tasks, and to apply the level of intelligence to basic business processes. For example, artificial intelligence chatbots can answer 80% of repetitive questions in contact centers, allowing staff to deal with more complex and important issues. These smart tools eliminate administrative burdens while providing a higher level of customer experience.

Industrial Internet, as big as it is, nourishes more emerging projects and applications under the advocacy of the three new strategies of "new policies, new technologies and new ideas", and plays a booster role in the transformation of traditional industries and Internet industries. During the 2019 Global New economy Annual meeting, an Industrial Internet Summit is hereby set up to analyze the intelligent development of IT services from a global perspective. First-tier enterprises at home and abroad are invited to share the development process and future trend of the industry.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.