Cutting edge technology

Open source software, AI... What are the highlights of IDC i

Introduction: In 2019, many organizations will invest in open source software, manage IoT devices, integrate artificial intelligence and machine learning into business operations, and prepare for new microprocessor designs.

In 2019, many organizations will invest in open source software, manage IoT devices, integrate artificial intelligence and machine learning into business operations, and prepare for new microprocessor designs.

The following are major trends in data centers that can help business managers create faster, more responsive, automated, and easier to maintain:

1. Industry giants invest in open source software

Traditionally, vendors have built proprietary hardware and software for their customers, but open source products are gaining attention in areas such as operations. With open source software, organizations can use the applications they need at a lower cost and with greater interoperability. The help of the open source community will also make it easier to mix and match open source products than proprietary systems, so data center managers can configure the software they need directly.

Two large commercial transactions reached in 2018 indicate that industry giants have increased their investment in open source. In June 2018, Microsoft invested $7.5 billion to acquire Github, an open source software development platform with 28 million developers registered. This transaction provides an easier way for organizations' developers and managers to manage, share and refine the code within their organization.

The largest open source acquisition in 2018 was IBM's acquisition of Linux developer Red Hat for $34 billion in October 2018. The main purpose of the transaction is to help IBM gain more momentum in the cloud computing market and strengthen its open source cloud support for customers.

Matthew Kimball, senior technical analyst at Moor Insights&Strategy Data Center, said: "IBM has paid a high price for the acquisition of Red Hat because they understand that they need new solutions for those who don't pay much attention to traditional solutions. Developers and IT departments provide products and services."

Increasing interest in open source means that data center managers should look at what open source software they can use in their data centers and which communities they can rely on in the future. system.

2. Adopting more artificial intelligence technology

Artificial intelligence is one of the trends in changing data center maintenance operations, especially artificial intelligence (AIOps) for IT operations. AIOps software combines big data, artificial intelligence, machine learning, visualization and more to simplify the processing of daily monitoring and management tasks.

Typically, automated techniques are used to offload routine tasks (such as generating alerts) from workers to machines. AIOP will further advance this process, providing greater accuracy than humans and simplifying the interaction between different data center management groups.

These tools collect data from log files, metrics, tickets, monitoring tools, and check how tasks are performed, identify patterns or anomalies, and then decide how to handle various tasks, such as identifying and blocking possible attempts to invade User of the corporate network.

Vendors such as CA Technologies, Loom Systems, and ScienceLogic believe this can simplify AIOps deployment. Research firm Gartner expects the use of these tools to increase over the next three years. The company estimates that only 5% of large IT departments currently use the AIOps platform, but by 2022 this percentage will reach 40%.

3. Server microprocessors are still an important trend for IDC

As enterprises deploy new compute-intensive workloads such as big data, artificial intelligence, machine learning, they need new computing processing hardware, while traditional CPU-based The server design is difficult to support these workloads.

The graphics processing unit continues to receive attention, and Google is developing a tensor processing unit (TPU). There are other alternative processors for new high volume applications. For example, ARM-based processors are expected to be available in 2019. This means that if hardware performance issues arise, IT managers must be able to troubleshoot multiple types of microprocessors, not just Intel-based processing systems.

4. Data center devices are more intelligent

Enterprises can use hardware such as smart sensors to distribute devices and data to the edge of the network. However, organizations don't want to create more networks by sending alerts from these locations and devices to the central service.flow.

According to Gartner, vendors are adding artificial intelligence and software control capabilities to their hardware and software products to better manage this process. Data center personnel must be able to manage collaboration between autonomous devices and keep the hardware up and running.

As organizations develop their edge computing and connected device infrastructure, IT managers need to study network bandwidth standards and software to ensure their environment can effectively support all connected devices with the right bandwidth and monitoring capabilities.

5. Help desks become smarter

Today, help desk software becomes smarter and the process uses more automation than ever before. Emerging technologies such as artificial intelligence, machine learning, and natural language processing are laying the foundation for the application of chat bots that understand customer issues and automatically provide solutions.

Chatbots can solve the basic problems that users ask of the organization's staff, enabling staff to focus on more complex support issues. In 2019, many companies are working hard to make these robots understand and respond to customer emotions through text and visual indicators.

These applications can find specific words or facial expressions from the video stream and evaluate the outcome of the problem. If the user is not satisfied with the results, the chat bot can direct these customers to the staff for processing, rather than letting the customer continue to use the automated system. The overall goal is to enable data center support staff to offload these routine tasks while providing customers with more substantial customer service.