To solve the challenge faced by
IT operations and DevOps teams is to be able to identify potentially small harmful problems in a large number of log data streams, which is what cognitive insights do.
In the next few years, DevOps (the intersection of development software engineering, technical operations and quality assurance) teams and IT operations departments will face new challenges, but such a statement sounds unavoidable, because they are the most important The responsibility is to solve difficulties and overcome challenges.
With significant changes in processes, technologies and tools, it has become increasingly difficult to deal with these issues. In addition, enterprise users have been putting pressure on
DevOps and IT operations teams to require everything to be resolved by clicking on the application. However, in the background, dealing with these problems is completely different. Users cannot realize how difficult it is to find a problem, let alone solve it.
One of the biggest challenges facing the current IT operations and DevOps team is being able to accurately point out the small but potentially harmful issues recorded in the big data streams in their work environment. In other words, it's like finding a needle in the grass.
If you work in the IT department of a company that is online 24/7, the following scenario may sound familiar: you suddenly received a call in the middle of the night, perhaps an angry consumer, or perhaps due to an application The program crashes and your boss comes over due to a credit card transaction failure. At this time, you will immediately open your laptop, open the log management system, and then you will see that within the set time range, 100,000 messages have been It is recorded-it is impossible for a person to check these data one by one.
So, what would you do in such a situation?
It is a story that every IT operation and maintenance expert will face. They have spent many sleepless nights. They are sailing in the ocean of log entries, looking for the key points that trigger emergencies. This is where real-time, centralized log analysis comes into play. It can help these people figure out the fundamentals of the log data and accurately identify the main problems. Through it, the process of fault diagnosis becomes as simple and effective as a walk in the park, and experts can also predict future problems based on this.
Artificial intelligence and its impact on IT operation and maintenance and DevOps
Ten years ago,
artificial intelligence was still a hype concept, but now it has been widely used by people for various purposes in all walks of life. Combining big data, artificial intelligence and vertical domain knowledge, technical experts and scientists have been able to create amazing breakthroughs and opportunities, which were previously only seen in science fiction novels and movies.
As IT operations and maintenance become flexible, dynamic, and complex, the human brain can no longer keep up with the speed, volume, and diversity of large data streams, which makes artificial intelligence a powerful and important tool in the optimization analysis and decision-making process. . Artificial intelligence helps fill the gap between humans and big data, provides humans with the necessary operational intelligence and speed, and greatly reduces the burden of human troubleshooting and real-time decision-making.
What can AI do for you?
In all of the above cases, one thing is common. As the beginning of the discussion, these companies need a solution that can help IT operations and
DevOps teams quickly find the problem from the pile of log data entries. To identify the log entry that adds trouble to your work environment and crashes the application, is it too simple if you just know what type of error has occurred in your log data? Of course it will also reduce some workload.
One solution is to build a platform through which you can collect various relevant data from the Internet, observe how people use similar devices to solve problems that occur in their systems, and scan your system to identify potential problems . One way to achieve this goal is to build a system that simulates how users investigate, monitor, and resolve events and allows it to underestimate the way humans interact with data rather than analyzing the data itself. For example, this technology can be similar to Amazon's product recommendation system and Google's PageRank algorithm, but this one focuses on log data.
Introduce cognitive insight
The latest technology to achieve the solution envisaged in this article, this recently caused a great reaction is called cognitive insight. This groundbreaking technology that uses machine learning algorithms can match domain knowledge with log data, open source repositories, discussion forums, and social threads. Combining all this information, the IT operations and DevOps team may obtain relevant insights from the data, which may contain solutions to key issues.
Real-time obstacles
DevOps engineers, IT operations managers, chief technology officers, deputy chief engineers, and chief information security officers all face many challenges, but by integrating artificial intelligence into log analysis and related operation and maintenance processes, the pressure caused by these challenges can be effectively alleviated . Let's cite two main use cases:
Security
Distributed denial of service (DDoS) attacks are becoming more and more common. In the past, targets were limited to governments, well-known websites and multinational organizations, but now they are generally starting to target celebrities, small and medium-sized enterprises and medium-sized enterprises.
To avoid such attacks, it is necessary to have a centralized architecture to identify suspicious activity and accurately identify potential threats from thousands of data entries. Therefore, resisting DDoS attacks through cognitive insight has proven to be very effective. In the past, leading companies such as Dyn and British Airways continued to be attacked by DDoS, but now, there is a mature, ELK-based anti-DDoS attack strategy to prevent hackers ’actions and to ensure that their operations are safe. Subject to future attacks.
IT operation and maintenance
After all the entries in all your logs have been carefully checked and registered, would n’t it be great to compile them into a single place? Well, it is. You will be able to clearly view the process table and query log data from different applications in the same place, which will greatly improve the efficiency of your IT operations.
To solve the challenge faced by IT operations and DevOps teams is to be able to identify potentially small harmful problems in a large number of log data streams, which is what cognitive insights do. Because the core of this program is based on the ELK stack, it can classify and simplify the data, and can easily describe your IT operation and maintenance clearly.
Integrated artificial intelligence can bring benefits
Using AI-driven log analysis system makes finding needles in weeds very easy and efficient. Such a system will have a huge impact on the management and operation of the entire organization. Like the company's problem discussed above, integrating AI with a log management system will benefit from the following:
Improve customer success rate
Monitoring and customer support
Reducing risks and optimizing resources
Maximize log data access efficiency
In other words, cognitive insight and other similar systems are of great help in data log management and troubleshooting. Rent-A-Center (RAC) is a Fortune 1000 company headquartered in Texas, which provides a variety of rental products and services. It has more than 3,000 stores and 2,000 kiosks in Mexico, Puerto Rico, Canada and the United States. The company tried to integrate two different ELK stacks, but it was too much trouble to process 100GB of data every day, not to mention the daily disk management and memory. High costs and time costs on calls, additional data entry functions and other technical issues. Later RAC turned to using cognitive insight, so they were able to detect future anomalies and enable them to easily expand the growing data volume. They are the ones that benefit from this dedicated IT team that manages the internal and external ELK stacks.
The role of open source in data log management
Many well-known suppliers are actively researching and testing artificial intelligence to improve the efficiency of the log data management system. Some suppliers are as follows:
There is no doubt that ELK is quickly becoming a trend, and more and more vendors are providing logging solutions. This is because it has become a good way for companies to avoid the huge upfront costs and install the necessary programs. It also has some basic drawing and search functions, and in order for organizations to recognize the problems in their log data, they will choose the latest technology such as cognitive insight to quickly find the "needle" and eliminate the main problem.
