DevOps and AI have a fruitful relationship. Combining DevOps with AI plays an important role in how IT teams manage and deploy systems. Lets see how the integration of AI and DevOps makes DevOps a more powerful tool. Artificial Intelligence is used across several industries not only to stimulate production but also to improve the accuracy and efficiency.
As more organizations are willing to move to DevOps to achieve efficiency, faster delivery and reliability and IT strategies and operations are more complex one needs to have a sharp focus to monitor the critical events that arise in real time. AI is a smart technology that comes to rescue in such times to identify and troubleshoot such issues and also warn us beforehand about the upcoming issues.
AI is no more a luxury but an essential technology to handle the challenges in today’s IT operations. AI has the smartness of technology incorporated with human knowledge to build the breakthroughs that wouldn’t have been possible.
In IT, where agile is implemented and has become rather dynamic as a result of DevOps, the complexity is reduced by the process of AI. The good thing about AI is that it simplifies the identification of problems and help gain deeper insights, which would otherwise be difficult to find.
DevOps being intricate and the complexities arising are out of the human mind. Some of the operations such as pace and precision often need the help of the powerful essential AI tool. AI is a tool for identifying issues and helps in better decision making. AI helps to bridge the gap between the manual capabilities and DevOps applications. AI offers key advantages such as improved real time decision making, quick identification of the problem for fast troubleshooting.
With increase in the rise of machine and algorithm learning there also arises some very interesting data gravity challenges for IT operations team. Since IT organizations are shifting to the multi cloud tenancy, Machine learning and algorithm learning are used to build AI applications which are bound to add value to the DevOps pipeline.
Some of the biggest challenges in today’s IT operations is identifying the potentially harmful issues that creep into the large streams of Big Data.
AI and its impact on DevOps and IT operations
Artificial Intelligence (AI) was one of the technology that was talked about alot. But today AI is implemented everywhere in various industries. Blending the combination of AI and human knowledge, its possible to build breakthroughs which would otherwise not be practically possible.
AI’s Cognitive Insights
One of AI technologies very innovative breakthrough is applied across IT operations called Cognitive Insights (CI) which makes use of the MI algorithm to match the human mind knowledge such as social threads, open source repositories etc. With the information acquired from the CI forms, its possible to draw deep insights which provides solutions for many of the challenges faced in the DevOps culture on a regular basis. The information is stored in a pool or a data reservoir where it contains the relevant insights that are used to address a wide variety of problems by the IT and DevOps teams. DevOps team face several critical challenges that can be tackled with ease using by combining AI with log analysis. There exist many applications of Cognitive Insights, which includes:
Security
Some of the commonly occurring attacks like the Distributed Denial of Service (DDoS) are more common. Some unusual threats which used to be restricted to only public websites with bigger profile are now focusing on the SMEs and SMBs. Building a centralized logging architecture is essential to identify such potential threats to put a check to such malicious attacks. The anti- DDoS mitigation using cognitive insights has proven beneficial to restrict hackers from entering operations in future.
IT operations
Cognitive Insight(CI) helps to compile logs at a centralized point, which can monitor and keep a track of the entries logged in to improve the overall efficiency. With the onset of AI Cognitive Insight, its relatively easier to accurately pinpoint even minute potentially harmful threats that creep up into the log data. The concept of this program is based on the ELK stack for a broader view of the DevOps process by means of classification and data simplification.
AI integration helps achieve
With the help of AI driven log analytics systems, finding out issues and resolving them has become considerably easy. Implementing such systems will have a good impact on the operations of the organization. Integrating AI with log management helps yield some benefits including:
✔ Enhanced customer success
✔ East identification and Monitoring
✔ Lesser Risk reduction and resource optimization
✔ Improved efficiency by making logging data accessible.
Conclusion
AI based log analytics is an effective way to identify the issues and resolve them at the earliest which reduces the management burden and achieves better results. Cognitive Insights, AI integrations will be of immense help in the data log management and troubleshooting. They can accurately pinpoint to the specific issues from within the ousands of log entries which are otherwise very difficult to find and consume time and human efforts.