Artificial Intelligence for IT Operations

artificial intelligence Mississauga

Artificial Intelligence for IT Operations

Artificial intelligence has taken a pledge to take the heavy duty work of enterprises on its shoulders. It holds an incredible ability to make business operations more efficient and profitable by automating various tasks. Today it also handles the work of the information technology departments of IT companies Mississauga as well.

How artificial intelligence help streamline and improve IT service?

AIOps stands for Artificial Intelligence in IT Operations. The concept of automation of the IT functions has witnessed many developments since years starting from a job scheduling system at the 90s to self healing system. Presently IT automation is identified by many names like autonomous system, self driving system or bots. The majority of it is termed as AI Ops participating in the family of XOPs methodologies. Assuring to utilize AI and machine learning to standardize, mechanize and automate the IT services Mississauga.

In a survey, initiated with almost 200 IT managers who are experienced in working with AIOps tools said that AI has helped them in handling their IT department efficiently. Another survey released by OPsRamp revealed that 87% believes that AIOs tools are adding value to the IT operations of their businesses. It also showed another side of the AIOps tools which are holding back the progress.

Issues encountered in AIOps initiative

1. Reliable data sets

The biggest issue with AI and Machine learning is creating reliable data sets and finding the right person to turn AI and AIOPs into a reality. According to more than two thirds of the AIOps users, it’s taking time to build trust in the relevance and reliability of AIOps recommendations. The IT team makes the final conclusion for performance optimization after combining the data driven insights with human judgment.

2. Skillset for data scientists

Almost 64 % of IT managers stated that they do not find sufficient skills to make AIOps a reality. The survey also added that most of the enterprises spend more than six to 12 months to appoint an efficient data scientist and analytics professionals. For some the search operation lasts for even more than a year. In the long run, AIOps, supposedly should trim down the list of skills needed to run data centers. For now, it is vital for the IT team to achieve expertise in machine learning techniques and mix them with incident analysis skills to help AIOps operation.

3. Control

Just like any other newly introduced technology, loss of control is another major concern of the IT professionals. The biggest question here is whether the IT managers are prepared to hand over the complete control to self driving autonomous systems that offer actionable insights for problem diagnosis, troubleshooting, and recovery and the answer is no.

The survey has also shown the positive side of AIOps which says there are some visible benefits surfacing especially on the operational part.

Here are the top five use cases of AIOps tools

1. Intelligent alerting

AIOPs tools send contextual alert notifications with the help of which DevOps teams get information about event history, streamline event collaboration, and meet service-level needs for problem resolution

2. Root cause analysis

AIOPs also guarantees a better service uptime and dependability with quick problem detection that merges impact visibility and service context to establish the cause and effect of operational issues.

3. Threat detection

Machine language algorithms are capable of quickly detecting outliers through pattern recognition so that IT teams can receive signals noise and spot events that are different from the regular system behavior.”

4. Capacity optimization

The heart of an IT management system is the ability to handle system resources. AI and machine language are helping to do so across various cloud and on promises system as required.

5. Incident auto-remediation

The survey discovered two in five respondents were capable of significantly speeding up the time to remediate incidents and one in ten was able to reduce overall incident resolution times by almost half.

The above-mentioned use cases and benefits of AIOps thus far relate to improving the performance and delivery of IT services from an internal standpoint. While it is still not apt for business benefits yet, it nevertheless will potentially strengthen IT goal to play the role of a business within a business, offering better customer service and customer experiences while keeping expenses low.