IT operations are quite hectic for companies that provide multiple services including cloud services, on-site services, SaaS applications, and everything in between. IT companies tend to keep performing better and keep the stakeholders satisfied by meeting their expectations, but it is getting harder and harder with every passing day.
The volume of data generated by companies is skyrocketing and they need efficient operations to capture and analyze data to improve their business process. With this recent explosion in data volume, the number of experienced technical IT workers has brought the IT industry in an uncomfortable position.
According to asurveyconducted by Gartner, 63% of the executives mentioned that the shortage of skilled IT workers was becoming a problem for their company. By 2030, it isestimatedthat a shortage of more than a million IT and telecom professionals will affect the US. While a shortage of 756,000 skilled workers is expected in the next 18 months according to the European Commission.
So how will the IT industry tackle such a shortage of a large workforce? One solution which has the potential to save the IT operations industry that the experts are looking forward to isAIOps.
AIOps refers to the use ofartificial intelligencein information technology operations. This is done with the integration of machine learning (ML) anddata sciencealong with big data analytics to improve proficiency and to improve all basic IT operations.
These operations include but are not limited to identifying, troubleshooting, and resolving available and performance-related issues. AIOps was developed to keep the lights on and to make sure that the performance of applications and infrastructure keep on performing as expected. The article will focus on getting to know what AIOps is, how it works, its evolution, and direction.
AIOps are implemented as a software platform using cutting edge technologies like machine learning and data analytics in the areas of monitoring, automation, and service desk.
Monitoring is the first thing that comes into play when using AI with IT operations, monitoring is done by collecting data which was previously stored and aggregating it. Since the data is aggregated into a single file, it becomes easier for machine learning algorithms to access the network characteristics and perform better as compared to before.
Another ease that AIOps have provided IT operators is response automation. Usually, IT operators detect breaches using the KPI as metrics, what AIOps does is that it automates the tasks by having a predefined value of KPI set by the IT operator.
These KPI are of specific applications or servers and are defined by running a series of tests to determine acceptable thresholds of KPI or any other metric. Once breached, AIOps software starts an automated root cause analysis and implements a solution if available.
The third area that is most affected by AIOps is the service desk. Every IT organization has its incident management system at its core which is referred to as a service desk. When applied, AIOps software automates the responses to routine alerts, this in return reduces the time spent by IT operators on doing mundane low-level tasks.
