However, managing such complex IT architectures is becoming increasingly difficult.
Heres everything you should probably know about AIOps and what it can do for your organization.
The challenges of modern IT
40% off TNW Conference!
More organizations are using cloud IT, and in many instances in conjunction with on-premise servers.
Many organizations use multiple clouds up to five.
You have on-prem environments, you havecloudenvironments.
It is much more complex than it used to be, Gupta says.
People have to understand that this is a way of augmenting their job.
The second trend is scale.
We have seen ten years of digitization in one year during the covid pandemic.
Organizations are moving to more digital experiences and more applications for getting work done.
There are a lot more applications in this hybrid cloud state, Gupta says.
Well, that is skills.
These trends are driving interest in automating the IT environment and getting help from AI.
AI and automation, which can be referred to as intelligent automation, are no longer nice-to-have.
This is where AIOps enters the picture.
Basically, AIOps helps IT staff do things that were impossible with their previous tools.
The first step to implementing AIOps is to collect quality information about your IT infrastructure and operations.
This first stage of AIOps is called observability.
AI-powered observability can lead to huge gains.
Consider ExaVault(acquired by Files.com), a company that provides file-transfer services to large organizations.
ExaVaults API receives 35,000 requests per minute and over 50 million calls per day.
As a result, they were able to track and resolve issues faster than before.
They reached 99.99-percent availability and reduced mean time to resolution (MTTR) by around 57%.
These are currently managed through smart guesses.
Another important aspect of AIOps is the optimization of IT resources.
Depending on your requirements, Turbonomic can automatically optimize your IT components or provide you with recommendations.
The benefits of AIOps can go beyond reducing IT costs and outages.
For example, BBC Studios used Turbonomic to manage its data pipe of more than 1,000 virtual machines.
Upon implementing Turbonomic, the BBC Studios team had a full-stack view of their environment.
Another challenge is finding the cause of failures and responding to them in a timely manner.
Fortunately, this is another area where AIOps can help.
Accordingly, it can provide recommendations on how to prevent such incidents.
Incident prediction is especially useful for organizations that are responsible for critical infrastructure.
NCHC used Cloud Pak for Watson AIOps to establish an AI-based automation system for predicting incidents and improving resilience.
For example, AIOps can help developer teams understand bottlenecks and the effects of failures in advance.
Several studies show AIOps are resulting in more clients coming to web applications, Gupta says.
Were going to see a huge amount of intelligence and AI brought to bear in managing IT systems.
We see an exciting road ahead with this evolution of using AI in IT.
