AI for better Cloud Operations

AI for better Cloud Operations

AI smoothen the way of adopting and maintaining cloud operations. IT operations have developed over time. DevOps has increased the performance quality and reduced the gap between engineers and IT operations. Did you know that the increasing use of the cloud is also increasing the complexity? To solve this problem, businesses are using a new way – AIOps. Developers keep employees to solve the complex and more recent problems while machines are doing the repetitive, known, and identifiable tasks. 

Four Areas to Use AI for efficient Cloud Ops

To manage the increasing adoption and complexity of the cloud, AI is automating the software building process. It helps to make decisions about known problems, predict issues, and send alerts. Can you guess in which areas of cloud AI is improving most? Have a look: 

1.      Manage Cost

Businesses prioritize cloud to optimize cost. But dynamic provisioning, the auto-scaling of support, and a lack of garbage collection for unused cloud resources, the expense is increasing. AI helps the IT Ops team to detect cost spikes and provide visibility into who used what. Thus it helps teams to deploy intelligent automation. It automatically reduces the cost of the power cycle of development instances by turning them off on the weekend.

2.      Ensure Security

AI ensures that every cloud resource is secure while meeting regulatory requirements. It uses real-time event configuration management data to reduce business risk. It can issue alerts within milliseconds and send them to the operation teams. If it can’t meet compliance, it automatically shut down machines.

3.      Reduce Noise

The increasing complexity of ITOps is addressing critical problems. Members find it difficult and time-consuming to manage and resolve them. Again most of the alerts are unnecessary and caused by unidentifiable patterns. AI and ML can filter out unnecessary and duplicate signals. Then it auto solves the identifiable alarms to minimize the noises.

4.      Automate operations

Machine intelligence and deep learning can create dynamic tools that can automate remediation actions and alert diagnostics. Thus teams can focus on their work of resolving problems. These remedies save hours after every deployment and help operators handle failures gracefully.

With the increasing use of the cloud, new challenges are introduced in the company. It is the perfect time for companies to adopt AI Ops and related technologies to ease infrastructure management.