AI and AIOps have been transforming the future of the workplace and IT operations, which accelerates digital transformations . The AIOps stands out as it uses machine learning (ML) and big data tracking, such as root cause analysis, event correlations, and outlier detection. According to the survey, large organizations have been solely relying on AIOps to track their performance. Thus, it is an exciting time for implementing AIOps that can help software engineers, DevOps teams, and other IT professionals to serve quality software and improve the effectiveness of IT operations for their companies.

Top AIOps Trends for 2023

AIOps empowers the changing digital transformation by accelerating the need of

Explainable AI

Explainable artificial intelligence (XAI) is a set of processes and methods that allow IT professionals to trust and comprehend the results and output created by ML algorithms. However, the black box conundrum is one of the main challenges that can prevent various industries from executing AI strategies. One of the industries that is facing such roadblocks is the banking industry.

Case Study

The emerging field of explaining AI (XAI) can help banking sectors navigate the issues of trust and transparency, providing great clarity on AI governance. Many banks are using XAI due to the increase in complex AI algorithms, which has made it critical to deploy advanced AI applications for facial and voice recognition, cybersecurity, and securities trading.

Auto-Remediation

Auto redemption is an approach to automation that responds to events with automation that fixes underlying conditions. It monitors the health of the system, can quickly add hardware to SDDC, and detects and prevents the workload of the cloud system from failing.

Case Study

Salesforce, a cloud-based software company, is a one-stop-shop integrated platform for businesses to connect sales, commerce, services, and many more. After thorough research, the Salesforce IT team uses Grafana's dashboards to manage and visualize the overall services and alerts, along with the product availability across the company. Frances Zhao-Perez, Senior Director of Product Management at Salesforce, said, “We leverage Grafana Labs' cloud-native solution to help us manage low-latency alerting and to help with auto-remediation and auto-scaling.”

Autonomous Operations

Autonomous operations are the future of smart IT and represent the last stage of the shift in autonomy. The main objective of AO is to minimize manual interaction and manage self-selected operations.

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