To date, AIOps has been a solution first and foremost for IT operations teams. In other words, AIOps has been used primarily to help IT teams manage what happens in the post-deployment part of a CI/CD pipeline, when they need to detect and remediate issues in production environments. That doesn’t mean, however, that AIOps leaves developers out of the picture. Although the conversation surrounding AIOps hasn’t paid a lot of heed to developers so far, it’s perhaps time to change that.

According to a public sector survey of federal employees, some useful insights were discovered.

In recent years, the adoption of artificial intelligence is on the rise. Different sectors of service providers are witnessing a massive integration of AI within their workflow. This singular action has given birth to a better work pattern and greater service delivery. This is because artificial intelligence is changing the narrative and dictating the pathway for the future of work.

The security stack is a crucial part of any company’s IT infrastructure. However, Security teams increasingly report that traditional SIEM solution approaches are “costly, complex, and resource-consuming,” according to a recent ESG survey. Fortunately, there has been significant innovation in how firms approach cybersecurity with new cloud-native technologies stack and breaking free from vendor lock-in and giving themselves more flexibility, cost advantage, and future-proofing.

Modern workflows are primarily aimed at one thing—reducing operational complexities so that stakeholders can focus on initiatives that boost business and innovation. For IT teams, Artificial Intelligence and Machine Learning play key roles in bringing this goal to life. And even though AIOps is considered to be not yet in mature stages, there is no denying that IT teams that do not adopt AI processes will be left behind. By 2023, the market for AIOps tools is predicted to reach $11.02 B.

As an idea conceived by Gartner four years ago, AIOps is already a mature practice. But it is also one that continues to evolve as businesses turn to AIOps to support new use cases, and as AIOps vendors build better and more efficient AIOps tools. That fact begs the questions: what’s next for AIOps? What are the relevant trends that will shape the future of AIOps over the next several years, and how will AIOps use cases evolve going forward?

With the ScienceLogic SL1 platform correlating and contextualizing data to generate actionable events that accurately reflect the issues that need attention, how do you make sure all your engineers and system admins are on the same page?

Artificial intelligence for IT operations (AIOps), although the new kid on the DevOps block, is here to stay. It’s the future of DevOps and the future is here with us now. AIOps is just the infusion of artificial intelligence to the practice of DevOps. This practice has shown that it’s of great value to a lot of software development firms. Firms that have already implemented AIOps have recorded a massive boost in overall IT productivity.

On your journey from reactive to proactive IT operations, you may be unsure where to start. If your organization is lacking visibility into your operations, that’s the best place to begin. Automation and artificial intelligence (AI) can help you gain that needed visibility. AIOps and visibility Artificial intelligence for IT operations (AIOps) offers numerous benefits, including faster response time, improved IT health, and simpler IT management.