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Accelerate & Automate Incident Recovery with AIOps

Automating incident recovery has inculcated rhythm to systems. But ITOps need more than automation. And, that is the acceleration of automated incident recovery. 79% reported in a survey that adding more IT staff to address IT incident management is not an effective strategy. Incident recovery needs accelerated intelligent automation. The two core outputs when accelerated are better and faster Incident Diagnosis and Resolution.

AIOps Has a Data(Ops) Problem

Modern complex systems are easy to develop and deploy but extremely difficult to observe. Their IT Ops data gets very messy. If you have ever worked with modern Ops teams, you will know this. There are multiple issues with data, from collection to processing to storage to getting proper insights at the right time. I will try to group and simplify them as much as possible and suggest possible solutions to do it right.

Let 'Data bots' do the hard work of making AIOps and DataOps effortless

For a long time, IT Ops teams have been trying to keep up with the advancements in data analytics and management. In certain organizations, this problem is charged to DataOps teams. .These teams are tasked with managing data growth and complexity as well as keeping pace with new technologies like Artificial Intelligence driven Ops (AIOps).

Keynote by Bojan Simic, DEJ | AIOps Virtual Conference | CloudFabrix

The AI market is projected to reach a $3 trillion mark by 2024, and machine learning, which is a big part of AI, is the key driver of that growth. Machine learning can augment human understanding in processing large and complex datasets that are typical in IT operations. With rapid advancements in AI/ML technologies, enterprise leaders are beginning to take big bets on AI.