Taking a cue from other business functions, we know that Artificial Intelligence (AI) is capable of helping IT operations proactively respond to slowdowns and outages. Understandably, the interest in applying AI in IT Operations (AIOps) has grown with IDC predicting that 75% of organizations will switch over in the next few years.
Remote workforces : Most organizations have dealt with fractures in traditional systems and processes that enable remote work by now. But, without the support of AI-based automation, distributed environments are still a challenge for operations teams.
Data explosion : As applications churn out huge volumes of siloed data such as system logs or alerts, the inability to learn, gather larger volumes of data, and recommend solutions quickly hinders teams with traditional systems from quickly pinpointing signals and resolving incidents.
Digital transformation : As the use of containers and open cloud-native architectures rise in popularity, IT operations teams are forced to navigate the intricacies of a hybrid multicloud environment while maintaining consistent application performance – a feat that puts DevOps teams in a tight spot.
Business continuity : IT operations teams have long outgrown the basic need to keep the lights on. The business cost of downtimes and evolving IT environments clearly show that merely having a runbook is not enough anymore.
Your organization might have experienced some of these scenarios, possibly more, in the last year itself. And the simple solution is AIOps. With AIOps, your I&O teams can detect, resolve, and prevent issues at a scale that is beyond human ability.
Moving towards AIOps vendor consolidation
While AIOps is still in the early stages of adoption, the diverse solutions and platforms offered by vendors is calling attention to the need for consolidation. Here are four reasons why I think consolidation is necessary:
Cost of using multiple point products
While some solutions include a combination of application monitoring, resource or infrastructure monitoring, security analytics, or automation, most cater to specific use cases. A downside to choosing point products is the difficulty in integration as you navigate multiple vendors, contracts, and associated regulations.
Limitations of built-in monitoring solutions
Most applications, such as ERP systems, incorporate certain intelligent monitoring mechanisms that alert against potential errors and automate tasks based on rules. But the insights are limited and do not provide a complete picture for operations teams that have to restore a slow website or an application that is down.
Fragmented integration of AIOps solutions
With a domain-centric approach to monitoring applications, the data available for AIOps is fragmented, thereby reducing its effectiveness. For example, it can be labour-intensive and challenging to attempt a root cause analysis by correlating data from different monitoring tools across applications, networks, systems, and cloud environments.
AIOps can help DevOps teams by automating repetitive tasks and enhancing visibility across applications and environments. But organizations can experience scalability only when the solution integrates with existing toolchains, supports microservices architectures, and operates across hybrid environments.
Bringing multiple capabilities into one platform – Watson AIOps
IBM, which entered the AIOps space with Cloud Pak for Watson AIOps, now includes application performance management (APM) and application resource management (ARM) capabilities with the addition of Instana and Turbonomic. As part of IBM’s Cloud Automation portfolio, Watson AIOps offers a comprehensive platform recognized by Gartner in the domain-agnostic AIOps platforms category.
Embed video link (from Watson AIOps landing page)- https://mediacenter.ibm.com/id/#1_cra59ldh
Through a single platform you can leverage automation, observability, APM, ARM, hybrid and multicloud monitoring, and incident response. Using an application-centric approach, IBM’s AIOps solution integrates structured and unstructured data across an enterprise, helping you respond to events faster by delivering insights where you work.
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