Artificial intelligence has become a keen talking point in the IT industry, and for a good reason. The manual configuration and management of IT infrastructure is inefficient and expensive. This goes against the desired outcomes of digital transformation in the cloud, which include zero-downtime, expedited implementation, and effortless server scaling in line with business growth.
AI operations management (AIOps) aims to overcome these bottlenecks, using a mixture of artificial intelligence and machine learning to automate the management of your IT systems. It requires a strategic shift from siloed IT environments to a unified big data and analytics platform, which then fuels the automation of continuous integration and deployment functions (CI/CD) on your network.
AIOps has two main components as defined by Gartner, which are:
Big Data - With AIOps, big data is the vital source of constant information that machine learning and AI uses to predict and implement operational changes on your network. The bigger the dataset your AI has access to, the more effective it will become for managing your IT operations.
Artificial Intelligence and Machine Learning – AI and ML are the cornerstones of AIOps, complimenting your existing service and performance management procedures through intelligent system automation. These two are not meant to replace your existing IT staff. Instead, they are built to complement and augment your existing human intelligence, to raise the bar for IT operations management effectiveness against business objectives.
In simple terms, AIOps aims to bridge the performance gap between your human administrative capacity and digital transformations administrative demands in the cloud.
IT Operations Management Complexity – Modern cloud-native IT environments come with a range of infrastructure types, including the managed/unmanaged cloud, third party service integrations, Software-as-a-Service integrations, and more.
The dynamic nature of the cloud has outpaced traditional IT operations management procedures, making it near-impossible for humans to manage without the assistance of AI/ML. As your IT services become more complex, so do the administrative workloads that are vital for maintaining long-term performance and reliability of these systems.
AIOps aims to analyze and algorithmically manage your IT operations. Instead of your staff manually performing low-level tasks, you can build management frameworks in which the AI can take control. These already exist on popular public cloud platforms in the form of auto-scaling, but you can extend these functions to your niche software packages. As an example, you could automate the ingestion of raw data into databases, categorizing and tagging data in line with your specified parameters.
End-Users and Staff Are Intolerant of Downtime – The retroactive remediation of network issues is no longer acceptable in the modern cloud-native world. End-users will not tolerate service interruptions, and they will start to look elsewhere at the first signs of operational incompetence.
AIOps has the potential to allow your systems to self-heal, creating the illusion of service continuity for end-users despite server outages on your network. In the event of a potentially critical server failure, an AI would be performing continuous integration and delivery (CI/CD) operations in the background. It would see the sudden influx of system errors and start proactively spooling data to a new identical server instance. Within seconds or minutes, you will have a replica of your live server instance that is ready for fail-over if your live server stops functioning altogether. Simultaneously, the AI would operate within your designated management framework, attempting to remediate and avoid the outage in the first place automatically.
Trianz is a leading IT operations management consulting firm, with decades of experience helping our clients to implement meaningful IT operations management strategies in the cloud. We understand the looming potential of AI and machine learning as part of IT operations management, setting you up to be architecturally ready for new developments in this field.
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