Remaining competitive in today’s competitive business environment depends on efficiency improvements. Enterprises rely on their IT infrastructure to improve efficiency and drive growth. But as the IT environment grows, it becomes complex and difficult to manage. Soon, IT becomes a major cost drainer and breeds inefficiency. Most enterprises struggle to optimise performance, troubleshoot issues, or secure their networks.

The limitations of traditional tools

Most enterprises have evolved organically and, in the process, create a complex maze of IT resources. They have an ever-proliferating infrastructure that includes decentralised data sources, microservers, containers, and more. These assets generate huge volumes of performance data and operational logs. Most of this data is in disparate silos, making integration and analysis challenging.

• Traditional network monitoring tools struggle to keep up with the scale and complexity of today’s IT environments. These tools lack:
• Capacity to process huge data volumes.  Analysing such large data volumes, coupled with the constant changes and the need for regular updates, overwhelms IT teams. 
• Ability to identify corrections and dependencies. Modern applications have numerous abstraction layers. Traditional tools cannot identify the specific underlying resources supporting any application. When issues emerge, identifying the root cause becomes difficult, delaying resolution.
• Automation capabilities to adapt fast to evolving infrastructure needs.
• Ability to overcome silos or integrate disparate data sources to offer complete visibility.

Enter AIOps

AIOps (Artificial Intelligence for IT Operations) rescue IT teams struggling with traditional tools.  

Research major Gartner coined the term ‘AI Ops’ to represent the new AI-driven approach. AIOps integrates artificial intelligence (AI), machine learning (ML) and big data analytics. The combo automates the most common IT tasks and resolves several issues with minimal human intervention. AIOps automates network monitoring, root cause analysis, event correlation, anomaly detection, and remediation. 

The right AIOps tools help businesses optimise performance, improve reliability, and drive innovation. 

Automating the mundane

Any IT team has to perform several mundane tasks that take most of their time but add little value. They cannot overlook these tasks, as they are essential to keeping the network running. Examples include updating security patches, log analysis, and provisioning resources for new users. Most of these tasks are routine and repetitive, requiring an army of expensive human technicians to execute. 

AIOps platforms use machine learning to automate these tasks. IT teams can predefine workflows and policies to automate responses to common issues. Tasks that consumed hours now execute in seconds. Still better, the process always takes place at the predetermined time, with precision. 

 The enterprise also saves on HR costs. Routine tasks on auto-pilot free up valuable time and resources for more strategic initiatives.

Proactive monitoring and anomaly detection

The key USP of AIOps platforms is their ability to analyse huge data volumes at scale. The analytics cover the entire infrastructure stack, including network servers, databases, and applications. AIOps uses AI to scan configurations, incidents, network traffic, and security events. Even social media traffic can come under its crosshairs. 

These tools identify patterns, anomalies, trends, and correlations faster than human operators. They also unearth insights that escape human observation. The IT team uses such actionable insights to uncover vulnerabilities. They can make timely interventions to boost performance, resource allocation, and security. 

IT operations have always been reactive, addressing issues after they occur. AIOps facilitates a paradigm shift to proactive management. It can identify problems and their underlying causes with speed and accuracy. The continuous analysis of data patterns and performance metrics leads to anomaly detection. The system identifies potential issues before they escalate into major problems. Incident resolutions also take place faster.

Another big impact area of AIOps is understanding correlations and dependencies. Most enterprises do not track dependencies or how all applications and systems work together. The lack of such information means they cannot understand how change in one place will impact the overall network. 

AIOps offer visibility into the dependencies within and outside the network. It correlates events and incidents. 

Consider a sudden increase in web traffic causing a spike in server CPU utilisation. Another possibility is an unexpected download starting in a critical server. A traditional monitoring system might trigger an alert but cannot determine the root cause. AIOps tools correlate multiple data sources. Next, it applies techniques such as anomaly detection, pattern detection and prediction analytics. Such an approach identifies the underlying root cause. 

AIOps analyses historical data to identify evolving patterns and trends. Such insights enable forecasting resource requirements and anticipating capacity issues. For instance, many e-commerce websites experience traffic spikes during the holiday season. The AIOps platform predicts when such spikes will occur. The tool goes further and provides additional resources to handle the increased load. IT teams can leverage such predictive analytics to scale resources and meet growing demands.

Automated insights and remediation

AIOps tools enable automated remediation of issues, reducing the need for manual intervention.  

In a traditional setup, the IT team scrambles for ad-hoc solutions. AIOps leverages advanced data analytics capabilities to remediate the issue. It may isolate the affected components., restart services, or reallocate resources.  

All these tasks take place automatically, reducing the time required for remediation. Today, cyber security is often a race between network security and cybercriminals. Both search for vulnerabilities in networks and applications, but with different objectives. AIOps-enabled speedy insights and resolution make a critical difference to network security.

But the biggest value addition AIOps brings is prioritisation. AIOps tools prioritise issues based on business impact. Consider an e-commerce website experiencing an outrage. AIOps tools prioritise restoring the customer interface of an e-commerce portal over the blog. 

Enhanced collaboration and knowledge sharing

Transparency and open information sharing are important for success in a digital ecosystem. But legacy systems, set up during a time when hoarding knowledge equated to power, often work against transparency. 

AIOps facilitates collaboration and knowledge sharing across IT teams. It integrates data from various disparate sources, overcoming silos in the way. Automatic tagging makes retrieval easy and efficient. Users get a single source of truth.

Optimised resource allocation 

AIOps platforms ensure seamless growth with optimal resource allocation. AIOps analyses historical resource use patterns and workload fluctuations to optimise resource allocation. The data-driven approach prevents overprovisioning of resources, leading to cost savings. 

All in all, AIOps represent a paradigm shift in how businesses manage and enhance their IT operations. Businesses benefit from reduced downtime, system reliability, improved productivity, and happy customers. 

AIOps is an approach. Enabling AIOps requires tools such as Dynatrace suited for the purpose. The AI-powered Dynatrace platform makes monitoring and securing the enterprise stack easy. It simplifies cloud complexity and breaks down silos to prevent issues before they escalate and impact end users. Enterprises using the Dynatrace platform reduce vulnerabilities by 95%. Their IT services become reliable and resilient, and innovation takes place faster.