Artificial intelligence (AI) technology is being rapidly incorporated into a wide range of software products and services. The ability of AI and machine learning (ML) tools to quickly ingest and analyze large volumes of data has enabled the technology to be used in solutions as varied as personal assistants, autonomous chatbots, financial fraud detection systems, and industrial processes. The drive to leverage the power of AI in corporate and consumer products shows no signs of slowing down anytime soon.
Most IT professionals interact with AI solutions daily to streamline various aspects of their work. However, many IT operations and management processes can be optimized with AI. AIOps is the inclusion of AI into IT operations, and it can have a dramatic effect on a company’s ability to manage its computing environment efficiently.
What is AIOps?
AIOps utilizes advanced analytics, machine learning, and automation to monitor, analyze, and optimize IT operations at scale. AIOps solutions can collect and process vast amounts of operational data more quickly and accurately than human IT team members. Companies that adopt an AIOps mindset and implement the appropriate tools can shift IT management’s focus from reactive issue resolution to a more proactive, predictive approach.
An AIOps platform makes more efficient use of the data that is already available to IT support teams. A platform relies on the veracity and volume of operational data it can access. Effective AIOps tools ingest and correlate data from multiple sources for a variety of purposes, including:
- Providing baseline performance and capacity data with infrastructure metrics such as CPU and memory utilization, server and virtual machine health, and hardware telemetry;
- Associating infrastructure performance with the user experience with application metrics like throughput, response time, and error rates;
- Obtaining details and contextual information from application, system, security, and audit logs;
- Supporting accurate impact analysis with infrastructure configuration, such as network topology and cloud service relationships;
- Correlating monitoring alerts, system events, and capacity threshold transgressions into actionable actions;
- Investigating root cause analysis with distributed traces on service dependencies or latency issues;
- Linking incidents to recent changes by reviewing patching data and configuration updates;
- Learning through historical ticket and incident data for more effective anomaly detection, predictive analysis, and automated problem resolution.
Primary AIOps Capabilities
AIOps platforms typically offer the following key capabilities that help teams optimize and streamline IT management.
- Data ingestion and normalization are the key to effective AIOps performance. As previously noted, the platform collects data from multiple sources, which may provide information in different formats. The AIOps tool normalizes and unifies the data into a common schema, a prerequisite that allows the solution to support additional functionality.
- The platform correlates events across systems and takes actions such as deduplicating alerts and grouping related issues into a single operational incident. This ability identifies the issues that need immediate attention and minimizes alert fatigue.
- AIOps tools that have been well trained on baseline and historical incident data can detect deviations from accepted behavior in real time. These solutions can identify anomalies and proactively address issues before they disrupt the IT environment.
- AIOps platforms perform predictive analytics on various infrastructure elements to support planning and proactive operations. For example, the system can provide information regarding impending component failure or breached capacity limits before they impact operational efficiency.
- AI tools support faster, more efficient root cause analysis by automatically tracing incidents across the entire infrastructure to identify the true source of an IT incident. The platform can significantly reduce the time an IT team needs to resolve an issue.
- An effective AIOps tool reduces downtime and manual intervention by performing self-healing activities to address emerging issues. The platform autonomously triggers scripts and workflows designed to resolve known issues before they affect operations.
- The inclusion of ML technology supports continual learning and adaptation, optimizing the platform over time. The platform learns from historical incidents and adapts to infrastructure changes for greater predictive and actionable accuracy.
- AIOps platforms also leverage learning and adaptation to develop business-impact awareness, enabling them to prioritize incidents based on their business-criticality. This awareness helps the tool and IT teams concentrate on fixing the issues most impactful to business objectives.
What are the Business Benefits of AIOps?
Organizations that adopt an AIOps approach to IT management stand to reap substantial benefits that directly affect their IT operations and business bottom lines. Companies can expect to enjoy the following benefits from AIOps.
Minimized downtime
Companies protect revenue streams by reducing outages and downtime with AI and ML operational tools. Fewer, shorter outages increase availability, leading to greater customer satisfaction and enhanced brand trust. The predictive capabilities of AIOps can proactively modify application and system capacity to address peak usage. Providers can offer their customers stronger SLAs by leveraging AIOps capabilities.
Lower operational costs
AIOps typically results in fewer manual interventions and reduces the need for large IT support teams. The tools can improve engineer productivity by prioritizing incidents and automating repetitive, time-consuming tasks. Companies can better leverage their IT staff to deliver value-added activities that drive business growth.
Improved resilience and business continuity
The reduced downtime and faster problem resolution possible with AIOps provide enhanced resilience and support business continuity. Predictive identification of failing components enables proactive action before they impact operations. Automated incident response and continuous learning reduce operational risks.
Enhanced IT decision making
The information available from AIOps platforms enables IT leaders and teams to make more informed financial and capacity-planning decisions. The AIOps platform can identify approaching capacity shortages and underutilized resources for more efficient infrastructure planning. Companies can budget more efficiently by eliminating unexpected IT expenses.
VAST Supports AIOps for Improved IT Management
VAST’s experienced technical teams are continually seeking advanced tools and solutions that support our customers’ business goals. Our partnerships with industry-leading technology providers give us a perspective on emerging products, such as AIOps platforms, that can help us manage your IT environment more effectively and efficiently. Contact us to learn how we can help transform and manage your infrastructure using the most effective tools available.
