There is no future of IT operations that does not include AIOps. This is due to the rapid growth in data volumes and pace of change (exemplified by rate of application delivery and event-driven business models) that cannot wait on humans to derive insights.
~ 2021 Gartner Market Guide for AIOps
The pandemic-led digital transformation is ramping up the need for AIOps as more business operations are digitized. After all, analyzing the growing quantum of IT data becomes critical yet impossible for the human eye to achieve.
Moreover, the complexity and diversity of today’s componentized IT environment often result in the deployment of multiple management tools, making it challenging to maintain a coherent view of the entire IT infrastructure.
Additionally, in today’s times, organizations can no longer afford the luxury of responding to IT issues after they occur. Instead, a proactive approach to IT operations management (ITOM) is needed to remediate problems before they disrupt entire business operations.
Enter AIOps – The infusion of artificial intelligence in IT Operations that “combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.”
Indeed, in the wake of a difficult-to-monitor IT landscape and the need for faster, smarter resolutions, the demand for AIOps has grown enormously. Several vendors are popping up with new AIOps solutions almost every day. In fact, “AIOps continues its growth and influence on the overall ITOM market, with an estimated market size of between $900 million and $1.5 billion in 2020 and a compound annual growth rate of around 15% between 2020 and 2025.”
However, as a first step, it’s crucial to evaluate the product to help you make intelligent investment decisions.
Below, we have compiled a list of the three features to look for when considering an AIOps solution.
Consider these 3 capabilities as the AIOPs solution.
1. Automation across IT operations
AIOps offers various use cases and benefits that simplify ITOM, improve key metrics like MTTR, MTBF, MTTF, MTTA, etc., and help businesses survive and thrive in an increasingly digitized landscape. Therefore, when considering an AIOps solution for your organization, it’s crucial to look at the functionalities the solution offers.
Some of these use cases include –
- Anomaly detection – AIOps can help secure the IT infrastructure by sifting out scripts, botnets, and other anomalies endangering the network. Machine learning capabilities reveal patterns and threats that hamper business continuity.
- Noise reduction – Traditional ITOps generates thousands of alerts and signals for a single event. In contrast, AIOps parses co-related logs and collates low-level events into minimum groups, thereby simplifying the work of the IT staff as they may now look at a small number of significant events only.
- Root cause analysis – AIOps enables organizations to reduce MTTA/R by analyzing the root cause of the issue and establishing correlations that illustrate hidden dependencies between incidents for faster diagnosis of the problem.
- Event escalation – AIOps identifies the root cause and escalates the issue to the right subject-matter experts or starts a remediation workflow, independent of human intervention, to ensure the end-user doesn’t face the consequences.
- Service desk automation – AIOps automates many functions, including ticket and log updates, audits, password resets, change risk analysis, etc. Leveraging chatbots accelerates self-service and allows users to solve routine issues on their own.
- Predictive maintenance – The infusion of artificial intelligence in IT operations predicts future incidents, prevents critical outages, and reduces operations and maintenance costs. Additionally, an analysis of the historical utilization trends indicates when an asset, component, or service will reach its full potential and avoids outages caused by capacity constraints.
While domain-agnostic AIOps tools cater to the broadest use cases but lack specialization, domain-centric tools focus on a particular domain like application performance monitoring
(APM), infrastructure monitoring, etc., without giving a holistic view of the overall IT infrastructure.
Hence, it’s crucial to evaluate vendor strengths in each area and lay down the objectives you want to achieve from implementing AIOps tools before selecting a solution.
2. Data ingestion and data enrichment capabilities
Modern IT operations require AIOps tools to break down silos and ingest information from diverse sources, including physical infrastructure, network, applications, and the cloud, to comprehend the present state of the IT infrastructure.
In support of domain-agnostic use cases, the tools must increase the breadth and depth of analysis, work with legacy and existing monitoring technologies, and access a wide range of historical and streaming data.
Furthermore, the AIOps platform should enrich logs and events with metadata and tags to provide a context for indexing and search and overlay data points with time stamps that generate time-series information.
3. Flexible deployment options
The mode of deployment is another significant consideration to look into when implementing an AIOps solution. The deployment approach must meet your business’s unique needs, be it a self-managed, on-premise, or a platform-as-a-service model.
Other Criteria to consider when searching for an AIOps solution
1. Estimated ROI from AIOps
While the estimated time-to-value for most AIOps solutions is measured in months or years, to calculate the return on investment (ROI) from AIOps, organizations must assess the inefficiencies removed between the “as is” and “to be” state, i.e., before and after deployment.
For this, it’s essential to know the quantum of IT incidents during a specific period, the number of incidents handled by humans, and the average time taken to resolve each issue. Then, plug in an estimated increase in efficiency, which organizations can evaluate as the ROI accrued from saving time and money (human “as is” cost) by leveraging automation.
Finally, when selecting an AIOps platform, organizations must budget for specific costs that inevitably come into the picture, such as administrative fees, software licensing costs, and deployment expenses.
How can Acuvate help?
At Acuvate, we help clients enhance IT operations through AI-driven analytics and performance management.
Our AIOps managed services monitor the IT network for anomalous behavior, improve infrastructure resiliency, agility, support desk efficiency, and uptime, and reduce costs. These include –
- Intelligent alerts and incident management
- Reduction in event noise
- Predictive analytics and insights
- Anomaly detection
- Root cause analysis automation
- Service desk automation
- Performance base-lining
To know more about our AIOps services, please feel free to schedule a personalized consultation with our experts.