IT engineers and executives are responsible for system reliability and availability. The volume of data can make it hard to be proactive and fix issues quickly. With over a decade of experience in the field, I know the importance of IT operations analytics and how it can help identify incidents and enable agile responses.

What Is IT Operations Analytics?

IT operations analytics (ITOA) uses big data techniques to analyze IT system performance. These findings help companies deploy IT resources more efficiently and effectively. IT teams turn to ITOA to diagnose and fix problems more quickly, thus reducing outages.

Organizations need ITOA because the IT environment is complex and changes frequently. Analytics helps cut through this complexity by making issues more visible and speeding up the troubleshooting process.

ITOA solutions look at a constant stream of data about system health. They spot trouble signs and flag them for IT Ops teams, which includes centralized IT operations teams, network operation center (NOC) teams, and increasingly, DevOps and SRE teams. Analytics helps these teams locate and diagnose problems. This streamlines a process that would otherwise be much more cumbersome to manage manually.

ITOA vs. AIOps

ITOA is evolving, and AIOps (artificial intelligence for IT operations) is its successor. Both analyze IT operations data. ITOA uses Big Data techniques. AIOps uses machine learning and artificial intelligence. This enables AIOps to improve on ITOA and be predictive and preventative.

ITOA vs. System of Intelligence

ITOA and systems of intelligence both improve IT operations. But ITOA is functionally oriented. A system of intelligence takes a wider view. It looks at technology within the context of the whole organization and is aimed at strategic purposes.

A system of intelligence is one of three types of systems under a theory about how companies gain an advantage over competitors with their technology systems.

Systems of intelligence stand between systems of record, which include applications containing data on IT management along with systems for customer, enterprise, and employee data, and systems of engagement, which are communications channels such as a website and social media.

The system of intelligence integrates systems of record and applies machine learning and analytics to their data. Then the system of intelligence yields insights about the business.

In IT, the system of intelligence performs some functions similar to ITOA. But the goal of systems of intelligence is more transformative. The system uses business intelligence and predictive analytics to drive competitive advantage and innovation.

Benefits of IT Operations Analytics

IT Operations Analytics offers many benefits. They help companies keep their technology systems working efficiently. They enable IT Ops teams to maximize resource usage, improve user experience, and limit downtime.

Top ITOA benefits include:

■ Ability to gain a comprehensive view of all IT operations

■ Automated notifications for common problems

■ Better decision-making

■ Decreased downtime

■ Efficient resource usage

■ Faster troubleshooting and problem resolution

■ Identifying hotspots that generate the most alerts

■ Improved user experience and satisfaction

■ Optimization of system and application performance

■ Proactive identification of issues

■ Quick resolution of common issues

■ Reduced risk associated with system changes

Applications for IT Operations Analytics

IT Ops teams apply operations analytics in multiple ways. Some of these use cases aim to figure out the causes and solutions of IT problems. Other uses are focused on understanding how the system performs and how to improve that performance.

■ Assist Root Cause Analysis: ITOA helps IT teams determine the root cause of an issue. This may be hard to spot if the initial problem caused a cascade of effects or multiple issues occurred at once. Event correlation, which links problems to system changes, helps significantly. If there are multiple root causes, ITOA can rank them in priority order. This speeds resolution and aids prevention.

■ Find the Right Owner: Analytics helps identify the department, team, or person that is best placed to solve the problem. That shortens time to response and resolution compared to passing around the issue before reaching someone who can solve it.

■ Optimize System Performance: IT teams can leverage analytics to understand how varying conditions affect system uptime, service availability, and overall system performance. This understanding helps IT Ops anticipate how the system will act in the future.

■ Visualization: ITOA models and patterns of IT infrastructure and applications can add to understanding of system architecture, network topologies, and dependencies from other mapping and discovery tools. This knowledge helps locate the site of an issue.

■ Understand Business Impact: Operation analytics can put issues within the context of the overall business. ITOA can highlight and prioritize problems that affect revenue generation. This may delay resolution of a less important issue that was reported earlier. Since metrics for time to resolution are typically the benchmark for grading IT teams, this may require changes. But it aligns IT with the business.

■ Automate Action: Once you have visualization, root cause analysis, and other insights from ITOA, you can create automated response steps. For example, certain conditions, error codes, or events can trigger actions. These could include diagnostics and notifications, as well as putting a predefined run book into action.

Go to: Everything You Need to Know About IT Operations Analytics - Part 2