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AIOps Event Correlation Use Cases: Technical, Operations & Business

AIOps Event Correlation Use Cases for IT Ops, NOC, DevOps, and SRE

AIOps, using artificial intelligence to manage IT operations, provides a powerful tool to drive efficiency and automation. This approach enables event correlation: finding patterns among a stream of operational events. You can use it to improve technical, operational and business processes.

In this article, you will learn valuable use cases, including:

Top AIOps event correlation use cases

The use cases for event correlation fall into three categories: technical, operations, and business.  AIOps uses artificial intelligence to analyze processes. That paves the way for efficiency and automation.

These use cases involve many stakeholders, from frontline operations teams to CEOs. But generally, the impact becomes more strategic in the operational and business use cases. Higher management ranks may focus on use cases that optimize the IT function, reaping operational efficiencies and enhancing business agility.

AIOps tools help teams quickly resolve IT problems and contribute to system stability and availability. To learn about the steps in event correlation, such as event aggregation and KPIs, read “The Definitive Guide to Event Correlation in AIOps: Processes, Examples, and Checklist.”

AIOps use cases and stakeholders

AIOps use cases and stakeholders

How is event correlation used in IT operations?

Event correlation detects patterns among IT problem signals. These include alarms and notifications that signify a potential incident. AIOps tools correlate these signals to system events and determine root causes.

The technology infrastructure and data flow at most companies are so complex that these signals arrive in a constant flood from monitoring applications.  IT teams struggle to make sense of this data and prioritize important problems over those that aren’t critical.

AIOps tools leverage data analysis, anomaly detection, and artificial intelligence’s predictive powers to conduct event correlation and find causes.  AIOps can automate incident detection and remediation.

AIOps with different tech frameworks

AIOps event correlation can benefit any technology framework. That includes Dev Ops, IT Service Management (ITSM) and Site Reliability Engineering (SRE).

IT Service Management (ITSM) is the traditional method of IT management using Information Technology Infrastructure Library (ITIL) best practices. The system administrator plays the central role here. AIOps event correlation speeds up the triage and resolution of IT issues under ITSM.

DevOps and Site Reliability Engineering (SRE) are two modern frameworks for managing technology at large organizations. AIOps event correlation supports both approaches by accelerating development, enhancing collaboration, and improving system health.

DevOps seeks to speed up the development cycle and prevent failed deployments. DevOps is a culture and set of practices that makes the application delivery workflow more efficient and unifies development and IT operations stakeholders.

Automation plays a big role in Dev Ops, often through continuous integration/ deployment (CI/CD) pipelines. AIOps event correlation and automation help Dev Ops teams rapidly detect and repair issues before affecting users.

SRE teams focus on system health and maximizing uptime. Automation is also important to the SRE function, which seeks to eliminate repetitive work, standardize processes, and break down siloes. AIOps event correlation supports SREs by making the task of preventing system degradation easier.

Technical use cases for event correlation in AIOps

Technical use cases for event correlation revolve around addressing the daily flow of alerts to network operations centers (NOC) and support teams. Coping with it all is no easy task.

Technical use cases focus on keeping networks, hardware, and applications running, so the business can operate normally. These needs prioritize the detection and remediation of issues impacting users and undermining service availability, security, and reliability.

See case studies for technical use cases, including alert noise reduction, automation, alert compression, incident enrichment, and IT reporting and analytics.

Here’s a rundown of technical use cases for event correlation in AIOps:

  • Alert noise reduction: The complexity of the computing environment at most companies has given rise to monitoring tools to surveil the infrastructure and send alerts. Large organizations typically employ more than 15 tools to monitor key applications, services, and computing resources.The proliferation of these tools has made the volume of alerts unmanageable, often numbering in the tens of thousands daily. Like static on the radio, this noise makes it very difficult to detect the true signals. ITOps, NOC, DevOps and SRE teams struggle to interpret the incoming information.Attempts to solve this problem include filtering only high-severity alerts, adding staff, or relying on customers to report problems. However, these solutions often put the team in a reactive stance.AI and machine learning (ML) are changing the game. AIOps tools can process large amounts of event data in real-time, analyze it, and detect meaningful insights. These tools can filter out false positives. The process can compress many alerts into a small number of actionable incidents by correlating multiple instances to the same cause. The most powerful AIOps platforms can reduce IT noise by up to 95 percent.
  • Automated incident detection: As AIOps tools learn from their environment, they can automate incident detection. The fragmented tools in most enterprises typically look only at part of the computing landscape and do not integrate. This leaves the monitoring data siloed. Cross-stack insights are hard to obtain.Strong AIOps platforms connect these tools and combine their data in real-time. They provide a unified view, making it possible to enrich monitoring alerts with context from other data sources. This process gives greater visibility into the scope and root causes of incidents and outages. ITOps, NOC and SRE staff benefit from analytics and dashboards.Additionally, enterprises that face compliance regulations can use event correlation to flag security threats and other issues.
  • Automated investigation: The best AIOps platforms provide an automated investigation of events. They perform root cause analysis of system changes, topology, and incident timelines. Machine learning enables these tools to become more effective over time.With many enterprises using cloud and hybrid cloud architecture, their infrastructure changes rapidly. This is the primary cause of incidents and outages.Change management tools do not track many of these shifts, making it hard to know which change caused an incident. Similarly, enterprises need to have real-time, full-stack topology models to find the root causes of problems. Otherwise, the investigation and resolution of incidents slows down, and issues can escalate.AIOps tools integrate all change monitoring data and compare changes to real-time monitoring alerts to discover root-cause changes.  By making insights from different tools easily accessible, AIOps platforms allow faster investigation.

    Topology modeling adds to accuracy, and incident visualization helps create a timeline of symptoms and events. In a single view, users can see when each alert in an incident occurred. Without this context, ITOps engineers struggle to know the order of symptoms and determine the cause.

  • Automated incident response: Automated incident response is another key technical use case for event correlation in IT Ops. AIOps platforms automate creating tickets, sending notifications, convening team members, initiating workflows, and triaging incidents.Without these capabilities, enterprises lose time to error-prone manual ticketing and notifications through multiple channels such as email, text, and Slack. In a major incident, setting up a war room with key participants, including Level 3 and Dev Ops members, is often cumbersome. Automated incident response can ensure all the right people are at the table, that everyone can communicate, and that all the relevant operational data is accessible.Incident triage can suffer because IT Ops and NOC teams lack important context about incidents, such as the business impact and affected services. That causes higher MTTR (mean time to resolve and repair.) AIOps platforms make it easy to incorporate business context and make all the relevant information available. This speeds up the resolution.AIOps platforms also automatically sync information on progress toward resolving the incident. This keeps everyone informed, including those on the incident team and users elsewhere in the organization.
  • IT Ops reporting and analytics: Just as AIOps brings together incident information from different monitoring tools, these platforms provide unified IT Ops analytics, performance dashboards, KPI tracking, and more.This use case makes the benefits of AIOps measurable and helps leaders improve IT Ops risk management.  With the right AIOps tools, you can build dashboards of key performance indicators (KPIs) that give you a customized view of the metrics that matter most to your organization. This makes it straightforward to show improved service reliability, availability, and return on investment.An AIOps event correlation and automation platform can report and analyze KPIs, including:
    • Service availability metrics
    • SLA (service level agreement) metrics
    • MTTR (mean time to resolve, repair)
    • MTTR by NOC, user, and priority level
    • Resolution rates
    • Escalation rates
    • Team performance
    • Individual performance
    • Enrichment rates
    • Recurring incidents
    • Alert correlation and compression percentage
    • Alert compression trends
    • Enrichment percentage
    • Mean time to detection (MTTD)
    • Mean time to identify (MTTI)
    • Mean time to acknowledge (MTTA)
    • L1 resolution rate

Operational use cases for event correlation in AIOps

The use cases for event correlation in operations revolve around simplification and communication. You can use AIOps tools to optimize processes and improve performance. They break down barriers and improve collaboration.

See case studies for operational event correlation, including tools, unifying siloed teams, and converged workflows.

Here’s a rundown of operational use cases for event correlation:

  • Tools consolidation: Tools enable IT operations teams to observe and monitor the computing environment, including infrastructure, networks, applications, and services. The objective is to gain visibility into system availability, reliability, and performance.But enterprises often find the number of tools in place creeps higher as they try to stay current and acquire new capabilities. Having up to 15 different monitoring and observability tools in use is not uncommon, as we mentioned earlier. This results in fragmentation.The proliferation of tools also contributes to excessive IT complexity, a cause of technical debt and poorly understood systems. Some enterprises have multiple tools seeking to solve largely the same problem.AIOps event correlation platforms overcome these challenges by ingesting data from different observability, change, and topology tools. AIOps layers share incident insights across ITSM, ticketing, on-call, chat, and runbook tools.

    This unifies fragmented tools and may make redundancy apparent, enabling the organization to consolidate the number of tools in use. Tools rationalization also helps simplify IT systems.

  • Unifying siloed teams: Enterprises have a variety of groups with responsibility for the computing environment. These may be centralized IT Ops staff or distributed Dev Ops and service reliability engineering (SRE) teams.Each of these teams may work only with certain monitoring tools.  In this case, the information and insights generated by the tools may not cross teams. This creates siloes and diminishes the value of the tools.Without shared context, a lack of alignment results. The incident response may be slower than needed, and teams may lose trust in their counterparts.AIOps event correlation applications unify the information from monitoring and observability tools and help teams collaborate on incidents quickly, easily, and consistently. AI event correlation platforms break down barriers and provide a richer and more contextualized view of the organization’s systems. And it puts siloed teams on the same page.
  • Unifying cloud architecture: Enterprises often operate complex architecture that includes private cloud, public cloud, and on-premises data centers. An AIOps event correlation and automation platform combine tools and teams managing different environments.AIOps event correlation platforms make it possible to connect cloud and on-premises architectures through a consolidated view. Topology data enable teams to find the source of an issue wherever it may be in the organization’s architecture.

Business use cases for event correlation in AIOps

Business use cases for event correlation start with improving efficiency. Other use cases include increasing performance and development speed.  Businesses can use AIOps tools to gain a competitive advantage.

See examples of event correlation use cases for reducing alert volume, improving service reliability, eliminating manual work, strengthening agility, resolving issues before they impact the business, optimizing service levels, topics, operational efficiencies, and enhancing user experience.

Here’s a summary of business use cases for event correlation in AIOps:

  • Increasing operational efficiencies: AIOps event correlation helps enterprises reduce operating costs. IT executives are constantly striving to reduce the resource demands of technology operations. Rapid IT complexity and scale growth can lead to more incidents, slower resolution, inconsistent team productivity, and headcount growth.
    • Reduced alert volume and workload for IT teams. Event correlation and automated response reduce the workload for IT Ops teams. By cutting alert volume by more than 95 percent, AIOps enables organizations to manage growth in data, scale, and incident volumes without needing more people.
    • Automated workflows. Similarly, automated workflows with AIOps event correlation are much faster and easier to scale than manual incident management. AIOps tools add business context and automate ticketing, notification, and custom workflows. This facilitates the detection of incidents as they form before they cause outages and avoids costly penalties for breaching SLAs.
    • L1 resolutions. Enriched incident information also helps level one (L1) engineers resolve more issues without escalating them to higher-cost teams, who can maintain their focus on important projects. The organization can more easily see which services or infrastructure cause the most recurring incidents, fixing them to reduce incidents and the associated costs.
    • Productivity analytics. Analytics make it easy for NOC directors and managers to track performance and productivity by team, site, and shift, even for outsourced work. This spotlights opportunities for sharing best practices, implementing efficiencies, and optimizing shift assignments.
    • IT Ops cost optimization. Lastly, AIOps event correlation enables companies to see which of their many monitoring tools are necessary for incident management. The organization can cut any that are redundant or not adding value. That’s another opportunity to lower expenses.
  • Improving performance, availability of digital apps, and services: Because IT infrastructure is a crucial enabler for businesses, profitability and customer service depend on technology performance. IT Ops leaders ensure service availability, system performance, and user experience. They want to keep revenue-generating services running.AIOps event correlation and automation often reduce MTTR by 50 percent or more.  Also, they help meet performance objectives in the following ways:
    • Making it easier to manage legacy tools
    • Improving user experience by reducing frequency and impact of outages
    • Surfacing root cause of incidents quickly
    • Accelerating remediation by pinpointing infrastructure hotspots
    • Routing incidents to the right teams for rapid resolution
    • Increasing SLA compliance
    • Automating incident management to speed up resolution
    • Restoring system performance and availability sooner
    • Reducing interruptions for customer transactions
    • Enabling real-time incident response
  • Improving development velocity and business agility: Many enterprises are targeting digital transformation initiatives. But alert noise, time-consuming incident management workflows, and bottlenecks can keep them stuck in a reactive, firefighting mode.Similarly, increasing IT complexity and data volumes often interfere with agility and development cycles. Level One (L1) support teams more frequently escalate problems to Level Three (L3) and development teams that should be dedicated to innovative projects.By removing manual tasks from incident management workflows and automating root cause analysis, AIOps event correlation tools help L1 engineers resolve more issues and keep high-value teams focused on strategic and innovative work.With event correlation, developers spend less time addressing deployment issues, and Dev Ops teams find the insights they gain help them improve applications and user experience.

    By supporting modern architecture and hybrid environments, AIOps event correlation platforms also increase the success of initiatives such as adopting microservices and containerization. Enterprises face barriers if they have incident management toolsets not designed for cloud and hybrid environments. They lose time as performance degrades, and staff must focus on dealing with issues.

Strategic importance of AIOps use cases

Strategic importance of AIOps use cases

Event correlation experience

Companies can benefit more and more as they gain experience with event correlation. The initial benefits center on becoming more proactive rather than reactive. Over time, businesses find strategic benefits such as automation and innovation.

As companies become proactive, they can detect incidents before they impact users, automate the response, and stop the same issue from recurring. Ultimately, the organization turns to prevent them altogether.

Implementing AIOps event correlation often unlocks benefits from all three use case categories – technical, operational, and business – simultaneously. But the opportunity to use AIOps event correlation for the strategic impact, such as increasing development frequency and business agility, comes with further use.

The future of event correlation

The future of event correlation may lie in business results. For example, AI tools might connect operational data to customer satisfaction. This could lead businesses to make better operational decisions based on the results.

Event correlation, at its core, connects different types of data with IT alerts or events. In the future, event correlation may evolve by connecting new data types.

Today this means giving IT operations personnel additional context for issues by correlating alerts with topology and system change data. Future use cases may connect the IT environment with business outcomes.

Here are a few hypothetical examples.

  • Retail: For a retailer, event correlation could be about correlating data from monitoring tools with successful or failed customer purchases (in-store and online) to demonstrate how IT problems affected transactions and revenue.
  • Gaming: For a gaming company, event correlation could expand into correlating monitoring tool alerts with the usage of their system and players’ ability to buy digital goods.
  • Travel: For a travel company, event correlation could correlate booking volume and transactions with system event and performance health indicators.
  • Brokerage: For an online brokerage and trading platform, event correlation could connect trading volumes, customer satisfaction, and latency.

So how does AIOps improve event management and monitoring in Dev Ops environments? For starters, it optimizes application performance by providing rapid feedback to development from production.

As a result, Dev Ops teams can create more custom apps, release more code to production, and achieve full remediation of issues instead of settling for stopgap workarounds.

Invest in AIOps event correlation for proactive problem management

IT can approach problem management in two ways: reactively or proactively. The big question is: What will it take to become more proactive?

If you are building a business case for investing in event correlation and want to determine all AIOps event correlation use cases for your company, please email us at or take a self-guided tour of BigPanda’s Event Correlation and Automation platform. We are always happy to help you determine all the ways that event correlation can reduce your IT operation costs, improve availability, reduce MTTR and increase Dev Ops velocity.