How IT Teams Leverage AIOps’ Capabilities

How IT Teams Leverage AIOps’ Capabilities

This article is the second in a 4-part series on leveraging artificial intelligence for IT operations (AIOps) to provide a more efficient, reliable, agile, cost-effective, and optimized IT infrastructure.

If Artificial Intelligence is the ultimate multi-tool for IT operations (as discussed in our first article), then DevOps, Network Ops, Site Reliability Engineers (SREs), and SecOps are the teams using it. How each team uses AIOps’ capabilities will improve interconnectivity across an organization’s digital landscape, accelerate the production of high-priority business objectives, and reduce downtime to pave the way for a smoother developer and user experience.

Meet the Crew: Defining the Teams of IT Operations

Before we map capabilities to teams, let’s establish some broad team definitions as they may currently exist within IT operations:

  • DevOps: Ensure smooth collaboration between development and operations. 

Priorities include automation, issue detection, and optimizing workflows to speed up software development and delivery.

  • IT Operations: Manage and maintain the organization’s IT infrastructure. 

Priorities include improving operational efficiency, reducing downtime, and improving system reliability.

Priorities include identifying bottlenecks and predicting potential network issues.

  • SRE: As an operational group, SREs own the back-end infrastructure responsible for the customer experience, and consult with developer teams to ensure the infrastructure can support applications. 

Priorities include avoiding downtime among revenue-critical systems, preventing bandwidth outages, and fixing configuration errors. 

Priorities include security log analyzation and response, and identifying anomalies or vulnerabilities.

Building Solid Foundations: Intelligent Capabilities by Team

AIOps uses artificial intelligence, machine learning, and consolidated operational platforms to automate repetitive or mundane tasks and streamline cross-team communications. An AIOps deployment is the scaffolding IT operations use to build evolving workflows so the teams can be more proactive, innovative, and able to accelerate the delivery of high-priority projects. That’s why we are seeing more AIOps success stories about how AIOps can liberate 40% of your engineering time through the automation of labor-intensive analysis, or how Managed Service Providers (MSPs) are implementing AIOps’ intelligent alerting capabilities to dramatically reduce downtime

So let’s dig into which three AIOps capabilities each team may leverage first:


  • Enhanced Efficiency: Automating repetitive and manual tasks frees up time to focus on higher-value initiatives, increasing efficiency and productivity across the entire team.
  • Faster Mean Time to Resolution (MTTR): Streamlining incident management processes ensures faster issue identification, analysis, “next steps” cross-team communications, and ultimately, issue resolution. With automation doing the heavy lifting, these steps can happen outside of work hours. This 24/7 approach reduces the time to resolution, minimizing any impact on operations.
  • Scalability and Adaptability: AI and machine learning’s self-learning properties are made to handle complex and rapidly evolving technology stacks in dynamic environments. 

Watch the 3-minute video below for more on how DevOps can use AIOps for faster issue resolution through an integration with open-source provisioning and configuration management tools.

IT Operations

  • Incident Management: AIOps streamlines incident identification and root cause analysis, and escalates incidents to the right teams and people who can pin-point source of an issue is quickly fix it. Post-incident reviews are used to build resilience in systems to prevent future occurrences similar incidents. Faster resolution reduces MTTR and operational impact.
  • Scalability and Adaptability: IT infrastructure has to adapt to business needs. AIOps systems handle the complexity of evolving modern stacks and dynamic environments including hybrid and multi-cloud architectures. Faster scaling sets ITOps up for success in that they can effectively manage and monitor expanding IT landscapes at any stage of growth.
  • Resource and Cost Optimization: Capacity planning and the automation of tasks lets ITOps teams allocate resources more efficiently, freeing up budget and personnel for new endeavors or headcount strategies.

Network Ops

  • Streamlined Troubleshooting: Automated root cause analysis capabilities quickly pinpoint the root causes of network issues, accelerating troubleshooting which improves uptime. 
  • Capacity Planning: Historical and real-time data analysis on network use patterns, forecasted future demands and resource allocation enables the team to reassign assets as needed to prevent network congestion, keep operations consistent while supporting business growth.
  • Network Security Enhancement: Leveraging AI-driven algorithms which analyze network traffic, detect anomalies, and identify potential security threats enables Network Ops teams to take proactive measures ahead of a breach.


  • Elasticity: As SRE teams manage complex and dynamic environments, including cloud-based systems and microservices architectures, AIOps provides the ability to scale and adapt to changing demands. AIOps ensures the SRE team can effectively monitor, manage, and optimize the system’s performance as it grows and evolves.
  • Continuous Optimization: AIOps analyzes data from various sources, including logs, metrics, and events, then identifies optimization opportunities which SRE teams can enact. Leveraging AI insights to make data-driven decisions, implement proactive measures, and continuously refine their infrastructure to achieve greater reliability.
  • Collaboration and Knowledge Sharing: By providing a centralized platform for data collection, analysis, and visualization, AIOps facilitates communication and sharing of information so associated teams (such as developers) can align their efforts towards common goals, leading to improved teamwork and faster problem-solving.


  • Advanced Threat Detection: AIOps enhances threat detection capabilities by analyzing vast amounts of security-related data from various sources, such as logs, network traffic, and user behavior. AI-driven algorithms can identify patterns, anomalies, and potential security threats in real-time, enabling SecOps teams to respond promptly to security incidents, minimizing damage caused by cyber threats.
  • Threat Intelligence Integration: AIOps integrates with threat intelligence feeds and external security sources to enhance the effectiveness of security operations. By leveraging external threat intelligence data, AIOps enriches its analysis and detection capabilities, allowing SecOps teams to stay updated on the latest threats and attack vectors. This integration strengthens the overall security posture and enables proactive defense against emerging threats.
  • Compliance and Regulatory Requirements: AIOps automate compliance monitoring and reporting processes then compare them against predefined standards and regulations to evolve the automation and compliance process so teams consistently meet compliance and regulatory requirements. 

AIOps give teams the tools they need to transform from reactive to proactive. The combination of artificial intelligence and machine learning accelerates issue mitigation, breaks through work silos, improves systems security and scalability, increases productivity, reduces error risk and optimizes resources and costs. Having an AI-empowered IT operation means an organization’s infrastructure is instantly ready to handle roadblocks for a smoother developer and user experience.

LogicMonitor is proud to power the journey to AIOps by offering these free educational resources:

What is AIOps and How is it Changing IT Operations? 

Simplify Troubleshooting with AIOps

Monitoring and Alerting Best Practices Guide 

Sensirion Goes from 8 Monitoring Tools to Just One

Comprehensive AIOps for monitoring 

Unlocking the Path to Automation with LogicMonitor