Detect anomalies faster with AIOps

Have you ever been trying to use an application and it went down? Is your organization challenged with keeping applications up? Maybe it’s not just Outlook, but other essential business applications aren’t stable.

Hi, I’m Peter Nichol, Data Science CIO.

Today we’re going to get into some of the benefits of AIOps, also known as artificial information operations. The mean time to fix a production outage is 4.5 hours. Extended outage periods negatively impact your staff productivity and efficiency. Benchmark studies estimate that $21.8 million per company is lost annually due to unexpected downtime.

What is AIOps?

AIOps applies the concepts of machine learning and data science to solve IT operational problems. Often, these problems are solved through the introduction of automation.

One of the fascinating examples of applying AIOps is leveraging this technology to identify network failure points. Operations—or, more specifically, artificial intelligence operations—use predictive technologies to identify the root cause of failures within software-defined networking in vast area networks (SD-WANs). SD-WANs carry mission-critical traffic (transactional, customer, member). These intelligent networks can dynamically partition and protect the network against vulnerabilities in other parts of the technical enterprise topology. These intelligent and predictive network tools are triggered by irregular patterns of behavior and near-instantly change the network’s topology.

AIOps offers benefits in many areas

When technology leaders have challenges with utilization or bandwidth, AI operations can immediately identify when threshold limits have been reached.

Amazingly, through the integration of other technologies, environments can provide auto-scale. Autoscaling is the act of dynamically increasing bandwidth for peak load and then contracting bandwidth when it’s no longer required. This process of ideal usage helps create a highly efficient infrastructure, saving dollars when we least expect it. Automating these processes using thresholds can generate significant benefits when monitored and implemented by experts.

There are numerous areas where AIOps can offer benefits:

  1. IT incidents
  2. Intelligent IT automation
  3. IT service management
  4. Alert management
  5. Automatic anomaly detection
  6. Ability to predict outages
  7. Freeing up expensive human capital
  8. Availability and performance monitoring
  9. Event correlation and analysis
  10. Cloud spend optimization
  11. Identifying the health of customer-facing issues

The growing market for AIOps

AIOps is erupting with potential. It’s forecasted that, by 2023, the market for artificial intelligence for IT operations will blow up to about $11.2 billion. This marks enormous growth in an industry that’s fascinating but relatively unknown.

When we look at the players in this space, the predictive capabilities they can provide are almost unbelievable:

  • Data agnostic tools: Anodot, FixStream, and OpsRamp
  • Legacy platforms: bms, ca technologies, and Micro Focus
  • Logging: elastic, OverOps, and splunk
  • Monitoring: Dynatrace, SignalFx, and ScienceLogic
  • Alerting: pagerduty, OpsRamp, and LogicMonitor

Again, AIOps focuses on taking action based on events that can be predicted through pattern analysis. Taking action based on failures or when things go wrong are typical applications of AIOps.

What applications do you use the most during the day? Which applications, when unavailable, most significantly impact your team’s performance? It’s not just Microsoft Outlook and other core applications that prevent individual users from performing their daily duties when they’re not available. To send that email, you might have to check a report in Tableau. You might have to download SQL Server Management Studio data or ask a team member to pull the data for you. Rarely does the primary business application meet 80% of the business needs.

Autoscaling is likely the most common AIOps application where bandwidth scales up or threat-based events trigger the auto partitioning. These are both examples of AIOps at work.

Has your organization fully leveraged the power of AIOps? For example, has your company defined standard operating procedures for auto-scaling? Are you in agreement with your business partners about those procedures? After all, when those services aren’t available, guess who they’ll affect the most?

The ability to introduce self-healing, self-monitoring, and self-management tools through the design of AIOps environments can transform outcomes for technology leaders.

AIOps offers a great ecosystem of platforms, services, and products when you have information overflow.

If you found this article helpful, that’s great! Also, check out my books, Think Lead Disrupt and Leading with Value. They were published in early 2021 and are available on Amazon and at http://www.datsciencecio.com/shop for author-signed copies!

Hi, I’m Peter Nichol, Data Science CIO. Have a great day!

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Peter is a technology executive with 19 years of experience, dedicated to driving innovation, digital transformation, leadership, and data in business. He helps organizations connect strategy to execution to maximize company performance. He has been recognized for Digital Innovation by CIO 100, MIT Sloan, Computerworld, and the Project Management Institute. As Managing Director at OROCA Innovations, Peter leads the CXO advisory services practice, driving digital strategies. Peter was honored as an MIT Sloan CIO Leadership Award Finalist in 2015 and is a regular contributor to CIO.com on innovation. Peter has led businesses through complex changes, including the adoption of data-first approaches for portfolio management, lean six sigma for operational excellence, departmental transformations, process improvements, maximizing team performance, designing new IT operating models, digitizing platforms, leading large-scale mission-critical technology deployments, product management, agile methodologies, and building high-performance teams. As Chief Information Officer, Peter was responsible for Connecticut’s Health Insurance Exchange’s (HIX) industry-leading digital platform transforming consumerism and retail oriented services for the health insurance industry. Peter championed the Connecticut marketplace digital implementation with a transformational cloud-based SaaS platform and mobile application recognized as a 2014 PMI Project of the Year Award finalist, CIO 100, and awards for best digital services, API, and platform. He also received a lifetime achievement award for leadership and digital transformation, honored as a 2016 Computerworld Premier 100 IT Leader. Peter is the author of Learning Intelligence: Expand Thinking. Absorb Alternative. Unlock Possibilities (2017), which Marshall Goldsmith, author of the New York Times No. 1 bestseller Triggers, calls "a must-read for any leader wanting to compete in the innovation-powered landscape of today." Peter also authored The Power of Blockchain for Healthcare: How Blockchain Will Ignite The Future of Healthcare (2017), the first book to explore the vast opportunities for blockchain to transform the patient experience. Peter has a B.S. in C.I.S from Bentley University and an MBA from Quinnipiac University, where he graduated Summa Cum Laude. He earned his PMP® in 2001 and is a certified Six Sigma Master Black Belt, Masters in Business Relationship Management (MBRM) and Certified Scrum Master. As a Commercial Rated Aviation Pilot and Master Scuba Diver, Peter understands first hand, how to anticipate change and lead boldly.