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  • What AIOps is.
  • Why do you need it.
  • Understand the Building Blocks of AIOps.
  • What are others saying about AIOps.

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Digitalization drives complexity in IT

INTRODUCTION

Today, we live and work in a digital economy that is becoming more and more vulnerable. Companies have come to rely on increasingly complex IT infrastructure, software applications and microservices to drive revenue and improve productivity. This holds true across industries but especially in technology, banking and finance, manufacturing, logistics / supply chain, retail and e-commerce, public sector and healthcare. As the IT ecosystem of companies becomes more agile, complex and real-time the IT operations challenge increases exponentially. Businesses have been ill-equipped to deal with looming technical issues, which has caused many to lose revenue or incur significant costs. No longer can information technology operation professionals rely on traditional methods.

AIOps Building blocks

To address problems before the business is impacted companies must make a shift towards automation. Artificial Intelligence (AI) is the new driver for transforming traditional ITOps into AIOps. Here we give you an introduction to what AIOps is, why it’s needed, and how it can be applied to your own operations. As when building a house, we explain how the key capabilities of AIOps ("elements of a house") must be built from the bottom up where the foundation for building (or “floor”) is quality data. Without the ability to harvest quality data, it's impossible to build the "house" with sound and solid "walls," and a "roof." When it comes to AIOps, what you put in (junk), is what you get out (junk). So, it's imperative that you use quality data as a foundation.

 

AIOps is Artificial Intelligence in IT Operations

What is AIOps?

AIOps, which is the acronym for Artificial Intelligence for IT Operations, is a term coined by Gartner, the top technology research and consulting firm. AIOps is powered by two core technologies that continue to go through a riveting pace of development, Big Data and Machine Learning (ML).  The availability of Big Data and Machine Learning capabilities powers the massive computing required to analyze the thousands, millions and billions of data points and log files harvested by AIOps tools.  Using smart algorithms, machine learning and artificial intelligence, AIOps gathers and analyzes data from different sources and automatically identifies issues through the IT layers and across the stack to ultimately trigger intelligent self-healing. 

AIOps 1

 

You need AIOps because the traditional IT Operations set-up is broken.

Why do you need AIOps?

The use of artificial intelligence is becoming a necessity for IT operations. As businesses go digital their use of more complex technologies like cloud architectures puts them at risk of failing with crucial governance and monitoring requirements. Failure will impact the corporate Profit & Loss through revenue- and productivity loss.  

Here are a number of reasons why you need AIOps:

  • Identify situations you would otherwise not capture
  • Address performance issues automatically preventing the need for middle-of-the-night emergency wake-up calls
  • Prioritization of alerts reduces notifications to focus only on those that are most important
  • Reduction in detection and repair time
  • Improved operational visibility
  • Analyze in real-time including causal analytics to address problems
  • Recommendations are data-driven making use of both real-time and historical data.
  • Reduce or eliminate costly and time-consuming human errors 
  • Free up IT capacity from mundane, repetitive tasks
  • Improved visibility to deploy code faster
5 Building blocks (+1) make up AIOps

What are the Building blocks of AIOps?

AIOps can be broken down into basic capabilities (or building blocks) from collecting data to taking action. AIOps allows for IT operations to employ a system that makes sense out of the data in a way that makes it actionable. These five (+1) capabilities of AIOps — each one delivering incremental value — should initially be implemented sequentially with later iterations. Just as when building a house you need a floor, walls, a ceiling, and a roof, these capabilities must function together in order to fully capture the value of AIOps.  That said, an intelligent self-healing AIOps with comprehensive data / system coverage (observability) is likely a few years away.  Self-healing it is today in use but for selective systems / data sets.  As the type and scope of data increase the predictability drops and increased intelligence is required.

If you prefer video ;)
AIOps building blocks

 

Junk in - junk out...

AIOps Capability 1: Data Harvesting (floor)

If you're trying to envision where the five capabilities of AIOps fit into a business, it starts with data harvesting. As the "floor" of the AIOps infrastructure, data harvesting involves collecting data on a continuous basis - time series performance metrics and text logs - from multiple sources. Structuring and normalization of the data is a key capability together with flexibility in the ingestion APIs.  AIOps is about making sense of data across huge data sets and sources.  Hence the ability to flexibly consume, normalize and structure the data for subsequent processing across any sources is fundamental.

Get the algorithms to work for you

AIOps Capability 2: Learning & Correlation Engine (walls)

If data harvesting is the floor of AIOps, then the learning and correlation engine represents two walls of the building. Using the power of machine learning (ML), AIOps learn the normal behavior patterns of the data and use correlation to identify relationships and make sense out of a vast amount of events. Using anomaly detection, AIOps detects abnormalities that can lead to problems. This helps to get to the root cause of the problem and speed up resolutions.

Understand the context

AIOps Capability 3: Topology Discovery (walls)

Topology discovery is another crucial capability. Topology refers to the physical structure, relationships and dependencies of artifacts or assets in an organization’s IT ecosystem. Topology can be represented in many layers and business needs.  From technical network diagrams to dependency topologies to higher level business topologies.  The ability to navigate through the topology layers - from/to - technical and business is key to understanding the context, and hence the importance, of any anomaly. The topology includes infrastructure, applications and services independent of data center, physical, container or cloud deployment.

The ability to get topology context with anomalies allows a drastic reduction in MTTK (Mean Time To Know) and the MTTR (Mean Time To Respond) beyond anything that humans are capable of doing alone.

Getting to relevant anomalies is a major milestone

AIOps Capability 4: Business Relevant Anomaly Alerts (ceiling)

Business relevant alerts are the "ceiling" of the AIOps architecture. What’s different about alerts in an AIOps infrastructure is that they do not rely on pre-configured alerting defined by technical teams - rather they rely on algorithms to identify anomalies.  This relies on solid data, a sophisticated and robust anomaly detection engine and context.  The alerts should be prioritized to those that are most relevant to the specific business operation impacted. The alerts that you don’t care about should be suppressed automatically. This contributes to eliminating the common alert fatigue that IT teams struggle with when trying to filter through all the alert noise to get to the most important problems and solve them as quickly as possible.

Don't underestimate the value of smart dashboards

AIOps Capability (Bonus): Actionable Dashboards

A bonus capability from all the data and actionable insight are dashboards and reports. In practice, the data is real time business intelligence.  Possibly better than from any traditional BI tool, real time with built in anomaly detection and context.  The ability to leverage this data and insight for reports and dashboards for stakeholders across an organization - from technical to managers and executives will be crucial to the required governance of IT that the profit & loss of businesses rely on.

Its all about taking early action to prevent

AIOps Capability 5: Taking Action (roof)

Last, but certainly not least, actually taking action with AIOps forms the roof. Every capability before this one enables you to take action whether that action is manual or automated. Once the data has been harvested, processed by the anomaly detection engine and analyzed for context-aware anomalies, then the resulting probable root cause can be identified and acted upon quickly.  This may be manual action or automated action by triggering auto-healing scripts.

Analysts agree - AIOps is unavoidable.

What Are Others Saying About AIOps?

While only a small percentage of businesses have taken on AIOps, Gartner predicts that a larger majority will be taking it on in the near future. If you’re not one of those, chances are you’ll be left in the dust as your competitors speed ahead. Here’s how other IT professionals think about AIOps as it pertains to their organizations:

  • 72% rely on up to nine different monitoring tools
  • 47% receive over 50,000 alerts per month.
  • 97% believe AIOps will deliver actionable insights to help automate and enhance IT operations
  • 90% agree that AIOps is very important for the future of IT operations

It’s very difficult for businesses to keep up with the rapid advances in technology. It’s seemingly easier to just stay in your comfort zone, resistant to change, rather than take on something like AIOps. It’s also understandable that you may have little to no knowledge of how to implement AIOps into your IT operations. However, as businesses grow and data increases along with the sources from which it’s collected, so do their technology needs. If you don’t leverage the automation power of machine learning and artificial intelligence, then you’ll find that your team won’t be able to handle big data. AIOps helps you to nip the issues in the bud before they have a chance to wreak havoc on your IT operations, which can lead to disastrous consequences for your customers and overall business.

As you can see now, AIOps isn’t just an option or alternative, it’s a must-have. When building a house, you can’t start with the roof without building the right foundation.  The foundation is the data which everything else relies on. And AIOps is not an option - it will be a requirement to succeed with digital business.  Hence, the question is only how and when you adopt.

References

https://www.gartner.com/en/documents/3881464/deliver-cross-domain-analysis-and-visibility-with-aiops-

https://sloanreview.mit.edu/article/how-big-data-and-ai-are-driving-business-innovation-in-2018/

https://sloanreview.mit.edu/article/the-building-blocks-of-an-ai-strategy/

https://reprints2.forrester.com/#/assets/2/601/RES158920/report

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