AIOps Blog

Accelerate IT and IoT with AIOps and Observability

AI Abstract Cityscape
2 minute read
Sam Lakkundi
image_pdfimage_print

Today’s IT organizations are faced with the daunting challenges of managing a vast variety of specialized IT infrastructures and applications and ensuring that everything operates seamlessly together like a perfectly synchronized dance. And yet, these teams are often siloed, using different tools to support their products.

The Internet of Things (IoT) refers to products that are always connected to the internet, streaming behavior-related information and other data. Vendors of these products then analyze the data and draw insights to achieve multiple benefits.

What is AIOps?

You’ve probably heard the term AIOps (artificial intelligence for IT operations) used repeatedly as the next big thing in IT management, or read something about it having a significant impact on system operations and administration in numerous trade publications. But what exactly is AIOps? And why should you care about it?

AIOps is an umbrella term for the use of big data analytics, machine learning (ML), and other artificial intelligence (AI) technologies to automate the identification and resolution of common IT issues.

AIOps marries big data with ML to create predictive outcomes that help drive faster root-cause analysis (RCA) and accelerate mean time to repair (MTTR). By providing intelligent, actionable insights that foster a higher level of automation and collaboration, IT operations (ITOps) can continuously improve, saving your organization time and resources in the process.

What is observability?

Observability is the ability to measure the internal states of a system by examining its outputs. Observability allows teams to monitor modern systems more effectively and helps them to find and connect effects in a complex chain and trace them back to their cause. A system is considered “observable” if the current state can be estimated solely by using information from outputs, namely sensor data.

How AIOps powers digital transformation and redefines IoT

Digital transformation through AIOps is about improving the user experience, whether it’s IT end users or IoT. AIOps bridges the needs of the business with emerging technologies, from the cloud to IoT to big data and AI.

What’s driving the transformation of the user and the IT experience?

  • Unpredictable and intense competition
  • Automation
  • Business innovation
  • Downward cost pressures
  • New and changing customer demands
  • Globalization
  • Changing business models

Final thoughts

Companies like BMC are a trusted leader in AIOps, deploying ML and advanced analytics as part of holistic monitoring, event management, capacity, and automation solutions to help ITOps run at the speed that digital business demands. AIOps can help reduce event noise, incidents, time to identify the root cause, and MTTR. AIOps and IoT are comingled and complementary—to deal with the multifaceted nature of the IoT framework, you need AIOps. To learn more about AIOps, visit our blog section on the subject here.

Originally published on LinkedIn.

Get the free 2021 Gartner Market Guide for AIOps Platforms

Artificial intelligence is already changing the way IT Ops groups work—but what’s the full potential of this technology, and how best can you realize it? Get your copy of the latest Gartner AIOps Guide to learn more.


These postings are my own and do not necessarily represent BMC's position, strategies, or opinion.

See an error or have a suggestion? Please let us know by emailing blogs@bmc.com.

BMC Bring the A-Game

From core to cloud to edge, BMC delivers the software and services that enable nearly 10,000 global customers, including 84% of the Forbes Global 100, to thrive in their ongoing evolution to an Autonomous Digital Enterprise.
Learn more about BMC ›

About the author

Sam Lakkundi

Sam Lakkundi is an entrepreneurial technology and business innovation leader with a proven track record of global scale achievements in envisioning and building intelligent technologies. He applies them to solve real-world problems to accelerate the digital and cognitive transformation of businesses, services, and machines. Through the course of his career, Sam has assumed different global leadership roles at enterprise software companies with continuously increasing technical, financial, and managerial responsibilities. Additionally, he is actively engaged with and serves on the board of different technology companies and non-profit organizations. Sam has two masters and currently working on his doctorate and speaks 4 languages.