Simplify IT operations with observability and AIOps

BrandPost By Jeff Miller
Mar 11, 20244 mins
IT Leadership

IT teams face multiple operational challenges that can be effectively addressed with the right observability and AIOps solution.

Social media concept. Communication network
Credit: metamorworks

IT organizations are taxed with managing, maintaining, and augmenting complex IT infrastructures that are constantly evolving. At the same time, they must deliver consistent IT service performance and availability to end users, while enabling innovative digital transformation for the business.

And yet, IT teams face significant challenges, including:

• Addressing information overload
• Predicting capacity planning
• Assessing risks that are sometimes unknown
• Meeting complicated regulatory standards

Complexity is the common thread that runs through these challenges. However, an integrated observability and AIOps solution can help IT teams unravel that thread and simplify IT operations.

AIOps, combined with observability capabilities, helps unearth patterns in data to provide a holistic view of the entire environment. It also identifies issues before they become problems, and reduces the amount of noise generated by alerts, while automatically remediating low-level problems without requiring human intervention.

Not all platforms, however, provide the key capabilities required to enable AIOps and observability functionality. For example, AI can only provide valuable insights if it has access to a wide array of data about the IT environment — such as logs, events, tickets, etc. The platform should natively collect this raw data and/or integrate with systems to access it.

“Vendors that take in filtered data or offload key processing of raw data leave customers without complete insights and a limited ability to act before business issues arise,” according to a recent Forrester Wave™ report.

Also, the platform should provide comprehensive, automated remediation capabilities. IT professionals are already overwhelmed by alerts and tasks. Unless the AIOps platform can automatically remediate the low-risk issues it detects, it will fail to provide much value. As Forrester notes, “Current IT landscape complexity and the speed of business require AIOps solutions to execute remediations when needed.”

The Forrester report identifies BMC Helix IT Operations Management (ITOM) as a leader in AIOps, citing the following in their vendor profile:

• Noise reduction: IT professionals no longer waste time on inconsequential alerts because the platform identifies them as noise. According to the report, “Reference customers raved about how easy it was to integrate data sources. One noted that an internal team was ‘blown out of the water’ by the noise reduction and predictive analytics capabilities. ”

• Blueprints: BMC Helix ITOM uses blueprint-based service modeling to bring together topology from a wide array of tools. According to the report, “The blueprint-based service modeling capability uses a modular design to stitch together topology from DEM, application performance management (APM), IT infrastructure management, and network performance monitoring tools. It works across major cloud providers and on-premises infrastructure to enable business insights.”

• Predictive AI: According to the report, BMC’s “superior vision focuses on unifying service and operations management, leveraging AI/ML technology for proactive insights, fostering cross-team collaboration, and enabling a business-centric preventative IT approach.” As noted in the quote above, one reference customer was very impressed by BMC’s predictive capabilities.

BMC Helix enables AIOps and observability functionality to simplify IT operations in complex environments. “BMC is a good fit for enterprises with complex and diverse environments that span mainframe to cloud and everything in between,” according to the Forrester report.

Learn more about AIOps and the BMC Helix platform by reading the full Forrester report. The Forrester Wave™: Process-Centric AI For IT Operations (AIOps), Q2 2023.