41% of Surveyed U.K. IT Staffs Investing in AIOps in 2021

As some observers note,  if all an enterprise is doing is monitoring bare-metal servers and networks in its own data center, “you can probably keep on using your legacy monitoring tools.”

Cloud computing, most would agree, changes matters. Applications running virtually, using cloud service providers plus in-house resources require a new set of monitoring tools. 

In 2021, U.K. technology executives have prioritized information technology operations management  tool investments such as hybrid infrastructure monitoring (51 percent), AIOps (48 percent), and cloud native observability (47 percent). Digital experience monitoring (46 percent) and Application performance monitoring (46 percent) tools are right behind, says OpsRamp, citing research by McKinsey Global. 

source: OpsRamp 

“Siloed tools have historically created problems for hybrid infrastructure management as they offer limited context for assessing the health and performance of an IT service,” says OpsRamp. “Our survey shows AIOps (48 percent) is a focus area for tools consolidation, though it trails network performance monitoring (56 percent) and hybrid infrastructure monitoring (54 percent).”

IBM Buys Turbonomic for Hybrid Cloud AIOps

IBM is acquiring Turbonomic, an application resource management (ARM) and network performance management (NPM) software provider based in Boston, Mass. 

IBM says the acquisition will make it “the only company that will be able to provide customers with AI-powered automation capabilities that span from AIOps (the use of AI to automate IT operations) to application and infrastructure observability, all built on Red Hat OpenShift to run across any hybrid cloud environment.” 

The acquisition will provide businesses with “full stack application observability and management” of containers, virtual machines, servers, storage, networks, and databases, IBM says, while also providing such value at lower cost in hybrid cloud environments. 

The acquisition complements IBM's recent acquisition of Instana for application performance monitoring (APM) and observability, and the launch of IBM Cloud Pak for Watson AIOps to automate IT Operations using AI. 

What is a Load Balancer?

Technologist Frank Yue explains

Masergy AIOps

Complexity Drives AIOps Interest

Complexity has been one reason for interest in AIOps. 

In the last year, the number of enterprises with over 500 known applications has grown by almost 50 percent, from 32 percent to 47 percent of respondents In parallel, those reporting greater than 20 SaaS applications grew by 37 percent, from 24 percent to 33 percent, according to Aryaka Networks’ State of the WAN report. 

With growth comes complexity, which is still the #1 issue for IT on par with last year at 37 percent, followed by slow application access (33 percent) and performance (32 percent). One area that stood out was cost, identified by 20 percent in 2021 vs 16 percent in 2020, a 25 percent rise. IT Time Sinks: Complexity results in increased resource requirements, spanning slow performance for both the branch and remote workers (44 percent), security breaches (38 percent), integration of cloud and SaaS applications (36 percent), and managing telcos (33 percent).

AIOps for Anomaly Detection

Mid-Size Firm AI Adoption is Likely Mostly Happening as they Adopt Cloud-based Enterprise Apps

For most companies and people, artificial intelligence is not a product, but a capability possessed by a cloud-based business application, such as customer relationship management, enterprise resource planning, supply chain management, or human capital management. 

For that reason, mid-size firms “adopting” AI are largely doing so by adopting cloud-based enterprise applications. 

source: Deloitte