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IBM buys Turbonomic for AIOps, hybrid-cloud management support

News Analysis
Apr 29, 20213 mins
Cloud ManagementNetwork Management Software

By acquiring Turbonomic, IBM gains tools that manage performance of everything from applications and containers to virtualization, cloud, and on-prem compute, storage, and network resources.

IBM logo sign
Credit: Stephen Lawson/IDG

Big Blue kept its checkbook open this week buying AI-based application and network-performance management vendor Turbonomic for an unconfirmed estimate of $2 billion.

The acquisition is the eleventh hybrid-cloud and AI-focused buy since Arvind Krishna became IBM CEO in 2020. “Hybrid cloud and AI are the two dominant forces driving change for our clients and must have the maniacal focus of the entire company,” he said at that time.

The Economic Times and Reuters said the deal was worth between $1.5 billion and $2 billion and would make it the largest since IBM grabbed Red Hat for $34 Billion in 2019.

Turbonomic’s Application Resource Management (ARM) and Network Performance Management (NPM) tools assess and manage the performance of everything from applications and containers to virtualization, cloud, and on-prem compute, storage, and network resources.

Once the acquisition closes, expected in the second quarter, IBM said it plans to integrate Turbonomic’s software with the real-time application observability capabilities of Instana that it bought in November and the ITOps capabilities of IBM Cloud Pak for Watson AIOps to help assure application performance across development, test and production environments.

“With the convergence of the Instana application performance monitoring and observability platform and IBM’s AI-powered automation portfolio, including Watson AIOps, IBM has assembled a strong set of technologies to transform the IT landscape, from the software development lifecycle to operations,” wrote Pratik Gupta, CTO, IBM Hybrid Cloud Management in a blog after the Instana buy.  “This convergence will help enable enterprise IT environments to transform, realizing faster development cycles and better, more-reliable operations.”

With integrated Turbonomic ARM and Instana APM,  a user could automate actions to optimize their underlying IT infrastructure and assure performance across applications, IBM stated. 

“The Turbonomic ARM integration with IBM Cloud Pak for Watson AIOps will bolster ITOps in cross-cloud management by bridging an application’s topology to the resources on which it runs. This ensures customers can deliver quicker resolution of incidents or, if resourcing actions are automated, automatically absorb demand spikes with no degradation to end user response time,” IBM stated. 

Driving all of this technology integration is the ability to automate as many basic IT tasks as possible and help tackle problems before they occur, experts say.  “Applications are one of the biggest pain points for organizations because they want to create demand for these tools, but it can be difficult to manage their performance across hybrid and multicloud environments,”  wrote Dinesh Nirmal, General Manager, IBM Cloud Automation in a blog about the acquisition. “This can lead to significant problems, such as IT departments spending too much time focused on troubleshooting vs. innovating, wasting dollars and delivering poor response times to customers.”

Through increased visibility, insights and automated actions from ARM, organizations can prevent problems and minimize troubleshooting, helping IT employees reclaim up to 50% of their time to focus on what matters most, Nirmal stated.

“Turbonomic technology will allow organizations to monitor the performance of their applications wherever they run and better manage the performance and availability of applications across their entire enterprise,” Nirmal stated.

Turbonomic also has a relationship with Cisco, which offers Turbonomic technologies through its Intersight Workload Optimizer. Intersight is the company’s cloud-based systems-management package aimed at helping customers orchestrate multicloud workloads.