IBM Is Bringing AIOps for Enterprises, Grabs Turbonomic Along the Way

IBM is making strides in the development of hybrid cloud-based solutions to automate IT operations for enterprises. The company has announced the acquisition of application resource management vendor Turbonomic as  part of its strategy to deliver AIOps solutions for enterprises leveraging hybrid cloud.

IBM last Thursday announced their acquisition of Turbonomic, a Boston-based company neck- deep in provisioning application resource management (ARM). Terms of the deal remain undisclosed by both companies, however, it stands to reason that the acquisition may have cost IBM upwards of $1 billion since Turbonomic was valued at $963 millionOpens a new window following its $70 million Series E-4 round in September 2019.

And if ReutersOpens a new window ‘ sources are to be believed, the acquisition may have fetched Turbonomic shareholders as much as $1.5 billion, but not more than $2 billion. The acquisition of Turbonomic comes months after the New York-based tech multinational took over Instana, it’s first venture into application performance monitoring (APM).

IBM’s Journey to AIOps via Hybrid Cloud

The move is a part of IBM’s strategy to provide observability into business IT applications, and automate task execution through artificial intelligence, built and delivered over its in-house Red Hat OpenShiftOpens a new window hybrid cloud. Red Hat, an open source vendor of enterprise software solutions such as Linux, cloud, containers, and Kubernetes, became a part of the IBM ecosystem in July 2019 costing $34 billion, its highest ever splurge yet.

IBM’s takeover of Turbonomic may be its second-biggest acquisition ever and the 11th since Arvind KrishnaOpens a new window took over the reins of the company in April 2020. Red Hat was IBM’s attempt at making a mark in the hybrid cloud space. The next step was to develop a portfolio of differentiated services, each pertaining to specific use cases.

That’s why IBM, which happens to be one of the earliest pioneers of the personal computer, launched multiple hybrid cloud-based services last year pertaining to 5G edge and AI, some of the most anticipated technologies that have one of the fastest growth rates. This hybrid cloud approach is quite different from delivering public cloud-driven services, which have the tendency to become homogeneous for enterprise clients.

Harish GramaOpens a new window , General Manager at IBM Cloud recently told Toolbox why adoption of hybrid cloud is consistently growing. Watch the interview:

See Also: Hybrid Cloud Settles In for the Long Haul. Here’s What to Consider Before Migration

IBM’s foray into hybrid cloud was equally important as its AI-driven business automation service that allowed users to automate regular tasks. IBM also launched Watson AIOps, which is an AIOps (AI for IT Operations) solution that can be leveraged to assess, diagnose, and resolve incidents across mission-critical workloads.

“Turbonomic is the next piece in our strategy around automation. We can bring distribution advantage plus integrating it into our AI ops strategy,” said Rob Thomas, SVP of IBM Cloud and Data Platform.

Application Resource Management 

The need for automated ARM is evident, at least to 67% respondents of an IDG surveyOpens a new window , who are of the opinion that IT modernization is essential for successful and effective business transformation while it streamlines IT operations.

ARM is basically a way for IT teams to decide on the allocation of compute, storage, and network resources for IT operations in real-time. It consists of tools to track performance, utilization, and availability of resources or assets. But without AI, the process may become a tad cumbersome to say the least. Vishwanath JakkaOpens a new window , Product Manager, Compute and Cloud at Cisco explained the importance of AI for ARM.

“To streamline processes and efficiently balance application performance and cost, the only choice is to automate resource management and decisions for workload placement and optimization,” Jakka saidOpens a new window . “But deciding what workloads to run on which platform, making real-time changes as required to ensure optimal performance and cost across any environment, monitoring and troubleshooting with minimum disruption, are all tasks that take time and resources. And as complexity increases, more and more human resources are required.”

Jakka adds, “To optimize an environment end-to-end, you need access to a constant stream of telemetry data from dozens, hundreds, perhaps thousands of sources. Correlating and continuously analyzing all this data with an intelligent real-time decision engine to understand how everything fits together now and in the future is the way forward. A new generation of open tooling is required to connect all the dots and offer the insights and automated actions to stay ahead of demand, stay ahead of problems, and respond to new projects with confidence.”

Turbonomic Acquisition

Expected to close in Q2 2021, IBM’s deal to acquire Turbonomic follows a couple of other acquisitions besides Instana made recently such as process mining company myInvenioOpens a new window , RPA-vendor and WDG AutomationOpens a new window .

Exactly a year ago, IBM and Turbonomic had entered an original equipment manufacturer (OEM) partnershipOpens a new window to ship the latter’s ARM products under the IBM ARM brand.

Now, Turbonomic’s ARM solutions will be integrated with IBM’s Watson AIOps and Instana’s APM solutions to bring real-time observability into IT operations and to automate them, thus becoming AIOps.

So, let’s say if a certain resource like network bandwidth is allocated but remains unutilized or underutilized, there need not be any major human involvement. The AIOps solution will take care of it by either shutting it down or suggesting a more prudent bandwidth allocation, which will:

• Save time
• Reduce costs
• Add value to the operation
• Improve operational efficiency/productivity

See Also: AIOps, Not ITOps Will Help Enterprises Manage Modern Environments in 2021

Conclusion

The biggest takeaway from the acquisition is the potential it presents to optimize ARM, especially for hybrid cloud architectures, which can prove to be more than a bit difficult to manage.The current deals clears the deck for all IBM partners with clients applications on a hybrid cloud, to embed the AI story therein with actionability and observability using Turbonomic. This consolidation really drives cost savings because now when resources are inactive, it’s easy to shut them down.

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