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IBM’s hybrid cloud strategy is gaining steam

PARIS, FRANCE - MAY 16: The logo of the software and computer services company IBM is displayed during the 4th edition of the Viva Technology show at Parc des Expositions Porte de Versailles on May 16, 2019 in Paris, France. Viva Technology, the new international event brings together 9000 startups with top investors, companies to grow businesses and all players in the digital transformation who shape the future of the internet. (Photo by Chesnot/Getty Images)
IBM logo is displayed during the 4th edition of the Viva Technology show at Parc des Expositions Porte de Versailles on May 16, 2019 in Paris, France. (Photo by Chesnot/Getty Images)

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IBM continues its efforts to refocus its core business around the cloud. It all started with a landmark $34 billion acquisition of Red Hat back in 2019. This was followed by a significant changing of the guard by appointing Arvind Krishna as the new CEO after a successful run at heading the cloud and cognitive software division. Krishna was also a key catalyst in the Red Hat deal and remains committed to refocusing IBM on the cloud, which is now generating $6.3 billion in revenue, a 30% increase from last year.

In October 2020, IBM spun off its legacy technology services business to focus on cloud computing and artificial intelligence. The split reflects just how decisively computing has shifted to the cloud and IBM’s pivot to go after the cloud market opportunity.

A hybrid approach

IBM’s strategy is to focus on the hybrid cloud market, which allows companies to connect public cloud providers with private cloud infrastructure. Hybrid cloud solutions have key benefits around control, speed, security, cost, and speed.

However, developing an application that works across cloud providers requires a platform that abstracts specific cloud functionality and ensures portability across cloud platforms. As part of IBM’s landmark acquisition of Red Hat, it gained OpenShift, which uses an open-source platform called Kubernetes to manage application functionality in portable containers. This allows organizations to create a consistent platform across multiple cloud providers and have their applications work seamlessly across these heterogeneous environments. IBM has now released more than 100 of its software products on the OpenShift platform.

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IBM formally announced Cloud Paks in November 2020 as a natural extension of IBM’s early work in containers and to support the Kubernetes open-source project. Cloud Paks furthers those efforts by creating lightweight, modular, enterprise-grade solutions that integrate a container platform and containerized IBM middleware and open source components, such as RedHat OpenShift.

IBM has continued to acquire strategic assets that are helping further its position in the cloud and AI market. Back in November 2020, it acquired Instana to better manage the complexity of modern applications that span hybrid cloud landscape and helps IBM further its AI automation capabilities. Instana’s software solution provides monitoring and performance management of software used in microservice architectures and permits 3D visualization of performance through graphs generated using machine learning algorithms.

Previously IBM acquired WDG Automation, which provides AI-powered robotic process automation (RPA) to help companies automate mundane operational tasks and cloud deployments. IBM integrated this into its Cloud Pak offerings on Red Hat OpenShift, which now provides over 600 pre-built RPA functions to help businesses turn insights from AI into automated actions.

IBM will continue its focus on acquiring strategic assets to further its cloud-first vision. The company will also continue to forge a large number of strategic partnerships such as with Verizon, Adobe, and — just last week — Palantir and Foghorn.

It’s all about streamlining the data

Cloud is now becoming a commodity, a basic utility of computing. The power that the cloud unleashes with its elasticity, scalability, accessibility, and speed is creating the foundation for new applications never before possible.

Companies are rapidly migrating their data assets to the cloud to gain agility flexibility and lower costs. But the real power lies in leveraging sophisticated machine learning algorithms to unleash key insights in the data

However, the effort, complexity and technical specialty required to develop and deploy cloud based AI applications has been very high. There is a growing AI skills gap and shortage because these AI applications require a multidisciplinary mix of statistics, computer science, signal processing, data modeling, and domain knowledge. According to IBM, “31% of businesses cited data complexities as an obstacle to launching AI applications and 37% of them highlighted skills shortages as a major challenge.”

Last week’s IBM/Palantir announcement provides a new solution called “Palantir for IBM Cloud Pak for Data,” which leverages Palantir’s Foundry Analytics platform to supplement IBM Watson and Red Hat OpenShift services.

IBM is positioning the new offering as a “low-code/no-code” platform for deploying enterprise AI applications that provides automated data discovery, processing, and pipelining across the vast amounts of siloed data that exists in on-premises, hybrid and cloud environments. This reduces the need for deep AI skills and compresses the time it takes to deploy AI applications.

IBM is effectively merging its hybrid cloud, artificial intelligence, data processing, and operational technology into this new product aimed at business clients and targeting this strategy at helping organizations accelerate their broader digital transformation journey.

But IBM is not the only winner here. The big winner in all this could actually be Palantir as its product is now in the hands of over 2,500 IBM salespeople and, more importantly, gains access to IBM’s blue-chip enterprise clients. Palantir’s stock rose over 15% following the announcement anticipating increased demand for their products.

Intelligence at the edge

Edge computing is a distributed, cloud-era architecture constructed to handle real time data integration that is produced from millions of connected devices. Applications require real-time data processing at the edge of the network to reduce latency. There are also cost benefits to not having to send large streams of data to centralized cloud servers for processing.

Businesses are using edge computing today to create a wide variety of applications like virtual and augmented reality, smart buildings, smart cities, workspaces, retail experiences, autonomous cars, automated factories, and more.

Extending edge computing to include cognitive processing creates even more intelligence right where the applications are being used. So the partnership with Foghorn IBM announced last week is significant. It brings FogHorn’s intelligent edge software platform to IBM’s Edge Application Manager, which runs on OpenShift and manages high performance workloads on edge devices instead of sending the data to the cloud for processing.

FogHorn’s Lightning platform is cloud-agnostic, closed-loop edge-to-cloud solution that enables rapid iteration of machine learning models to help companies optimize their operations for maximal efficiency and reduction of overall costs.

A rising force

The global cloud computing market is expected to reach $623.3 billion by 2023. While AWS, Microsoft Azure, and Google Cloud are clearly leading the charge, IBM is quietly acquiring capabilities and establishing partnerships that may make it the number one provider of hybrid cloud solutions. IBM doesn’t always lead technology transformations, but throughout its 109-year existence, it has proven to be an expert at pivoting its business model. It is now clearly betting its future on the cloud.

(Disclosure: My company has a partnership with IBM. However, we also have partnerships with a number of other cloud competitors, including Google Cloud, AWS, and Microsoft Azure.)

Frank Palermo is EVP, Global Digital Solutions at Virtusa and a member of the Forbes Technology Council.

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