Skip to main content

We Are in the Model T Era of Hybrid Cloud

Kash Shaikh
Virtana

The Model T automobile was introduced in 1908. Then known as horseless carriages, Henry Ford wanted it to be "affordable, simple to operate, and durable." As one of the first mass production vehicles, it made owning a car attainable for the masses. It came in a choice of one color: black. It was offered in several body styles mounted on a uniform 100-inch-wheelbase chassis: a five-seat touring car, a two-seat runabout, and a seven-seat town car.

Within a few years, competitors arrived on the scene including relic names such as Overland, Maxwell, and names that survived like Buick and Dodge.

So, what does this have to do with the hybrid cloud market? From a business perspective — a lot. This evolution of the automobile from Model T to dozens of competitors by the 50s, to hundreds of auto choices today, is the classic evolution of markets whether it be B2C or B2B.

Boxed software emerged in the 80s, it evolved to online/on demand. And, then in the past decade, tech and the world have been flooded by data. During the growth of this tsunami of data, large enterprises have kept most of their data on-premises. In fact, Gartner "predicts that by 2025, 85% of infrastructure strategies will integrate on-premises, colocation, cloud and edge delivery options, compared with 20% in 2020." Bottom line is that with just 20% of enterprise applications having been moved from on-site data centers to the public cloud — we are at the start of hybrid cloud with four major players: AWS, Azure, IBM and Google Cloud.

So, perhaps we can equate this to 1915 in the auto industry when there was the Model T and a few strong competitors. The Model T of cloud is AWS.

The public cloud is affordable for cloud-native companies that start in the cloud, but a huge risk for large enterprises. Most enterprises that started on-premises are stuck in the public cloud migration starting blocks. The issue is fear of moving critical workloads and needing to repatriate them.

Our own survey of IT decision makers revealed that most enterprises (95%) say they have moved some applications to the cloud, but not without difficulty. Seventy-two percent (72%) of the enterprises had to move one or more of their migrated applications or workloads back on-premises. Top reasons for this move back, were the following:

■ The applications should not have been moved to a public cloud in the first place (41%)

■ Technical issues associated with public cloud provisioning (36%)

■ Degradation of performance (29%)

■ Unexpected cloud costs (20%)

The critical issue for companies is needing to know projected performance before they move applications to the cloud. Large enterprises need to understand application dependencies before they migrate. This may be even more important than cost. In fact, application dependency is subsumed in the top three issues above facing large enterprises.

While enterprises have most applications "on hold" for public migration, the cloud market is about to get much more complex.

A subtle but very important component to watch is the expansion of public cloud providers into industry verticals. This battle matters because the market is huge, and it involves a different set of very large competitors from the on-premises sector.

As more mature companies move up the digital technology stack, the ground game to monitor is who is capturing loyalty from key verticals to win loyalty. The Big 4 hyper-scalers are all aggressively targeting the hybrid cloud market.

Thomas Kurian, Google Cloud CEO, recently announced that the company is selling enterprise companies on the fact that it can target individual industries better than anyone else. It is targeting retail, healthcare, financial services, media and entertainment, and manufacturing — and each has different selling points.

So, we will move quickly from the Big 4 to hundreds of providers with industry specific solutions. If we think about the tens of thousands of applications that large enterprises can consider moving off-premises to the public cloud, and marry that with not four, but hundreds of choices of cloud providers — the complexity of cloud choice will grow exponentially.

The bottom line is that the cloud wars have only begun

The bottom line is that the cloud wars have only begun. And they will be splintering into hundreds of battles by industry sector. On the cloud provider side, look for winners to emerge in media, entertainment, healthcare, and more. From the enterprise point of view, the challenges of making the wrong hybrid move will only increase.

So, what do enterprises need? Likely, a way to test drive a number of cloud providers at once so they know before they go.

Kash Shaikh is CEO and President of Virtana

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

We Are in the Model T Era of Hybrid Cloud

Kash Shaikh
Virtana

The Model T automobile was introduced in 1908. Then known as horseless carriages, Henry Ford wanted it to be "affordable, simple to operate, and durable." As one of the first mass production vehicles, it made owning a car attainable for the masses. It came in a choice of one color: black. It was offered in several body styles mounted on a uniform 100-inch-wheelbase chassis: a five-seat touring car, a two-seat runabout, and a seven-seat town car.

Within a few years, competitors arrived on the scene including relic names such as Overland, Maxwell, and names that survived like Buick and Dodge.

So, what does this have to do with the hybrid cloud market? From a business perspective — a lot. This evolution of the automobile from Model T to dozens of competitors by the 50s, to hundreds of auto choices today, is the classic evolution of markets whether it be B2C or B2B.

Boxed software emerged in the 80s, it evolved to online/on demand. And, then in the past decade, tech and the world have been flooded by data. During the growth of this tsunami of data, large enterprises have kept most of their data on-premises. In fact, Gartner "predicts that by 2025, 85% of infrastructure strategies will integrate on-premises, colocation, cloud and edge delivery options, compared with 20% in 2020." Bottom line is that with just 20% of enterprise applications having been moved from on-site data centers to the public cloud — we are at the start of hybrid cloud with four major players: AWS, Azure, IBM and Google Cloud.

So, perhaps we can equate this to 1915 in the auto industry when there was the Model T and a few strong competitors. The Model T of cloud is AWS.

The public cloud is affordable for cloud-native companies that start in the cloud, but a huge risk for large enterprises. Most enterprises that started on-premises are stuck in the public cloud migration starting blocks. The issue is fear of moving critical workloads and needing to repatriate them.

Our own survey of IT decision makers revealed that most enterprises (95%) say they have moved some applications to the cloud, but not without difficulty. Seventy-two percent (72%) of the enterprises had to move one or more of their migrated applications or workloads back on-premises. Top reasons for this move back, were the following:

■ The applications should not have been moved to a public cloud in the first place (41%)

■ Technical issues associated with public cloud provisioning (36%)

■ Degradation of performance (29%)

■ Unexpected cloud costs (20%)

The critical issue for companies is needing to know projected performance before they move applications to the cloud. Large enterprises need to understand application dependencies before they migrate. This may be even more important than cost. In fact, application dependency is subsumed in the top three issues above facing large enterprises.

While enterprises have most applications "on hold" for public migration, the cloud market is about to get much more complex.

A subtle but very important component to watch is the expansion of public cloud providers into industry verticals. This battle matters because the market is huge, and it involves a different set of very large competitors from the on-premises sector.

As more mature companies move up the digital technology stack, the ground game to monitor is who is capturing loyalty from key verticals to win loyalty. The Big 4 hyper-scalers are all aggressively targeting the hybrid cloud market.

Thomas Kurian, Google Cloud CEO, recently announced that the company is selling enterprise companies on the fact that it can target individual industries better than anyone else. It is targeting retail, healthcare, financial services, media and entertainment, and manufacturing — and each has different selling points.

So, we will move quickly from the Big 4 to hundreds of providers with industry specific solutions. If we think about the tens of thousands of applications that large enterprises can consider moving off-premises to the public cloud, and marry that with not four, but hundreds of choices of cloud providers — the complexity of cloud choice will grow exponentially.

The bottom line is that the cloud wars have only begun

The bottom line is that the cloud wars have only begun. And they will be splintering into hundreds of battles by industry sector. On the cloud provider side, look for winners to emerge in media, entertainment, healthcare, and more. From the enterprise point of view, the challenges of making the wrong hybrid move will only increase.

So, what do enterprises need? Likely, a way to test drive a number of cloud providers at once so they know before they go.

Kash Shaikh is CEO and President of Virtana

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...