Are Industry Clouds Taking Off? Yes and No

Arun Ramchandran
Hexaware

Cloud providers Amazon Web Services, Google Cloud and Microsoft Azure each have rolled out multiple industry-specific offerings in an attempt to better appeal to companies in specific industries, including financial services, retail, telecommunications, media, energy, to name a few.

Amazon and Google Cloud have been the most aggressive in this area, each with 20 different industry-specific cloud offerings.

In some ways, vertical industry clouds are a natural evolution after the general purpose cloud services (like Azure and AWS), and the horizontal function-driven SaaS platforms.

Works for Some, Not for All

While the idea of an industry-specific offering certainly has some appeal for many of the targeted customers, there are still other instances in which these offerings aren't quite the right fit.

The horizontal cloud providers haven't had the expertise in house to fully understand all of an industry's needs and restrictions (e.g., security, compliance requirements, etc.). As a result, they have been honing their industry-specific offerings using input from former industry experts. These horizontal providers have either hired former industry professionals directly or have acquired their services as the result of an acquisition.

The new employees and industry partners handle the brunt of the industry-specific refinements while the cloud providers focus on technical aspects of their technologies, like edge computing, networking, and more.

There are a few different reasons why an industry-specific cloud might not provide as many benefits as the cloud providers say they will — advantages that seem to be expected, at least at first glance.

The financial services sector provides a good example of such a difference in industry-specific cloud offerings and the needs of different customers.

While some financial services providers are somewhat narrowly focused, providing basic banking services, such as loans, checking, savings, online payments and maybe a couple of other products, others are designed to be "one-stop" financial services providers, with insurance, wealth management, robust investment services, and a host of other offerings.

Many organizations may find that an industry-specific cloud provides just what they need in terms of features. It may serve their needs much better than anything they could develop in house. It could enable them to provide their customers with cloud-based services.

However, for some of the smaller, more specialized financial services providers, an industry-specific cloud may be oversized — and therefore, overpriced — for their needs.
Still others may be concerned that their cloud-based data may not be insulated sufficiently enough from competitors using the same cloud provider. Such firms may still rely on an industry-specific cloud for some uses - but will elect to keep much of their data in house.

Another challenge is that the industries themselves keep changing, offering new products and services that previously weren't considered part of their business. The iPhone is only 15 years old, but who doesn't have at least one of those (or one or more of its competitors) today? So, an industry-specific cloud offering may be too restrictive to serve a company's needs as it expands.

Companies in the financial services, telecom, energy and other industries continue to evolve. Truist Financial Services, for example, the result of the 2019 BB&T acquisition of SunTrust Banks, has a wider customer base and selection of offerings than either bank by itself pre-merger. As a result, it is working with not one, but three different cloud providers — AWS, Google and Microsoft — to meet all of its needs.

That means the added complexity of managing different cloud providers. While such a situation may be workable for Truist, at least for now, other financial services providers wouldn't want to have the complexity of overseeing different cloud services providers.

So expect the cloud services providers to continue to continue to further refine and expand their vertical industry offerings in an attempt to capture more of these lucrative markets, but also realize that there will be a significant percentage in those industries that the cloud services providers may not be able to satisfy. The general-purpose cloud providers will co-exist with horizontal function-driven SaaS providers and the emerging vertical industry cloud platforms as part of an enterprise business value chain.

Arun "Rak" Ramchandran is a Corporate VP at Hexaware

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

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 ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

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 ...

AI Deepfakes: Rethinking Trust in the Workplace

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 ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

5 Takeaways from the Observability Forecast for Media and Entertainment

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 ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

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

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

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 ...

Are Industry Clouds Taking Off? Yes and No

Arun Ramchandran
Hexaware

Cloud providers Amazon Web Services, Google Cloud and Microsoft Azure each have rolled out multiple industry-specific offerings in an attempt to better appeal to companies in specific industries, including financial services, retail, telecommunications, media, energy, to name a few.

Amazon and Google Cloud have been the most aggressive in this area, each with 20 different industry-specific cloud offerings.

In some ways, vertical industry clouds are a natural evolution after the general purpose cloud services (like Azure and AWS), and the horizontal function-driven SaaS platforms.

Works for Some, Not for All

While the idea of an industry-specific offering certainly has some appeal for many of the targeted customers, there are still other instances in which these offerings aren't quite the right fit.

The horizontal cloud providers haven't had the expertise in house to fully understand all of an industry's needs and restrictions (e.g., security, compliance requirements, etc.). As a result, they have been honing their industry-specific offerings using input from former industry experts. These horizontal providers have either hired former industry professionals directly or have acquired their services as the result of an acquisition.

The new employees and industry partners handle the brunt of the industry-specific refinements while the cloud providers focus on technical aspects of their technologies, like edge computing, networking, and more.

There are a few different reasons why an industry-specific cloud might not provide as many benefits as the cloud providers say they will — advantages that seem to be expected, at least at first glance.

The financial services sector provides a good example of such a difference in industry-specific cloud offerings and the needs of different customers.

While some financial services providers are somewhat narrowly focused, providing basic banking services, such as loans, checking, savings, online payments and maybe a couple of other products, others are designed to be "one-stop" financial services providers, with insurance, wealth management, robust investment services, and a host of other offerings.

Many organizations may find that an industry-specific cloud provides just what they need in terms of features. It may serve their needs much better than anything they could develop in house. It could enable them to provide their customers with cloud-based services.

However, for some of the smaller, more specialized financial services providers, an industry-specific cloud may be oversized — and therefore, overpriced — for their needs.
Still others may be concerned that their cloud-based data may not be insulated sufficiently enough from competitors using the same cloud provider. Such firms may still rely on an industry-specific cloud for some uses - but will elect to keep much of their data in house.

Another challenge is that the industries themselves keep changing, offering new products and services that previously weren't considered part of their business. The iPhone is only 15 years old, but who doesn't have at least one of those (or one or more of its competitors) today? So, an industry-specific cloud offering may be too restrictive to serve a company's needs as it expands.

Companies in the financial services, telecom, energy and other industries continue to evolve. Truist Financial Services, for example, the result of the 2019 BB&T acquisition of SunTrust Banks, has a wider customer base and selection of offerings than either bank by itself pre-merger. As a result, it is working with not one, but three different cloud providers — AWS, Google and Microsoft — to meet all of its needs.

That means the added complexity of managing different cloud providers. While such a situation may be workable for Truist, at least for now, other financial services providers wouldn't want to have the complexity of overseeing different cloud services providers.

So expect the cloud services providers to continue to continue to further refine and expand their vertical industry offerings in an attempt to capture more of these lucrative markets, but also realize that there will be a significant percentage in those industries that the cloud services providers may not be able to satisfy. The general-purpose cloud providers will co-exist with horizontal function-driven SaaS providers and the emerging vertical industry cloud platforms as part of an enterprise business value chain.

Arun "Rak" Ramchandran is a Corporate VP at Hexaware

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

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 ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

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 ...

AI Deepfakes: Rethinking Trust in the Workplace

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 ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

5 Takeaways from the Observability Forecast for Media and Entertainment

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 ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

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

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

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 ...