Skip to main content

Cloudy Business: How the Cloud Impacts Businesses of All Sizes

Raman Sharma
DigitalOcean

Digital acceleration took off during the pandemic, and companies are still prioritizing adapting to the digital-first world. In fact, recent surveys show 38% of companies are planning to spend more on digital transformation in 2022 than in 2021.

However, even with an increase in investment, not all organizations are on the same page of this transition. In this blog, we'll examine the findings from the latest DigitalOcean Currents report and what it reveals about the ways companies are leveraging the cloud to adapt to the digital future.

The Knowledge Gap

There is a large cloud knowledge gap between traditional small-to-medium businesses (SMBs) and enterprises.

For example, 48% of respondents from traditional SMBs are not familiar with the term "cloud native," compared to just 5% of respondents from enterprises who are not familiar with the term.

Meanwhile, 56% of respondents from traditional SMBs are not familiar with the term "digital native," compared to the 18% of respondents from enterprises who are not familiar.

Because of this knowledge gap, SMBs are interested in simpler cloud solutions. The survey found that SMBs across all industries generally have fewer technical staff than enterprises with 43% having zero full-time technical staff, and are more likely to have multiple priorities when it comes to managing cloud solutions as a result. Because of this difference, SMBs are actively seeking cloud services that reduce time spent managing infrastructure.

Given the increasing investment in digital transformation and SMBs' need for streamlined services, there will likely be an increase in the adoption of cloud services with easily manageable infrastructure in 2022.

Pandemic Recovery

While the knowledge gap is primarily a concern for SMBs, 69% of all businesses — from major enterprises to bootstrapped startups — reported the cloud was a major factor in their pandemic recovery. Of the respondents who reported increased cloud usage in 2020 due to COVID-driven digital acceleration, 82% of traditional SMBs, 83% of tech-focused SMBs, and 92% of enterprises said their cloud usage continued to increase in 2021.

The broad popularity among different-sized businesses signals that adoption won't slow down anytime soon. However, the increased adoption doesn't mean smaller businesses are not struggling to keep up with larger companies on the technology curve. The majority of businesses, regardless of size, listed the impacts of COVID-19 as the biggest challenge they face right now. But for small to medium businesses, keeping up with the technology curve is the second biggest challenge, mostly due to the perceived cost of and time needed to manage tech services.

One Size Doesn't Fit All

Beyond increased adoption rates, the survey also found different-sized businesses need different cloud architectures to meet their needs, and what works best for the enterprise could cost SMBs and startups valuable resources.

For example, multi- and hybrid cloud adoption is more prevalent among enterprises (44% multi-cloud, 44% hybrid cloud) and tech SMBs (40% multi-cloud and 36% hybrid cloud), while traditional SMBs are more likely to have a single cloud (46%).

In most cases, traditional SMBs often start with on-premise infrastructure and graduate to the cloud (51%). This is a slight difference compared to enterprise and tech-focused SMBs, who are near equally likely to be hybrid or completely cloud-based from the start (65% of enterprises, 64% of tech-focused SMBs).

However, tech-focused SMBs are most likely to consciously seek out a multi-cloud architecture to meet their needs because of limited architecture management resources as less than half of SMBs have a dedicated staff person managing infrastructure.

Going Forward

While companies of all sizes have leaned into the cloud to offset the negative impacts of COVID-19 on their business, this recent survey shows smaller companies still struggle to overcome the tech curve. Going forward, it's likely that SMBs and startups will continue to seek out simple, cost-effective and flexible cloud services and straightforward educational services/communities in order to continue to reap the benefits of the cloud and grow their businesses.

Raman Sharma is VP Product Marketing at DigitalOcean

The Latest

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 ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Cloudy Business: How the Cloud Impacts Businesses of All Sizes

Raman Sharma
DigitalOcean

Digital acceleration took off during the pandemic, and companies are still prioritizing adapting to the digital-first world. In fact, recent surveys show 38% of companies are planning to spend more on digital transformation in 2022 than in 2021.

However, even with an increase in investment, not all organizations are on the same page of this transition. In this blog, we'll examine the findings from the latest DigitalOcean Currents report and what it reveals about the ways companies are leveraging the cloud to adapt to the digital future.

The Knowledge Gap

There is a large cloud knowledge gap between traditional small-to-medium businesses (SMBs) and enterprises.

For example, 48% of respondents from traditional SMBs are not familiar with the term "cloud native," compared to just 5% of respondents from enterprises who are not familiar with the term.

Meanwhile, 56% of respondents from traditional SMBs are not familiar with the term "digital native," compared to the 18% of respondents from enterprises who are not familiar.

Because of this knowledge gap, SMBs are interested in simpler cloud solutions. The survey found that SMBs across all industries generally have fewer technical staff than enterprises with 43% having zero full-time technical staff, and are more likely to have multiple priorities when it comes to managing cloud solutions as a result. Because of this difference, SMBs are actively seeking cloud services that reduce time spent managing infrastructure.

Given the increasing investment in digital transformation and SMBs' need for streamlined services, there will likely be an increase in the adoption of cloud services with easily manageable infrastructure in 2022.

Pandemic Recovery

While the knowledge gap is primarily a concern for SMBs, 69% of all businesses — from major enterprises to bootstrapped startups — reported the cloud was a major factor in their pandemic recovery. Of the respondents who reported increased cloud usage in 2020 due to COVID-driven digital acceleration, 82% of traditional SMBs, 83% of tech-focused SMBs, and 92% of enterprises said their cloud usage continued to increase in 2021.

The broad popularity among different-sized businesses signals that adoption won't slow down anytime soon. However, the increased adoption doesn't mean smaller businesses are not struggling to keep up with larger companies on the technology curve. The majority of businesses, regardless of size, listed the impacts of COVID-19 as the biggest challenge they face right now. But for small to medium businesses, keeping up with the technology curve is the second biggest challenge, mostly due to the perceived cost of and time needed to manage tech services.

One Size Doesn't Fit All

Beyond increased adoption rates, the survey also found different-sized businesses need different cloud architectures to meet their needs, and what works best for the enterprise could cost SMBs and startups valuable resources.

For example, multi- and hybrid cloud adoption is more prevalent among enterprises (44% multi-cloud, 44% hybrid cloud) and tech SMBs (40% multi-cloud and 36% hybrid cloud), while traditional SMBs are more likely to have a single cloud (46%).

In most cases, traditional SMBs often start with on-premise infrastructure and graduate to the cloud (51%). This is a slight difference compared to enterprise and tech-focused SMBs, who are near equally likely to be hybrid or completely cloud-based from the start (65% of enterprises, 64% of tech-focused SMBs).

However, tech-focused SMBs are most likely to consciously seek out a multi-cloud architecture to meet their needs because of limited architecture management resources as less than half of SMBs have a dedicated staff person managing infrastructure.

Going Forward

While companies of all sizes have leaned into the cloud to offset the negative impacts of COVID-19 on their business, this recent survey shows smaller companies still struggle to overcome the tech curve. Going forward, it's likely that SMBs and startups will continue to seek out simple, cost-effective and flexible cloud services and straightforward educational services/communities in order to continue to reap the benefits of the cloud and grow their businesses.

Raman Sharma is VP Product Marketing at DigitalOcean

The Latest

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 ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...