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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

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

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

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...