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Pandemic Continues to Drive Digital Transformation

Companies have significantly sped up their digital transformation efforts in the past year, a theme anticipated to persist beyond the pandemic, according to the 2021 State of Application Strategy from F5. With limited in-person interactions, applications — and the digital experiences they facilitate — have become synonymous with an organization's presence and ability to thrive.


"This year's report highlights the many contrasting priorities that IT teams are currently facing. Of course, there's the familiar one of flexibility and convenience versus security, but then you also have organizations generating an immense amount of data while seeking ways to extract meaningful insights from that data," said Kara Sprague, EVP and GM, BIG-IP at F5. "Similarly, we find companies relying more on automation to reduce operating costs while increasingly tailoring applications for customer-centric digital experiences. Many of these are a function of the speed in which the industry has responded to COVID — in that it forced a myriad of operational considerations, concerns and opportunities to be addressed simultaneously almost overnight."

Improving connectivity, reducing latency, ensuring security, and leveraging data insights are now even more essential, as IT teams have found it nearly impossible to keep pace with the rate of change and digitization of experiences.

Moreover, while microservices, APIs, and containers may accelerate individual application rollouts from a DevOps perspective, the reach and pervasiveness of modern apps has also resulted in heightened complexity — with many organizations lacking the skill sets to truly streamline deployments. This is especially the case when managing broader application portfolios that span multiple generations of application architectures.

Correspondingly, this new research centers on the following four trends, pointing to an elevated interest in cloud and as-a-service offerings, edge computing, and application security and delivery technologies that require less expertise to deploy and manage while providing out-of-the-box insights.

1. Continued Modernization of Apps and Architectures to Enable Better Digital Experiences

According to the survey, 87% of organizations operate both modern and traditional architectures, with modernization deemed necessary when legacy systems are too rigid to adapt to rapidly changing business conditions.

More than three-quarters of respondents (77%) reported that they are presently modernizing internal or customer-facing applications, with APIs as the primary method given their ability to combine capabilities of traditional and modern application components.

In addition, the percentage of organizations maintaining multiple app architectures is growing, with the survey also affirming that as-a-service and managed service offerings continue to be viewed as replacements for some applications where vendors can provide cloud-friendly alternatives.

2. The Rise of the Edge as Containerization Expands

Edge computing generally refers to operations performed outside of a centralized data center. With employees and consumers logging on from increasingly distributed locations, edge computing has been identified as a significant means to reduce latency and increase the real-time responsiveness required by today's applications.

Accordingly, the edge must evolve to better support modular application components such as containers residing across multiple cloud locations. In addition to promoting faster and more efficient deployments, placing containerized applications at the edge can improve scalability and the customer experience.

Demonstrating an appetite for these advantages, survey results note that 76% of organizations have implemented or are actively planning edge deployments, with improving application performance and collecting data/enabling analytics as the primary drivers.

3. Accelerating Growth in SaaS and Cloud Deployments, Balancing Flexibility and Security

With the percentage of applications deployed in the cloud rising‚ more than two-thirds of respondents (68%) are also hosting at least some of their application security and delivery technologies in the cloud.

Simultaneously, organizations are positioning themselves to address the architectural complexity that results from adding SaaS and edge solutions, maintaining on-premises and multi-cloud environments, and modernizing applications.

Successful integration of these elements within a cohesive application strategy will require up-leveling how tools, skill sets, IT processes, and analytics are applied across dynamic architectures. Security continues to be a key driver, with efforts to stay ahead of attackers frequently requiring capabilities beyond what organizations have the resources to manage on premises.

Further highlighting this challenge, SaaS for security was identified as the top strategic trend among survey respondents.

4. The Importance of Telemetry in Meeting Evolving Customer and Business Expectations

Harnessing telemetry to turn large volumes of data into business insights is essential for adaptive applications. Even still, an overwhelming 95% of respondents believe they are missing insights related to performance, security, and availability, indicating a desire for a much clearer end-to-end picture than their current monitoring and analytics solutions provide.

Individuals across organizational roles were in uniform agreement on the topic, citing the top three insights missed as: the root cause of application issues; performance degradation causes; and potential attack details.

In parallel, nearly three-quarters of respondents intend to leverage AI to better utilize telemetry data, and more than half are looking toward AI to help their organizations transition to applications that can automatically adapt to better defend themselves and respond to changing conditions.

Methodology: The report represents more than 1,500 respondents worldwide from a breadth of industries, organization sizes, and professional roles. Fundamentally, the survey focused on IT decision-makers to best highlight the priorities, concerns, and expectations of those most responsible for meeting the toughest challenges of today's digital economy. Together, their responses form a compelling perspective of how organizations are evolving application strategies to better serve the current and anticipated needs of customers.

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 ...

Pandemic Continues to Drive Digital Transformation

Companies have significantly sped up their digital transformation efforts in the past year, a theme anticipated to persist beyond the pandemic, according to the 2021 State of Application Strategy from F5. With limited in-person interactions, applications — and the digital experiences they facilitate — have become synonymous with an organization's presence and ability to thrive.


"This year's report highlights the many contrasting priorities that IT teams are currently facing. Of course, there's the familiar one of flexibility and convenience versus security, but then you also have organizations generating an immense amount of data while seeking ways to extract meaningful insights from that data," said Kara Sprague, EVP and GM, BIG-IP at F5. "Similarly, we find companies relying more on automation to reduce operating costs while increasingly tailoring applications for customer-centric digital experiences. Many of these are a function of the speed in which the industry has responded to COVID — in that it forced a myriad of operational considerations, concerns and opportunities to be addressed simultaneously almost overnight."

Improving connectivity, reducing latency, ensuring security, and leveraging data insights are now even more essential, as IT teams have found it nearly impossible to keep pace with the rate of change and digitization of experiences.

Moreover, while microservices, APIs, and containers may accelerate individual application rollouts from a DevOps perspective, the reach and pervasiveness of modern apps has also resulted in heightened complexity — with many organizations lacking the skill sets to truly streamline deployments. This is especially the case when managing broader application portfolios that span multiple generations of application architectures.

Correspondingly, this new research centers on the following four trends, pointing to an elevated interest in cloud and as-a-service offerings, edge computing, and application security and delivery technologies that require less expertise to deploy and manage while providing out-of-the-box insights.

1. Continued Modernization of Apps and Architectures to Enable Better Digital Experiences

According to the survey, 87% of organizations operate both modern and traditional architectures, with modernization deemed necessary when legacy systems are too rigid to adapt to rapidly changing business conditions.

More than three-quarters of respondents (77%) reported that they are presently modernizing internal or customer-facing applications, with APIs as the primary method given their ability to combine capabilities of traditional and modern application components.

In addition, the percentage of organizations maintaining multiple app architectures is growing, with the survey also affirming that as-a-service and managed service offerings continue to be viewed as replacements for some applications where vendors can provide cloud-friendly alternatives.

2. The Rise of the Edge as Containerization Expands

Edge computing generally refers to operations performed outside of a centralized data center. With employees and consumers logging on from increasingly distributed locations, edge computing has been identified as a significant means to reduce latency and increase the real-time responsiveness required by today's applications.

Accordingly, the edge must evolve to better support modular application components such as containers residing across multiple cloud locations. In addition to promoting faster and more efficient deployments, placing containerized applications at the edge can improve scalability and the customer experience.

Demonstrating an appetite for these advantages, survey results note that 76% of organizations have implemented or are actively planning edge deployments, with improving application performance and collecting data/enabling analytics as the primary drivers.

3. Accelerating Growth in SaaS and Cloud Deployments, Balancing Flexibility and Security

With the percentage of applications deployed in the cloud rising‚ more than two-thirds of respondents (68%) are also hosting at least some of their application security and delivery technologies in the cloud.

Simultaneously, organizations are positioning themselves to address the architectural complexity that results from adding SaaS and edge solutions, maintaining on-premises and multi-cloud environments, and modernizing applications.

Successful integration of these elements within a cohesive application strategy will require up-leveling how tools, skill sets, IT processes, and analytics are applied across dynamic architectures. Security continues to be a key driver, with efforts to stay ahead of attackers frequently requiring capabilities beyond what organizations have the resources to manage on premises.

Further highlighting this challenge, SaaS for security was identified as the top strategic trend among survey respondents.

4. The Importance of Telemetry in Meeting Evolving Customer and Business Expectations

Harnessing telemetry to turn large volumes of data into business insights is essential for adaptive applications. Even still, an overwhelming 95% of respondents believe they are missing insights related to performance, security, and availability, indicating a desire for a much clearer end-to-end picture than their current monitoring and analytics solutions provide.

Individuals across organizational roles were in uniform agreement on the topic, citing the top three insights missed as: the root cause of application issues; performance degradation causes; and potential attack details.

In parallel, nearly three-quarters of respondents intend to leverage AI to better utilize telemetry data, and more than half are looking toward AI to help their organizations transition to applications that can automatically adapt to better defend themselves and respond to changing conditions.

Methodology: The report represents more than 1,500 respondents worldwide from a breadth of industries, organization sizes, and professional roles. Fundamentally, the survey focused on IT decision-makers to best highlight the priorities, concerns, and expectations of those most responsible for meeting the toughest challenges of today's digital economy. Together, their responses form a compelling perspective of how organizations are evolving application strategies to better serve the current and anticipated needs of customers.

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 ...