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Cloud-Native Architectures Break Traditional Approaches to Application Security

The rising adoption of cloud-native architectures, DevOps, and agile methodologies has broken traditional approaches to application security, according to Precise, automatic risk and impact assessment is key for DevSecOps, a new report from Dynatrace, based on an independent global survey of 700 CISOs.


As organizations shift more responsibility "left" to developers to accelerate innovation, increasingly complex IT ecosystems and outdated security tooling can slow releases by leaving blind spots and forcing teams to manually triage countless alerts, many of which are false positives reflecting vulnerabilities in libraries that are not used in production.

Organizations are calling for a new approach that is optimized for multicloud environments, Kubernetes, and DevSecOps.

This research reveals:

■ 89% of CISOs say microservices, containers, and Kubernetes have created application security blind spots.

■ 97% of organizations do not have real-time visibility into runtime vulnerabilities in containerized production environments.

■ Nearly two-thirds (63%) of CISOs say DevOps and Agile development have made it more difficult to detect and manage software vulnerabilities.

■ 74% of CISOs say traditional security controls such as vulnerability scanners no longer fit today's cloud-native world.

■ 71% of CISOs admit they are not fully confident code is free of vulnerabilities before going live in production.

"The increased use of cloud-native architectures has fundamentally broken traditional approaches to application security," said Bernd Greifeneder, Founder and Chief Technology Officer at Dynatrace. "This research confirms what we've long anticipated: manual vulnerability scans and impact assessments are no longer able to keep up with the pace of change in today's dynamic cloud environments and rapid innovation cycles. Risk assessment has become nearly impossible due to the growing number of internal and external service dependencies, runtime dynamics, continuous delivery, and polyglot software development which uses an ever-growing number of third-party technologies. Already stretched teams are forced to choose between speed and security, exposing their organizations to unnecessary risk."

Additional findings include:

■ On average, organizations need to react to 2,169 new alerts of potential application security vulnerabilities each month.

■ 77% of CISOs say most security alerts and vulnerabilities are false positives that do not require actioning as they are not actual exposures.

■ 68% of CISOs say the volume of alerts makes it very difficult to prioritize vulnerabilities based on risk and impact.

■ 64% of CISOs say developers do not always have time to resolve vulnerabilities before code moves into production.

■ 77% of CISOs say the only way for security to keep up with modern cloud-native application environments is to replace manual deployment, configuration, and management with automated approaches.

■ 28% of CISOs say application teams sometimes bypass vulnerability scans to speed up software delivery.

"As organizations embrace DevSecOps, they also need to give their teams solutions that offer automatic, continuous, and real-time risk and impact analysis for every vulnerability, across both pre-production and production environments, and not based on point-in-time 'snapshots'," continued Greifeneder.

Methodology: The report is based on a global survey of 700 CISOs in large enterprises with over 1,000 employees, conducted by Coleman Parkes and commissioned by Dynatrace in 2021. The sample included 200 respondents in the US, 100 in the UK, France, Germany, and Spain, and 50 in Brazil and Mexico, respectively.

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Cloud-Native Architectures Break Traditional Approaches to Application Security

The rising adoption of cloud-native architectures, DevOps, and agile methodologies has broken traditional approaches to application security, according to Precise, automatic risk and impact assessment is key for DevSecOps, a new report from Dynatrace, based on an independent global survey of 700 CISOs.


As organizations shift more responsibility "left" to developers to accelerate innovation, increasingly complex IT ecosystems and outdated security tooling can slow releases by leaving blind spots and forcing teams to manually triage countless alerts, many of which are false positives reflecting vulnerabilities in libraries that are not used in production.

Organizations are calling for a new approach that is optimized for multicloud environments, Kubernetes, and DevSecOps.

This research reveals:

■ 89% of CISOs say microservices, containers, and Kubernetes have created application security blind spots.

■ 97% of organizations do not have real-time visibility into runtime vulnerabilities in containerized production environments.

■ Nearly two-thirds (63%) of CISOs say DevOps and Agile development have made it more difficult to detect and manage software vulnerabilities.

■ 74% of CISOs say traditional security controls such as vulnerability scanners no longer fit today's cloud-native world.

■ 71% of CISOs admit they are not fully confident code is free of vulnerabilities before going live in production.

"The increased use of cloud-native architectures has fundamentally broken traditional approaches to application security," said Bernd Greifeneder, Founder and Chief Technology Officer at Dynatrace. "This research confirms what we've long anticipated: manual vulnerability scans and impact assessments are no longer able to keep up with the pace of change in today's dynamic cloud environments and rapid innovation cycles. Risk assessment has become nearly impossible due to the growing number of internal and external service dependencies, runtime dynamics, continuous delivery, and polyglot software development which uses an ever-growing number of third-party technologies. Already stretched teams are forced to choose between speed and security, exposing their organizations to unnecessary risk."

Additional findings include:

■ On average, organizations need to react to 2,169 new alerts of potential application security vulnerabilities each month.

■ 77% of CISOs say most security alerts and vulnerabilities are false positives that do not require actioning as they are not actual exposures.

■ 68% of CISOs say the volume of alerts makes it very difficult to prioritize vulnerabilities based on risk and impact.

■ 64% of CISOs say developers do not always have time to resolve vulnerabilities before code moves into production.

■ 77% of CISOs say the only way for security to keep up with modern cloud-native application environments is to replace manual deployment, configuration, and management with automated approaches.

■ 28% of CISOs say application teams sometimes bypass vulnerability scans to speed up software delivery.

"As organizations embrace DevSecOps, they also need to give their teams solutions that offer automatic, continuous, and real-time risk and impact analysis for every vulnerability, across both pre-production and production environments, and not based on point-in-time 'snapshots'," continued Greifeneder.

Methodology: The report is based on a global survey of 700 CISOs in large enterprises with over 1,000 employees, conducted by Coleman Parkes and commissioned by Dynatrace in 2021. The sample included 200 respondents in the US, 100 in the UK, France, Germany, and Spain, and 50 in Brazil and Mexico, respectively.

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AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...