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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shift more responsibility "left" to developers to accelerate innovation, increasingly complex IT ecosystems and outdated security tooling can slow releases by leaving blind spots and forcing teams to manually triage countless alerts, many of which are false positives reflecting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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One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...