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Urgency Grows for Observability and Security Convergence

Organizations find increasing difficulty in maintaining software reliability and security as the demand for continuous release cycles and the rising complexity of cloud-native environments create more risk for undetected defects and vulnerabilities to escape into production, according to the 2023 Global CIO Report, Observability and Security Convergence: Enabling Faster, More Secure Innovation in the Cloud, from Dynatrace.

CIOs and senior DevOps managers are looking to DevSecOps processes, the convergence of observability and security, and the increased use of AI and automation to balance accelerated innovation with reliability and security.

The research reveals the following:

■ 90% of organizations say digital transformation has accelerated in the past 12 months.

■ 78% of organizations deploy software updates into production every 12 hours or less, and 54% say they do so at least once every two hours.

■ DevOps teams spend nearly a third (31%) of their time on manual tasks involving detecting code quality issues and vulnerabilities, reducing the time spent on innovation.

■ 55% of organizations make tradeoffs between quality, security, and user experience to meet the need for rapid transformation.

■ 88% of CIOs say the convergence of observability and security practices will be critical to building a DevSecOps culture, and 90% say increasing the use of AIOps will be key to scaling up these practices.

"It's difficult for teams to accelerate the pace of innovation while also maintaining the highest quality and security standards," said Bernd Greifeneder, Founder and CTO at Dynatrace. "More frequent software deployments, combined with complex cloud-native architectures, make it easier for errors and vulnerabilities to escape into production where they impact customer experience and create risk. There simply aren't enough hours in the day for teams to test code as thoroughly as when they had only a single monthly deployment, but there's no margin for error in today's ultra-competitive, always-on economy. Something has to change."


Additional findings from the survey include:

■ Organizations plan to increase their spending on automation across development, security, and operations by 35% by 2024, as they invest more in continuously testing software quality (54%) and security (49%) in production, automatic vulnerability detection and blocking (41%), and automating release validation (35%).

■ 70% of CIOs say they need to improve their trust in the accuracy of AI's decisions before they can automate more of the CI/CD pipeline.

■ 94% of CIOs say extending a DevSecOps culture to more teams is key to accelerating digital transformation and driving faster, more secure software releases.

"Organizations know that manual approaches aren't scalable," continued Greifeneder. "Teams can't afford to waste time and effort chasing false positives, searching for vulnerabilities whenever a new threat alert appears, or conducting forensics to understand whether data has been compromised. They need to work together to drive faster, more secure innovation. Automation and modern delivery practices such as DevSecOps are key to this, but teams need to trust that their AI is reaching the right conclusions about the impact of a particular vulnerability. To accomplish this, organizations require a unified platform that can converge observability and security data to eliminate the silos between teams. By bringing their data together and retaining its context, DevOps and security teams can unlock the insights they need through causal AI. This enables them to harness intelligent automation to rapidly deliver high-performing and secure applications that delight their users."

Methdology: The report is based on a global survey of 1,300 CIOs and senior IT practitioners involved in DevOps management in large organizations with more than 1,000 employees, conducted by Coleman Parkes and commissioned by Dynatrace. The sample included 200 respondents in the US, 100 in Latin America, 600 in Europe, 150 in the Middle East, and 250 in Asia Pacific.

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Urgency Grows for Observability and Security Convergence

Organizations find increasing difficulty in maintaining software reliability and security as the demand for continuous release cycles and the rising complexity of cloud-native environments create more risk for undetected defects and vulnerabilities to escape into production, according to the 2023 Global CIO Report, Observability and Security Convergence: Enabling Faster, More Secure Innovation in the Cloud, from Dynatrace.

CIOs and senior DevOps managers are looking to DevSecOps processes, the convergence of observability and security, and the increased use of AI and automation to balance accelerated innovation with reliability and security.

The research reveals the following:

■ 90% of organizations say digital transformation has accelerated in the past 12 months.

■ 78% of organizations deploy software updates into production every 12 hours or less, and 54% say they do so at least once every two hours.

■ DevOps teams spend nearly a third (31%) of their time on manual tasks involving detecting code quality issues and vulnerabilities, reducing the time spent on innovation.

■ 55% of organizations make tradeoffs between quality, security, and user experience to meet the need for rapid transformation.

■ 88% of CIOs say the convergence of observability and security practices will be critical to building a DevSecOps culture, and 90% say increasing the use of AIOps will be key to scaling up these practices.

"It's difficult for teams to accelerate the pace of innovation while also maintaining the highest quality and security standards," said Bernd Greifeneder, Founder and CTO at Dynatrace. "More frequent software deployments, combined with complex cloud-native architectures, make it easier for errors and vulnerabilities to escape into production where they impact customer experience and create risk. There simply aren't enough hours in the day for teams to test code as thoroughly as when they had only a single monthly deployment, but there's no margin for error in today's ultra-competitive, always-on economy. Something has to change."


Additional findings from the survey include:

■ Organizations plan to increase their spending on automation across development, security, and operations by 35% by 2024, as they invest more in continuously testing software quality (54%) and security (49%) in production, automatic vulnerability detection and blocking (41%), and automating release validation (35%).

■ 70% of CIOs say they need to improve their trust in the accuracy of AI's decisions before they can automate more of the CI/CD pipeline.

■ 94% of CIOs say extending a DevSecOps culture to more teams is key to accelerating digital transformation and driving faster, more secure software releases.

"Organizations know that manual approaches aren't scalable," continued Greifeneder. "Teams can't afford to waste time and effort chasing false positives, searching for vulnerabilities whenever a new threat alert appears, or conducting forensics to understand whether data has been compromised. They need to work together to drive faster, more secure innovation. Automation and modern delivery practices such as DevSecOps are key to this, but teams need to trust that their AI is reaching the right conclusions about the impact of a particular vulnerability. To accomplish this, organizations require a unified platform that can converge observability and security data to eliminate the silos between teams. By bringing their data together and retaining its context, DevOps and security teams can unlock the insights they need through causal AI. This enables them to harness intelligent automation to rapidly deliver high-performing and secure applications that delight their users."

Methdology: The report is based on a global survey of 1,300 CIOs and senior IT practitioners involved in DevOps management in large organizations with more than 1,000 employees, conducted by Coleman Parkes and commissioned by Dynatrace. The sample included 200 respondents in the US, 100 in Latin America, 600 in Europe, 150 in the Middle East, and 250 in Asia Pacific.

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People want to be doing more engaging work, yet their day often gets overrun by addressing urgent IT tickets. But thanks to advances in AI "vibe coding," where a user describes what they want in plain English and the AI turns it into working code, IT teams can automate ticketing workflows and offload much of that work. Password resets that used to take 5 minutes per request now get resolved automatically ...

Governments and social platforms face an escalating challenge: hyperrealistic synthetic media now spreads faster than legacy moderation systems can react. From pandemic-related conspiracies to manipulated election content, disinformation has moved beyond "false text" into the realm of convincing audiovisual deception ...

Traditional monitoring often stops at uptime and server health without any integrated insights. Cross-platform observability covers not just infrastructure telemetry but also client-side behavior, distributed service interactions, and the contextual data that connects them. Emerging technologies like OpenTelemetry, eBPF, and AI-driven anomaly detection have made this vision more achievable, but only if organizations ground their observability strategy in well-defined pillars. Here are the five foundational pillars of cross-platform observability that modern engineering teams should focus on for seamless platform performance ...

For all the attention AI receives in corporate slide decks and strategic roadmaps, many businesses are struggling to translate that ambition into something that holds up at scale. At least, that's the picture that emerged from a recent Forrester study commissioned by Tines ...

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...