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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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Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

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2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

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