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How observability, application security, and AI enhance DevOps and platform engineering maturity

Dynatrace

DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior.

DevOps 181
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What is digital immunity? Creating secure, resilient software with observability

Dynatrace

According to one statistic, 76% of digital teams are responsible for delivering revenue , so software reliability and scalability are an increasing focus as these teams contribute to the bottom line. Today, software development teams use artificial intelligence (AI) to conduct software testing so they can eliminate human intervention.

Software 197
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Ensuring Performance, Efficiency, and Scalability of Digital Transformation

Alex Podelko

How is DevOps changing the Modern Software Development Landscape? , Marrying Artificial Intelligence and Automation to Drive Operational Efficiencies by Priyanka Arora, Asha Somayajula, Subarna Gaine, Mastercard. – Application of Artificial Intelligence to operations – as done at Mastercard.

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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

‘Composite’ AI, platform engineering, AI data analysis through custom apps This focus on data reliability and data quality also highlights the need for organizations to bring a “ composite AI ” approach to IT operations, security, and DevOps. Causal AI is critical to feed quality data inputs to the algorithms that underpin generative AI.

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Modern observability is no longer optional on the path to digital transformation

Dynatrace

With increased scalability, agility, and flexibility, cloud computing enables organizations to improve supply chains, deliver higher customer satisfaction, and more. That’s why teams need a modern observability approach with artificial intelligence at its core. “We The benefits of the cloud are undeniable.

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Why you need Dynatrace on Azure Workloads

Dynatrace

Operations: Responsible for ensuring flawless performance of the overall applications they support requires real-time, contextual data, powered by built-in Artificial Intelligence to avoid war rooms. Organic scalability of the monitoring platform with the applications. Strong integrations into common DevOps practices.

Azure 138
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Three ways intelligent automation can advance release validation and break down DevSecOps silos

Dynatrace

Moreover, the demand for rapid software delivery is putting additional stress on DevOps teams. Overall, 36% of respondents agreed that the silos among DevOps and security teams leads to a resistance to collaboration. A manual approach to release validation is not scalable for the demands of modern digital transformation.

DevOps 215