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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 189
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What is artificial intelligence? See how it differs from machine learning in IT ops

Dynatrace

Therefore, organizations are increasingly turning to artificial intelligence and machine learning technologies to get analytical insights from their growing volumes of data. Both machine learning and artificial intelligence offer similar benefits for IT operations. So, what is artificial intelligence?

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What is predictive AI? How this data-driven technique gives foresight to IT teams

Dynatrace

Therefore, the integration of predictive artificial intelligence (AI) in the workflows of these teams has become essential to meet service-level objectives, collaborate effectively, and boost productivity. Through predictive analytics, SREs and DevOps engineers can accurately forecast resource needs based on historical data.

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Technology predictions for 2024: Dynatrace expectations for observability, security, and AI trends

Dynatrace

That’s why many organizations are turning to generative AI—which uses its training data to create text, images, code, or other types of content that reflect its users’ natural language queries—and platform engineering to create new efficiencies and opportunities for innovation. Data indicates these technology trends have taken hold.

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The state of AI in 2024: Overcoming adoption challenges to unlock organizational success

Dynatrace

Artificial intelligence (AI) has revolutionized the business and IT landscape. As they continue on this path, organizations expect other benefits , from enabling business users to easily customize dashboards (54%) to building interactive queries for analytics (48%). This means greater productivity for individual teams.

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The path to achieving unprecedented productivity and software innovation through ChatGPT and other generative AI

Dynatrace

For example, it can help DevOps and platform engineering teams write code snippets by drawing on information from software libraries. Engineering teams will, therefore, always need to check the code they get from GPTs to ensure it doesn’t risk software reliability, performance, compliance, or security.

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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. Enter causal AI.