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RSA guide 2024: AI and security are top concerns for organizations in every industry

Dynatrace

In fact, according to the recent Dynatrace survey, “ The state of AI 2024 ,” 95% of technology leaders are concerned that using generative AI to create code could result in data leakage and improper or illegal use of intellectual property. In this blog, Carolyn Ford recaps her discussion with Tracy Bannon about AI in the workplace.

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Runtime vulnerability management is still a vexing challenge for organizations

Dynatrace

As a result, C-level executives say that cloud environments have bolstered cybersecurity challenges. Further, software development in multicloud environments introduces multiple coding languages and third-party libraries. According to the Dynatrace CISO report, organizations still lack the insight they need to monitor this code.

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OpenTelemetry enables automated operations management at scale

Dynatrace

The OpenTelemetry project was created to address the growing need for artificial intelligence-enabled IT operations — or AIOps — as organizations broaden their technology horizons beyond on-premises infrastructure and into multiple clouds. This is when the API library is referenced from the application code. Dynatrace news.

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How to fine tune failure detection

Dynatrace

Once the failure is detected, Davis our artificial intelligence engine will decide whether the issue should be reported or not. Automatic failure detection works well in most cases especially for web services and when developers follow good coding practices. Code. …. }. What about HTTP error codes?

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5 key areas for tech leaders to watch in 2020

O'Reilly

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. After several years of steady climbing—and after outstripping Java in 2017—Python-related interactions now comprise almost 10% of all usage.

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Structural Evolutions in Data

O'Reilly

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” But in its early form of a Hadoop-based ML library, Mahout still required data scientists to write in Java. Mental contortions led to code contortions led to frustration.