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Rethinking Programming: Automated Observability

DZone

Observability is the ability to understand the internal state of your system by looking at what is happening externally. In a software system, in order to acquire observability, we mainly implement the following aspects: logging, metrics, and tracing. This is mainly due to the added complexity of working with a distributed system.

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Real-Real-World Programming with ChatGPT

O'Reilly

The inspiration (and title) for it comes from Mike Loukides’ Radar article on Real World Programming with ChatGPT , which shares a similar spirit of digging into the potential and limits of AI tools for more realistic end-to-end programming tasks. Setting the Stage: Who Am I and What Am I Trying to Build?

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Dynatrace announces start of assessing its Dynatrace platform through IRAP

Dynatrace

In today’s fast-paced digital landscape, both public and private organizations need to stay focused on making sure their digital systems are secure. Stay tuned for more updates. Dynatrace exists to make software work perfectly. 

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Tech Transforms podcast: How one federal agency is embracing AI to support and empower its cyber workforce

Dynatrace

But if you don’t take the time to train the workforce in the programs or the systems you’re bringing online, you lose that effectiveness. Additionally, as the program gathers more data, it will enable predictive analytics to forecast future talent and skill deficits.

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Tech Transforms podcast: Navigating complex cloud environments and improving efficiency

Dynatrace

UK Home Office: Metrics meets service The UK Home Office is the lead government department for many essential, large-scale programs. When the UK Home Office first shut down these programs, the artificial intelligence-based tools had to adapt to the environment disappearing overnight. It also helps reduce the agency’s carbon footprint.

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Tech Transforms podcast: Government digital transformation and how agencies can balance innovation and security

Dynatrace

Specifically, we considered how to strike the right balance between embracing these advancements and safeguarding systems, data, and users. Agencies] are moving more sensitive data sets and systems into cloud environments because people are working remotely,” Nodurft said. Nodurft is the executive director of the Washington, D.C.

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Machine learning systems are stuck in a rut

The Morning Paper

Machine learning systems are stuck in a rut Barham & Isard, HotOS’19. In this paper we argue that systems for numerical computing are stuck in a local basin of performance and programmability. That said, after around 17 minutes Tensor Comprehensions does find a solution that outperforms a hand-tuned CUDA solution.

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