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Dynatrace Observability for Developers saves time with real-time data

Dynatrace

Developers are key stakeholders in modern observability. In this blog post, we will see how Dynatrace harnesses the power of observability and analytics to tailor a new experience to easily extend to the left, allowing developers to solve issues faster, build more efficient software, and ultimately improve developer experience!

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Create simple workflows to automate alerts during development

Dynatrace

Developers need a way to quickly set up alerts for targeted pre-production exceptions without incurring steep costs or heavy overhead. To orchestrate the different logging services, you use Fluent Bit to forward these logs to your centralized logging system, like Dynatrace. Ready to try Simple Workflows?

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Dare to debug production with Dynatrace Live Debugger

Dynatrace

Every software developer has faced the frustration of debugging. Developers deserve a seamless way to troubleshoot effectively and gain quick insights into their code to identify issues regardless of when or where they arise. With a single click, developers can access the necessary and relevant data without adding new code.

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How low-code/no-code AutomationEngine advances automated workflows

Dynatrace

To tame this complexity and deliver differentiated digital experiences, IT, development, security, and business teams need automated workflows throughout these cloud ecosystems. But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise.

Code 264
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Measuring Code Quality: Qualitative and Quantitative

DZone

Code Quality defines that the code is good, which means code is of high quality, and code is bad, which means code is of low quality. Code can be considered good quality if it is clear, simple, well tested, bug-free, refactored, documented, and performant.

Code 278
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New continuous compliance requirements drive the need to converge observability and security

Dynatrace

The Federal Reserve Regulation HH in the United States focuses on operational resilience requirements for systemically important financial market utilities. Proactive systems like Dynatrace’s Davis AI can automate responses to threats, swiftly implementing remediation while keeping executives informed of actions taken and their impact.

Analytics 289
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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly

The system is inconsistent, slow, hallucinatingand that amazing demo starts collecting digital dust. Weve seen this across dozens of companies, and the teams that break out of this trap all adopt some version of Evaluation-Driven Development (EDD), where testing, monitoring, and evaluation drive every decision from the start.

Systems 69